Package: afni-atlases Source: afni-data Version: 0.20180120-1.1 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_all.deb Size: 98215048 SHA256: b7b30ce4345671d92cb08f939b76de42f81a6839abe3d47dba1db0620fe64e0c SHA1: 792d6506cc866acfa54fc71475f823e686f169f7 MD5sum: deaddf5e6992face9b5edeb62644187c 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: aghermann Version: 1.1.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1585 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:3.0), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl2, libgtk-3-0 (>= 3.3.16), libitpp8v5, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 5.2), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.1.1-1~nd16.04+1_amd64.deb Size: 514928 SHA256: b89f724f495b2351f9adc3482851ea5c6217cdd0411b253c9d334ad00a17e3fc SHA1: 5e29a5129e00211cdf429ba0db3e3fcd1cb85f57 MD5sum: 04118e6ce11df5c69257dd8fa440a60a Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: ants Version: 2.2.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 359999 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.0), libinsighttoolkit4.9, libstdc++6 (>= 5.2) Recommends: environment-modules Suggests: fsl, gridengine-client, r-base-core Conflicts: gpe-conf Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_2.2.0-1~nd16.04+1_amd64.deb Size: 40511656 SHA256: 1c98ea3f17686a50e55e86564f1d37b4edf76b2594d511d697ab28780c1001f5 SHA1: c72430c1ec4d602757ee35d2e62940d030dfc34a MD5sum: dd9f97dbdfa6b1c78b27545e3195644f Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). . This package provides environment-modules configuration. Use 'module load ants' to make all cmdline tools available in your shell. Package: btrbk Version: 0.26.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 306 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv Homepage: http://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.26.0-1~nd16.04+1_all.deb Size: 85914 SHA256: 6b6405a88c6d3435f72248bd835614a7e087580868f255b291fd54ee33c1c1f9 SHA1: fa5140bc04c46578fa1aba3a20440df64f4525b0 MD5sum: 0baef24a5a91e68b27dbc093a194f2a3 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: cde Version: 0.1+git9-g551e54d-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1019 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd+1+nd16.04+1_amd64.deb Size: 146038 SHA256: eb56362a6b3ce0989408660070e532c3daf16c3c2b3370fa3f0a72482b65d6ac SHA1: 2f18dadcc4d3237870e8d22c399dc1001e0ac009 MD5sum: 3e45cf198b6c729ae80dd94f03474114 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cmtk Version: 3.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27134 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk5, libfftw3-double3, libgcc1 (>= 1:3.0), libgomp1 (>= 4.9), libmxml1, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_3.3.1-1~nd16.04+1_amd64.deb Size: 3812882 SHA256: 7bd11292411aa5591adfd6b713c87ec3e9a7e65c3ad9c35167bd304f4dd33ee6 SHA1: 4cecbd124bdca46f244790b49e499a952b345a00 MD5sum: 5061e29e36890eb9b9b21599c0be0d24 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cnrun-tools Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.1.0-1~nd16.04+1_amd64.deb Size: 17520 SHA256: 696816b47a80ace49369085919d567aaa0811146e427c2381d790464c2b3a3ba SHA1: 9b25b44d79a5f4343edd4e5b1c1c0ecf972b34cd MD5sum: 9ea4b4b3841514f19d814316fa3b7e5b Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16238 SHA256: 924a250e1bd7ec5712ba4e4d1b2a205ad154b72c7d38a5ecbd2fc0fccea19429 SHA1: ba5cbaaa726fc483256e9f5290e0149d81075b95 MD5sum: fea7b065cc3515413551b14dca22889d Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16248 SHA256: 4bead7f7bbc458cb62193c47d509c5542ccd6a78587e7b31b1e8044f9dfb0fa6 SHA1: 6e4eafa61b7512a8c44323d03cc98552d85e02a4 MD5sum: b44e2b9c8a82520233d2300f279d7ef5 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16250 SHA256: e3ba0b70729b2cf5a31e7520a8139429bee9ef72e77e8d7e5b8d91be52d14b40 SHA1: 1be8c0ca974ff69b8119b248d6c21fa48ce2dbec MD5sum: a6b3362321345b33de7f9c94f313ee55 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16242 SHA256: 1dd6eca6bc2317250e89af6c59c499f3b0bdd2caf7fde1edc3511dba3cc94046 SHA1: 6ab39f994bfa2d1e7f16f12a6f8d22e1b9900a9e MD5sum: 0628b2da9ac86ab37554bb2ea191b358 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: connectome-workbench Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48353 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.9), libosmesa6 (>= 10.2~), libqt5core5a (>= 5.5.0), libqt5gui5 (>= 5.2.0) | libqt5gui5-gles (>= 5.2.0), libqt5network5 (>= 5.0.2), libqt5opengl5 (>= 5.0.2) | libqt5opengl5-gles (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5widgets5 (>= 5.2.0), libqt5xml5 (>= 5.2.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.2.3.4) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.3.1-1~nd16.04+1_amd64.deb Size: 22030102 SHA256: 5fe1de0671efbb1f606f095c32cc5b8b2bfefb02b038513b1d9522416862c00b SHA1: bd6b9e234dc20be7d7031b92ad77b6442231c43b MD5sum: 6c7c71a110c12354f3fbc3abec412267 Description: brain visualization, analysis and discovery tool Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. Package: connectome-workbench-dbg Source: connectome-workbench Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198309 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.3.1-1~nd16.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.3.1-1~nd16.04+1_amd64.deb Size: 195433600 SHA256: 8037f0836d25776e0ca983b29f2e08d77b40f388bbd91e537a1fb40fafb1edd5 SHA1: c52dcb9c5f3bd2a87c8502b6647c0e5bc39abeff MD5sum: 963647572252b3aa9bca4c4709b5fe89 Description: brain visualization, analysis and discovery tool -- debug symbols Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. . This package contains debug symbols for the binaries. Build-Ids: a411a91dcb70588537a7bf135c161ac9f1e24b55 ee53b2846710a7202a56707b2b62c05b60175001 Package: convert3d Version: 0.0.20170606-1~pre1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 55873 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfftw3-double3, libgcc1 (>= 1:4.0), libgdcm2.6, libinsighttoolkit4.9, libqt5core5a (>= 5.0.2), libqt5gui5 (>= 5.0.2) | libqt5gui5-gles (>= 5.0.2), libqt5widgets5 (>= 5.0.2), libstdc++6 (>= 5.2) Homepage: https://sourceforge.net/projects/c3d/ Priority: optional Section: science Filename: pool/main/c/convert3d/convert3d_0.0.20170606-1~pre1~nd16.04+1_amd64.deb Size: 8539606 SHA256: 0e7fe140d45cb90a6b62ac0889b17997fcbb7a829ffd646019aebc00919b0921 SHA1: 875c7664cc966e46f83d4e0c818fe7c1a08fbd02 MD5sum: ce4dcac7259b3803e1a66642d9fd4fd4 Description: tool(s) for converting 3D images between common file formats C3D is a (command-line and GUI) tool for converting 3D images between common file formats. The tool also includes a growing list of commands for image manipulation, such as thresholding and resampling. Package: datalad Version: 0.10.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, python3-datalad (= 0.10.1-1~nd16.04+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_0.10.1-1~nd16.04+1_all.deb Size: 85000 SHA256: af3a7c52f85089cc7230aa25cc321605c4c28c16ce2213c2a1515f6a561ce1b9 SHA1: f5f7a55e488ff91dc03244c341c3b8db2a369c2a MD5sum: 3b9026f0c580ccf42c95dc73ff20eddd 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: dcm2niix Version: 1:1.0.20180614-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 630 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libyaml-cpp0.5v5 Homepage: https://github.com/rordenlab/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_1.0.20180614-1~nd16.04+1_amd64.deb Size: 162574 SHA256: 94ce69932e915da4c01312317597400fb909481843c1317e9c153e2c1b59ad63 SHA1: 964049c389d3661c346aafde5e043c9600afbfe5 MD5sum: 7b77c4e97286f4451e079f6fb919a42f Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd+1+nd16.04+1_amd64.deb Size: 38404 SHA256: 4fb44a4b64ebac715085eedc85f4b47ec9b8e642670af3ea6aac74ad3a1b717d SHA1: c80b3c636dcaae3c569696434d7d3e0fddc25544 MD5sum: b591bd9be2b09aef38c2a05fd449a773 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: docker-compose Version: 1.5.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 267 Depends: neurodebian-popularity-contest, python-docker (>= 1.3.0), python-dockerpty (>= 0.3.4), python-docopt, python-enum34, python-jsonschema, python-requests (>= 2.6.1), python-six (>= 1.3.0), python-texttable, python-websocket, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: docker.io (>= 1.6.0) Homepage: http://docs.docker.com/compose/ Priority: optional Section: admin Filename: pool/main/d/docker-compose/docker-compose_1.5.2-1~nd16.04+1_all.deb Size: 76930 SHA256: 316cea0fe5c368a1842c83370416a42eb29e3932fefa0d1465a86bd5dd6d8e49 SHA1: daabface947f49a630be5939805f0aa9706a4ce4 MD5sum: caa54173f115f40f815c49117eee989c Description: Punctual, lightweight development environments using Docker docker-compose is a service management software built on top of docker. Define your services and their relationships in a simple YAML file, and let compose handle the rest. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8117 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 7059424 SHA256: 3f090fdf3072e4e5b6ac524be1fff62f6d940c0e49f39e0843ba76d43e5b7d2b SHA1: 3f7081f142023ddee661a2980ff92df8a18bf7fe MD5sum: b9da13b2959435f2ec53d8cfda008794 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.9.7-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1274 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), init-system-helpers (>= 1.18~), lsb-base (>= 2.0-7) Recommends: python, iptables, whois, python3-pyinotify, python3-systemd Suggests: mailx, system-log-daemon, monit Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.7-1~nd16.04+1_all.deb Size: 263620 SHA256: b03d502cda5aa71922761c1df64c50cd71e07b59c6aca7556718d7ec6bc1cd80 SHA1: 8d69c55f37571cb94facc41de4d5d7385c5c6729 MD5sum: 8e61ce74c577ebf7d0af2a971ca61d7c Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd+1+nd16.04+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~nd+1+nd16.04+1_all.deb Size: 13946 SHA256: 98fec451744471ae6b47ee84ac52821b45ffd63401f9f29586a9aa6be46a8702 SHA1: 0fb8488befc01e715be4378c0affa5f4d8bce34c MD5sum: 7b7b1bf6546af8b8bcfa435171ebfc89 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: 0.15.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 239480 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-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_0.15.1-2~nd16.04+1_all.deb Size: 33200182 SHA256: 4c3e8ca647dc8f0fc28b0e143861bccdef60709a3ecf0ce91c9582f5383d4c82 SHA1: 142d9154407af64cac2affddba814d89edda29af MD5sum: 5d1da84a2444088f1bca4ea784d9fc38 Description: FSL image viewer Feature-rich viewer for volumetric (medical) images. Package: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6807 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.0), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 5.2), libvtk5.10, libvtk5.10-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-6~nd+1+nd16.04+1_amd64.deb Size: 1344678 SHA256: e63635f648e66f1ed1a8ce622bd7510aa5406dab67da1296ac9bf2ebe683dfc7 SHA1: 1ef5299926d994293e44554757b29d508c88482c MD5sum: 7a00919d11c047c4e4e3fd90add99cc8 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2930 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-6~nd+1+nd16.04+1_all.deb Size: 2227648 SHA256: d85f59cee9b040e9680c9817ee0e831d88dca517d2880029a7e9674aead08469 SHA1: 326b580203ce06c723591e460854d73845119293 MD5sum: 9b50fc95856220ca1a5876e4772eff2f Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1766 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.4.0-1~nd16.04+1_all.deb Size: 1669680 SHA256: 4a58773ebb4576609bd4161572178d94854997e74ff3145fb33e74ab97a987ff SHA1: e62edfdb9467c933ae868eb3630a0b9229c77b7e MD5sum: 2446d0cab9c54b99c87e2fee70e5cd85 Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: gifti-bin Source: gifticlib Version: 1.0.9-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgiftiio0, libnifti2 Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-2~nd16.04+1_amd64.deb Size: 23988 SHA256: e747b3a33acc82b419239d82691b01431cff7ee3c04b8fc0ae273e1323fd0d90 SHA1: 2127be32095878df9c41b533749853281e05569b MD5sum: 09f8bf29b791fb059048e03c3441d50d Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: git-annex-metadata-gui Version: 0.0.0~pre1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 60 Depends: neurodebian-popularity-contest, python3-git-annex-adapter, python3-pyqt5, python3:any (>= 3.3.2-2~) Homepage: https://github.com/alpernebbi/git-annex-metadata-gui Priority: optional Section: python Filename: pool/main/g/git-annex-metadata-gui/git-annex-metadata-gui_0.0.0~pre1-1~nd16.04+1_all.deb Size: 10326 SHA256: 84eae851a9a3219b0ed7e22c062b2c05f6fd614b11748324e085f8f96b0a76ef SHA1: 8aed7cf7c1092d4fe898927457e13bdc512a9176 MD5sum: 36389572dc0866a39d5897d8d1b275d3 Description: graphical interface to the metadata functionality of git-annex Flexible graphical user interface to view and manipulate metadata of git-annex repositories. Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: git-annex-standalone Source: git-annex Version: 6.20180523+gitg90dbb8968-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 178680 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, youtube-dl, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, adb, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Breaks: datalad (<= 0.9.1) Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20180523+gitg90dbb8968-1~ndall+1_amd64.deb Size: 62853064 SHA256: b3d33d54781909ac11e84a2b9317e977258f1310f19a9b3d860640737fa97f58 SHA1: 00acecad42b05d652a32c08019ede794ad65098e MD5sum: 0c2f282fad68a3db62b21c7ff083a649 Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: git-hub Version: 0.10.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Depends: neurodebian-popularity-contest, python, git (>= 1:1.7.7) Homepage: https://github.com/sociomantic/git-hub Priority: optional Section: vcs Filename: pool/main/g/git-hub/git-hub_0.10.3-1~nd16.04+1_all.deb Size: 34122 SHA256: f648dabac3d22d9594b73d0981f146638cd0fb011a163b5640dce71b1c2fddff SHA1: 92b5c34727ed27f277544db7dc276f31f1ddfd54 MD5sum: fd17abf7b6323d8b898c55b3a1af3c75 Description: Git command line interface to GitHub git hub is a simple command line interface to GitHub, enabling most useful GitHub tasks (like creating and listing pull request or issues) to be accessed directly through the Git command line. . Although probably the most outstanding feature (and the one that motivated the creation of this tool) is the pull rebase command, which is the rebasing version of the GitHub Merge (TM) button. This enables an easy workflow that doesn't involve thousands of merges which makes the repository history unreadable. . Another unique feature is the ability to transform an issue into a pull request by attaching commits to it (this is something offered by the GitHub API but not by the web interface). Package: golang-github-ncw-rclone-dev Source: rclone Version: 1.36-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 1198 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-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 Built-Using: go-md2man (= 1.0.6+ds-1), golang-1.7 (= 1.7.4-2), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-blackfriday (= 1.4+git20161003.40.5f33e7b-1), golang-github-aws-aws-sdk-go (= 1.1.14+dfsg-2), golang-github-davecgh-go-spew (= 1.1.0-1), golang-github-go-ini-ini (= 1.8.6-2), golang-github-google-go-querystring (= 0.0~git20151028.0.2a60fc2-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-ncw-go-acd (= 0.0~git20161119.0.7954f1f-1), golang-github-ncw-swift (= 0.0~git20160617.0.b964f2c-2), golang-github-pkg-errors (= 0.8.0-1), golang-github-pkg-sftp (= 0.0~git20160930.0.4d0e916-1), golang-github-pmezard-go-difflib (= 1.0.0-1), golang-github-rfjakob-eme (= 1.0-2), golang-github-shurcool-sanitized-anchor-name (= 0.0~git20160918.0.1dba4b3-1), golang-github-skratchdot-open-golang (= 0.0~git20160302.0.75fb7ed-2), golang-github-spf13-cobra (= 0.0~git20161229.0.1dd5ff2-1), golang-github-spf13-pflag (= 0.0~git20161024.0.5ccb023-1), golang-github-stacktic-dropbox (= 0.0~git20160424.0.58f839b-2), golang-github-tsenart-tb (= 0.0~git20151208.0.19f4c3d-2), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-go.crypto (= 1:0.0~git20170407.0.55a552f+REALLY.0.0~git20161012.0.5f31782-1), golang-golang-x-net-dev (= 1:0.0+git20161013.8b4af36+dfsg-3), golang-golang-x-oauth2 (= 0.0~git20161103.0.36bc617-4), golang-golang-x-sys (= 0.0~git20161122.0.30237cf-1), golang-google-api (= 0.0~git20161128.3cc2e59-2), golang-google-cloud (= 0.5.0-2), golang-testify (= 1.1.4+ds-1), golang-x-text (= 0.0~git20161013.0.c745997-2) Homepage: https://github.com/ncw/rclone Priority: extra Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.36-1~ndall0_all.deb Size: 201776 SHA256: 88274c394a26a9f8f5f4766873acde54192537112e0f0e24ddfff1b9a5361f7c SHA1: fb44d37c3df4bdf641c85720b35bbfd835870a05 MD5sum: fdc9cfc7b0a9e18cdc83ed2fbce61433 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~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 198 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~nd16.04+1_all.deb Size: 46456 SHA256: 268fc22cd72361d7a39e3dfdaae20bafe2c869946482b390a957557cb13389b2 SHA1: ff216541e749476659f01d82cfcd7c146e5b9480 MD5sum: 3fdd28a1cdbca6eecde1a1d168211fc1 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: htcondor Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 12761 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.9~dfsg.1-2~nd16.04+1), perl, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:3.0), libglobus-callout0 (>= 3), libglobus-common0 (>= 16), libglobus-ftp-client2 (>= 7), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 6), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 9), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 11), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 5), libgsoap8, libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.13~alpha1+dfsg), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libltdl7 (>= 2.4.6), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libx11-6, zlib1g (>= 1:1.1.4) Recommends: dmtcp, ecryptfs-utils Suggests: docker, coop-computing-tools Breaks: condor (<< 8.0.5~) Replaces: condor (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: science Filename: pool/main/c/condor/htcondor_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 3637848 SHA256: 5d2141f7c912b73710e0d5e3d1c455b74d22419aaf70f2f61da854dac3abacd3 SHA1: 96c92b2571ffa429d8fab57988a9fca0e47663d1 MD5sum: 604be40c3448e9369705b6760163a6a5 Description: distributed workload management system Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package can set up an appropriate initial configuration at install time for a machine intended either as a member of an existing HTCondor pool or as a "Personal" (single machine) HTCondor pool. Package: htcondor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 31973 Depends: neurodebian-popularity-contest, htcondor (= 8.4.9~dfsg.1-2~nd16.04+1) Breaks: condor-dbg (<< 8.0.5~) Replaces: condor-dbg (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: debug Filename: pool/main/c/condor/htcondor-dbg_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 29808680 SHA256: 0f0e54ab4544c54c47bbf28aba2aa82d58b8852da6b59f824b27582fbe16acea SHA1: 3e8508d8b692a36a4eb3bcf16e951c776e67de73 MD5sum: bc1e3a9b7decb256253955e54347adff Description: distributed workload management system - debugging symbols Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for HTCondor. 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Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of HTCondor add-ons. Package: htcondor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6108 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 1065712 SHA256: e19399294a01d36957e0481ff5a7548b187099d290ec5f968f110a127abb8230 SHA1: 94b6487128920243d3dc94a1943da0a3a3aabe2e MD5sum: 2bca3f07fbb7d1bfcf4f285102560861 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.12.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 468 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil, mupdf-tools (>= 1.5) | xpoppler-utils Recommends: mplayer, ffmpeg, pdftk, perl, xdg-utils Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.12.0-1~nd16.04+1_all.deb Size: 184484 SHA256: a361ba7f168ba3950af9201f894ff8fc21d251adb7aa661ea96b6474ee66f53a SHA1: b35ed36286e28a70d95e9fc3ebcc63b864c3aef7 MD5sum: 66a33c4406dc411682ae4962455c177c Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 39 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd+1+nd16.04+1_all.deb Size: 9092 SHA256: 3768f288d0fb7988e227131b3e41a31c00436992b06d2b18e8113e0db08835c0 SHA1: 65c2eeeeb2ec075ec99aecec567a613b9ed2343c MD5sum: 4ff78d0c6fe0960cbf435512258152c0 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 5088 SHA256: 5336188e50c28a623d14ce0305ec77a4efef641cdef4c53c5e52157daf080def SHA1: 3ec074921fdde47d6c380e07226bacd940068f41 MD5sum: 349af0ebe53b5ed02810a3874940a35c Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 419 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1), libboost-program-options1.58.0, libc6 (>= 2.14), libfftw3-single3, libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 121502 SHA256: 78302d6acdcf63e8083196cc0edd2f0a98d7204d8f816753b250d027125383a4 SHA1: 8f50df9dca9e2dbf195d8bb277ae7aea5a6131d7 MD5sum: 3f44b7ab42956260ceb8b5c4571295b5 Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: jasp Version: 0.8.1.0~dfsg.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 39454 Depends: neurodebian-popularity-contest, libarchive13, libboost-filesystem1.58.0, libboost-system1.58.0, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libqt5core5a (>= 5.5.0), libqt5gui5 (>= 5.0.2) | libqt5gui5-gles (>= 5.0.2), libqt5network5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5webkit5 (>= 5.0.2), libqt5widgets5 (>= 5.2.0), libqt5xml5 (>= 5.2.0), libstdc++6 (>= 5.2), libjs-marked, r-base-core, r-cran-afex, r-cran-bayesfactor, r-cran-car, r-cran-effects, r-cran-hypergeo, r-cran-lme4, r-cran-logspline, r-cran-rjson Recommends: r-cran-ggplot2, r-cran-lsmeans, r-cran-plotrix, r-cran-rcpp, r-cran-rinside, r-cran-vcd, r-cran-vcdextra Homepage: https://jasp-stats.org Priority: optional Section: science Filename: pool/main/j/jasp/jasp_0.8.1.0~dfsg.1-1~nd16.04+1_amd64.deb Size: 32435662 SHA256: 17854c1240cbf2b30ae44533b017a1ebe1d0f572c85f1d5781128e0bd55dcfc3 SHA1: 7c4444d1ff94831d91febf10604c150e16ab4a13 MD5sum: 94ceb04d79a0a642a43b21ba0b09895e Description: Bayesian statistics made accessible This is a statistics package with a graphical user interface. Its authors consider it "a low fat alternative to SPSS, a delicious alternative to R. Bayesian statistics made accessible." Package: libclassad-dev Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1424 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.9~dfsg.1-2~nd16.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 238644 SHA256: 771069e1091c3edfa6f04bdd913f97be744e18c34d1af50a48ba7a411bdb0ff0 SHA1: 1da0e2ab4efdb67f80b74b7f8733d081d5b5d732 MD5sum: af5b65814028b65fbd361d4a14975967 Description: HTCondor classads expression language - development library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the static library and header files. Package: libclassad7 Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libpcre3, libstdc++6 (>= 5.2) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 190090 SHA256: 4c4d77a15f17d724601cf716e469d7b79eb43297b55f47e0d09f4a496f1e1c76 SHA1: 837d8053eee9ac83e5ce38cae3815b29c4bab1db MD5sum: 05febdb72ac20a805505a3438517db6c Description: HTCondor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libcnrun2 Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 288 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.1.0-1~nd16.04+1_amd64.deb Size: 81750 SHA256: ab2507bba9fc94472bc3556029aa8aded42c2a114eecb3c8482325878aeb7277 SHA1: 044fc9dcef7d9383a30fcc66d6d059f9f276ad9c MD5sum: 51e5e9b1b5d5066069e7b926cc2f7450 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.1.0-1~nd16.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.1.0-1~nd16.04+1_amd64.deb Size: 21456 SHA256: e7717c4aa14384368315e7aef433db18cee3ca84767b6b47c9c44a716134e69a SHA1: 97b6a31218649f77d29f2663ebbf472858797eab MD5sum: 54e7caa3886938d0a2846fbc96a16c85 Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libdrawtk-dev Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 40838 SHA256: f5feeff6952ddeb62dd87daf609d42a85fd1256793c02cff655a28c5c1135527 SHA1: 25c2d35f4e1bcce2638318b5dd68f1779ac56b6c MD5sum: 732f85a397a9c47b3ecf6d33e0237aed Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), libfontconfig1 (>= 2.11.94), libfreeimage3, libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.11) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 22950 SHA256: a4ec511db2ae929dca64942b19dde14e37cc930fbba040f3540fc05c2350fb89 SHA1: ef54e9475cb903a84c59f9205712fe358ad3dbbb MD5sum: a9c93cacded8f138c4be6762e3626d06 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 78044 SHA256: 2c4fb8f4d282ef67ab0f9a567faa2500c17c5c84abfc554680619e038658e98a SHA1: 6fc79165c562d2cabf4a83e7d168a9f8e50d2813 MD5sum: 35283c42813f7ba96f1f23cd7f1b2276 Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Build-Ids: c41828d10c9804b856f1c119e946fc5911d6ba88 Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 241 Depends: neurodebian-popularity-contest, libgiftiio0 (= 1.0.9-2~nd16.04+1), libnifti-dev Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-2~nd16.04+1_amd64.deb Size: 48078 SHA256: 3b014f691cbadbf00928c69469d12c862bccd74bba477cd0f9c51f7cb9b71a28 SHA1: 7ad1d6a648cbcea8f2fd8fec845bd76cbecfe0c9 MD5sum: 0d267b3b0fc5afeb236be4cd9907fe23 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 163 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libexpat1 (>= 2.0.1), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-2~nd16.04+1_amd64.deb Size: 45444 SHA256: 3cde981845a3276d1a1a822b4561cc5a160c18e14bcd1a54e0e5a9560da85cc9 SHA1: 75bf597569627dd9b6a7db7d2518994aa8f43471 MD5sum: 68cb690520175f5c3cd0f288ec695da0 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 13854 SHA256: fce1dcfd5beb5df399ccfb6498202a50a40e0064d01475991f1704a427d2170a SHA1: 02fdb706e684aa870a2a9e72a4c977d1446e85c9 MD5sum: 4381a6b43e5c57caa311110668c0ce39 Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1961 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 157932 SHA256: 2f24afbb9b3936557b75c9f69827bad728cd057e3a34aac31466f47d948cb216 SHA1: accfe2ca334b0b97c931424db47de6e435fae5f7 MD5sum: f81b7692ba25e05413fe88a248cc60a4 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libhdf5-10, libpugixml1v5 (>= 1.4), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 77426 SHA256: 4f6d5e547780343ed4e69c90cc6758d33dd63726c043cfb2f9aedb8e4fac976c SHA1: 534f1d6d4992eadf722ca065ddc80d68a863133e MD5sum: b833217e3b785a0eec90d15a348a51f0 Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 719 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 141804 SHA256: 94288ad8b34fc9e5153c428b991bb393ceb4639f25155e419474d6e7dc5d73ab SHA1: 3ea2e3e1d120cfe2ced2b587f4b52e9a3f6778cf MD5sum: 5f1fe237ba0bfa83ebbf919e677b3488 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 517 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 140886 SHA256: 609bc6cbce66ff9dfb18a6bf219eb48b0843e6668cb05464b95c4a0dec57a9a9 SHA1: b8866c2e347c0a7732ac1aa24453fdb4db5510b5 MD5sum: 75fdd8f2faf079608577afd2e9315aa4 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1274 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 328612 SHA256: c8f1275c4aacd25a2468ce435b019ffd5061444d29abb8288a60ff869e9bc12b SHA1: 8798dafcffac3fd5625874b3109acdcfa435e74d MD5sum: fc61b3041dbf76ab8dc9baff10c7c159 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 277 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74226 SHA256: 23c4508e06435a593df82eb7ce2ed01fb266f8a181cda9ceae84b95f61f82190 SHA1: 38662d93b0426d0f1fcb71df41cd78d4bd59ed8f MD5sum: 3984760e7a13df1cd289e15835d484ab Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1786 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdcm2.6, libstdc++6 (>= 5.2), libvtk5.10, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 445290 SHA256: a6f8e6f152d55de7e111d1725d33fc240ed5d63e543288fc46f23c57114c7dd4 SHA1: 489f5ae091cc6574ac92c344cad671eea9a48741 MD5sum: 2316cc705030caf3896c8e1dd4be9d2c Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 565 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd+1+nd16.04+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 81110 SHA256: 4834857f522b21905239609c60952b1baf8cd1032446672eca6954a03b6776cb SHA1: 4c3664ff72f9f8264fc222c34bc8ec8d8dc2cdb1 MD5sum: 329447cfc41445c3f1f55dc28448c1e5 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 121 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.1.0-1~nd16.04+1_amd64.deb Size: 38584 SHA256: f31e8033fb730dca87770aaf79f3eac103ca44048f87d8b9f95b80b193a94bc1 SHA1: ff26d2fa039288d579561c3a3a3da1e282475f11 MD5sum: a23b0e78c025f6efbe1327820ad6351d Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.4-2~), libglib2.0-0 (>= 2.41.1), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 68744 SHA256: e6edea5d6279b95758d3d8fcef82495d58ba2d0f79cdb52b50efcfd096a8dc36 SHA1: 37aa16f4e74dbbf39a3591d3d351dc18cf070c7c MD5sum: d8cfe7b9bc985019b8a2a6c250623148 Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd+1+nd16.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 160232 SHA256: f8215de9087fcd45d680f4c99bdbb04b68e9f52eb5bb7a08ecc352e41708753f SHA1: 2923ca8c1a2f24708c36bc3dcd0fab49f8bf8eef MD5sum: fe81542df04c8f3de1ac5730f5b41b56 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Build-Ids: 70b701f30b49c51e532be8647e4165bee8a3bae2 Package: mridefacer Version: 0.2-1~nd16.04+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~nd16.04+1_all.deb Size: 637352 SHA256: 77d8497006f219516a5d682f4dcbc432cafef37779349576a55adc80daea7509 SHA1: f5e58b7c8b273455ab745b500c367c0747692c56 MD5sum: 11a7610ad8e894687feae0d8b5a6c618 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: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd+1+nd16.04+1_amd64.deb Size: 31150 SHA256: 044e5be3e9c3d37d3d9b6d7277091323144dbcaf24a6fa473d2280d9649bf38e SHA1: 9a9e2c6319c86b91d886207a1dfb6609b10dc572 MD5sum: 5fe7ee1c9d627c00f7606510809930cf Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd+1+nd16.04+1_all.deb Size: 16814 SHA256: 22e5cc29f87c08ceb667084f2af3810aaefd1b5fc0828b2f0b0e29cb2a4dc46e SHA1: 90467c75aaba4e464a72ac39884410acc60cfc49 MD5sum: 60f499833563a70a8dc586c029092380 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 91 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.5~nd16.04+1_all.deb Size: 34692 SHA256: a782eeb34e4e6c636517778c4ff979c12e9a230fbcedb23c122e7002655b6451 SHA1: 9315d5405e9604f9b7d20f83240b5d9b4097c9c1 MD5sum: 918d375cf39b03b83676ed89631ea9dd Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: gnupg2 | gnupg, dirmngr Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.5~nd16.04+1_all.deb Size: 10378 SHA256: 43d94888c0bbb446b9f2a2d796441b71067126e5152efa50ae52bf6f0d70b829 SHA1: d8c7b1b10beaf2c54d021faddc31b0db56812875 MD5sum: e0c8f57ee231061ca4f5cbe445371af8 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.5~nd16.04+1_all.deb Size: 116402 SHA256: 338f1476f9040ead6f5c01c581e3a3b8ed847592f4fdd441d358f7a9188bcc79 SHA1: 3f92954e7fcb8dd6435b6a99da191290c314b689 MD5sum: c732398e4e41daae5a5a16883ef5c9d0 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.5~nd16.04+1_all.deb Size: 32768 SHA256: b607a59ddd213529a6b7074dcb368280f9f0f04a19e42dab4cdb5cbc919f0d58 SHA1: a04beb5d390f0d731f625291fec9831e24fe4931 MD5sum: 7de749bf47072b733c9696f9e5110c3e Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.5~nd16.04+1_all.deb Size: 12380 SHA256: 9206f3a429df0b39a73d49bea5cb2979721e3a00ab38ebe53e0cc08ffe5a0fef SHA1: da69b2b40f9dccd606151011bdf9680ac1fa9a8e MD5sum: c7ff04f1195fe0fe3d15bc072dce04f8 Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.5.29.4+ds-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6842 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_0.5.29.4+ds-1~nd16.04+1_all.deb Size: 732742 SHA256: f3f92f46c7d7d1af63c9e37dd6bc0104cd4ff696725e09f78a93515b73362805 SHA1: 66de4bd24313c93cb41f9824c4015f017f91e1ff MD5sum: 5bf08149e606d084148bbfa504dbf34f 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: numdiff Version: 5.9.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 917 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.9.0-1~nd16.04+1_amd64.deb Size: 593000 SHA256: c88dea57b7315d45691ad3547cbf687b311cb49852a9fda8a0a460b3d04b1b22 SHA1: 68c44319932580a06875dacaac09ab5b3320fbe4 MD5sum: 097538322dbbc85ac876937de690bdb4 Description: Compare similar files with numeric fields Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4766 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.0.0), liboctave3, libopenal1 (>= 1.14), libpciaccess0 (>= 0.10.7), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3 (>= 1:5.0), libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.4.0), libxxf86vm1, psychtoolbox-3-common (= 3.0.14.20180526.dfsg1-1~nd16.04+1), psychtoolbox-3-lib (= 3.0.14.20180526.dfsg1-1~nd16.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics, octave-pkg-dev Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.14.20180526.dfsg1-1~nd16.04+1_amd64.deb Size: 936484 SHA256: b9b663c0bb44040a326fc1c6e40a9f9c2a096dbd55b2610ced25dc5b1ec66437 SHA1: e0471bfe082d63e848a9069c1acb7143dd323000 MD5sum: 51848c40f41e7d153c6b4b2a5400cf6c Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: openstack-pkg-tools Version: 52~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, autopkgtest, libxml-xpath-perl, madison-lite, pristine-tar Priority: extra Section: devel Filename: pool/main/o/openstack-pkg-tools/openstack-pkg-tools_52~nd16.04+1_all.deb Size: 52268 SHA256: ce9a5f309792b3a87d6f8c00259b993da4eae392c3cd59c2d63acb6640964cc5 SHA1: 9b2978d36e9fe7878444813081916d17fc5178d1 MD5sum: 421e6c2753576c0ad60b3b768f92362c Description: Tools and scripts for building Openstack packages in Debian This package contains some useful shell scripts and helpers for building the Openstack packages in Debian, including: . * shared code for maintainer scripts (.config, .postinst, ...). * init script templates to automatically generate init scripts for sysv-rc, systemd and upstart. * tools to build backports using sbuild and/or Jenkins based on gbp workflow. * utility to maintain git packaging (to be included in a debian/rules). . Even if this package is maintained in order to build OpenStack packages, it is of a general purpose, and it can be used for building any package. Package: p7zip Version: 16.02+dfsg-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 853 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Suggests: p7zip-full Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip_16.02+dfsg-1~nd16.04+1_amd64.deb Size: 339260 SHA256: afc271ce5ccbdfd2c37da631535b7fddef7df63d3dfbd64bc0a1895f2f868d9c SHA1: f42d0a4f91e4e3e6cce27b2e8c4ea8ad50337d62 MD5sum: b7ad4745b81248a4d91da2db8b3f2355 Description: 7zr file archiver with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip provides: - /usr/bin/7zr a standalone minimal version of the 7-zip tool that only handles 7z, LZMA and XZ archives. 7z compression is 30-50% better than ZIP compression. - /usr/bin/p7zip a gzip-like wrapper around 7zr. . p7zip can be used with popular compression interfaces (such as File Roller or Nautilus). . Another package, p7zip-full, provides 7z and 7za which support more compression formats. Package: p7zip-full Source: p7zip Version: 16.02+dfsg-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4235 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd16.04+1), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Suggests: p7zip-rar Breaks: p7zip (<< 15.09+dfsg-3~) Replaces: p7zip (<< 15.09+dfsg-3~) Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip-full_16.02+dfsg-1~nd16.04+1_amd64.deb Size: 1166002 SHA256: c3b43506d10c326e80eb194eba855922dbdf8f16e5a5b368b0283a0d5833da4a SHA1: e3dccde72ac6dde99a16779b41d426caf363ca24 MD5sum: c6a3222617b4e36bb983a6ec1ed235b7 Description: 7z and 7za file archivers with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip-full provides utilities to pack and unpack 7z archives within a shell or using a GUI (such as Ark, File Roller or Nautilus). . Installing p7zip-full allows File Roller to use the very efficient 7z compression format for packing and unpacking files and directories. Additionally, it provides the 7z and 7za commands. . List of supported formats: - Packing / unpacking: 7z, ZIP, GZIP, BZIP2, XZ and TAR - Unpacking only: APM, ARJ, CAB, CHM, CPIO, CramFS, DEB, DMG, FAT, HFS, ISO, LZH, LZMA, LZMA2, MBR, MSI, MSLZ, NSIS, NTFS, RAR (only if non-free p7zip-rar package is installed), RPM, SquashFS, UDF, VHD, WIM, XAR and Z. . The dependent package, p7zip, provides 7zr, a light version of 7za, and p7zip, a gzip-like wrapper around 7zr. Package: patool Version: 1.12-3+nd1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 410 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python3:any (>= 3.4~) 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~nd16.04+1_all.deb Size: 37618 SHA256: 0185d18529fd526bf7e8865eca4f5b5414817046fb05bcc5305051b1d05a2287 SHA1: f28dbad483daffbf49ad9886f973e93bed945e6d MD5sum: 8dc28ec1f82fba6b44c1130832e66dbd 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: prov-tools Source: python-prov Version: 1.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, python3:any (>= 3.3~), python3-prov (= 1.4.0-1~nd16.04+1) Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/prov-tools_1.4.0-1~nd16.04+1_all.deb Size: 6446 SHA256: bdbee846a60a80a04461221ce243e1d122e6487696020fee2bc8a9eb4daa20bf SHA1: d4ca2cf1ddc0c1064c702378baec913c7a0be031 MD5sum: 6d7dbfa568d26547c324f3bcff31e0d9 Description: tools for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the command-line tools for the prov library. Package: psychopy Version: 1.85.3.dfsg-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15994 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-requests, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython, python-future Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.85.3.dfsg-1~nd16.04+1_all.deb Size: 6618940 SHA256: 27c6237091516aa46f7ff786230efdd638bcdb0007a16e4139bfbb69ce7b1b7e SHA1: bb3a846e10fafc823913898101b51e7badcbff64 MD5sum: f88081f84ee6557285239f39cfd17883 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd16.04+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~nd16.04+1_all.deb Size: 24458728 SHA256: cb7a14d5c5bf0659d9df06a087dbbb418306d97face464430a1b0849d4a21931 SHA1: 08ee0a4edbfe109831e2662f8414b9ebc782299e MD5sum: 5edf33326dcfa8281d17b2025efbee4a Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3894 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.14.20180526.dfsg1-1~nd16.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.14.20180526.dfsg1-1~nd16.04+1_amd64.deb Size: 742724 SHA256: 2fb8048b703509a65bda2a7322d1c94f80c11c9f8192dac75a3536186cd0115e SHA1: 604a8b754bf22be561c10a11d6737b4be860d134 MD5sum: 303c8453c47974a2672150bb3c65bb9f Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.11.94), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.14.20180526.dfsg1-1~nd16.04+1_amd64.deb Size: 73626 SHA256: 40539b9f41495caabba7b411784fd72294983a243e3d65d683d75673f73a10a3 SHA1: eb4e1e1e174bbe4c13836d6a1316f441888d016f MD5sum: fe2d4265a4908febac7ca6853422d96a Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: pypy-hypothesis Source: python-hypothesis Version: 3.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 386 Depends: neurodebian-popularity-contest, pypy-enum34, pypy Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/pypy-hypothesis_3.6.0-1~nd16.04+1_all.deb Size: 70086 SHA256: 107d15e7462f80624f5eec39a65f3db0ac8f1b3d6f9dc18d0f4bab69441dffd6 SHA1: 5fad1e5f0f66c35bf6865eee9b89d8f1e2e32003 MD5sum: 7b841c7aa1ddc645501e9b63427b89ea 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: pypy-json-tricks Source: json-tricks Version: 3.11.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, pypy Homepage: https://github.com/mverleg/pyjson_tricks Priority: optional Section: python Filename: pool/main/j/json-tricks/pypy-json-tricks_3.11.0-1~nd16.04+1_all.deb Size: 18858 SHA256: 680fddf2f25611f156874ec5faa6b7b595291c3104fb49db8ac45d3598d0c6f4 SHA1: 097d9090a239d4288420b08a270a4694e0be60f5 MD5sum: dcfbbbd8982bd499d79045ddc6202632 Description: Python module with extra features for JSON files The json_tricks Python module provides extra features for handling JSON files from Python: - Store and load numpy arrays in human-readable format - Store and load class instances both generic and customized - Store and load date/times as a dictionary (including timezone) - Preserve map order OrderedDict - Allow for comments in json files by starting lines with # - Sets, complex numbers, Decimal, Fraction, enums, compression, duplicate keys, ... . This package provides Python3 module. Package: pypy-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, pypy Suggests: pypy-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/pypy-pkg-resources_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 111986 SHA256: a46960af40580a044791897da065b2134da92f6d08d8ec79d1f33deeb625ecc0 SHA1: dac82101358b768239ad58198ddb5026edd9d48a MD5sum: a0c65b88155a87713bb05df6d5d6d571 Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: pypy-py Source: python-py Version: 1.4.31-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, pypy, pypy-pkg-resources Suggests: subversion, pypy-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/pypy-py_1.4.31-2~nd16.04+1_all.deb Size: 82320 SHA256: 8f9a86a093a652dd90c1f5c9c5e0a5ea8fbfc982fab835a965029fc36e85f123 SHA1: 58774cbf15de9d824528961f26c28db4c7e3b004 MD5sum: 09b9d8ba0ae2193fc758c6b3aed02782 Description: Advanced Python development support library (PyPy) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the PyPy 2 modules. Package: pypy-pytest Source: pytest Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 600 Depends: neurodebian-popularity-contest, pypy-pkg-resources, pypy-py (>= 1.4.29), pypy Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/pypy-pytest_3.0.4-1~nd16.04+1_all.deb Size: 136092 SHA256: d33dfeeb58239ad6c8688e0dc8a20c61f85d52f44ec2c09cb50aaa37e7d4ddfa SHA1: aa54b5c6064c48a84fe956b64531abb42494f9be MD5sum: 6a035f11b30459b792627e5d5b6cd712 Description: Simple, powerful testing in PyPy This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the PyPy module and the py.test-pypy script. Package: pypy-setuptools Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 431 Depends: neurodebian-popularity-contest, pypy-pkg-resources (= 20.10.1-1.1~bpo8+1~nd16.04+1), pypy Suggests: python-setuptools-doc Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/pypy-setuptools_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 121934 SHA256: 1bb6cba9bde6ce0c1d41ecaa37e8ed9ef9f752fc1c3b129e8ba537b8c951deea SHA1: cfdd22d42984b1473f6dd9b5626cb0d36e93b036 MD5sum: aa12a9636bd95f3d3331dc4481c41e7c Description: PyPy Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: pypy-six Source: six Version: 1.10.0-3~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 50 Depends: neurodebian-popularity-contest, pypy Multi-Arch: foreign Homepage: https://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/pypy-six_1.10.0-3~bpo8+1~nd16.04+1_all.deb Size: 11734 SHA256: c6109c0e56ee0185b0c2b2048d80d4dfca1e54794fed44cdea78cdbe50421e43 SHA1: 8474dde97e39637f12c220ea65ebe06ea9b2cdc3 MD5sum: 374add4c5e6975ab260bb266f76abaaf Description: Python 2 and 3 compatibility library (PyPy interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the PyPy module path. It is complemented by python-six and python3-six. Package: python-argcomplete Version: 1.0.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 24608 SHA256: 156b7dbfd8a99d398fe740c822ba51762781af630c9ce000cdebb5622fe4cd2a SHA1: 937a26dd82a75e4b14bb613ae8f6dd187ee9e10b MD5sum: 3f721e38ee6f5930587547ae87875163 Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-boto Version: 2.44.0-1~nd16.04+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~nd16.04+1_all.deb Size: 741840 SHA256: 843bef9704cfe6735a962ea2335da8cc9f53aa5d9655f6275b4ccc5d7ad2617b SHA1: e77a184c34c4f77730c4affca3692157df265a32 MD5sum: c29670c509c00b01a5eec8e607b86efa 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-boto3 Version: 1.2.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 720 Depends: neurodebian-popularity-contest, python-botocore, python-concurrent.futures, python-jmespath, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-requests, python-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python-boto3_1.2.2-2~nd16.04+1_all.deb Size: 58388 SHA256: 7b073c2e5bedfe1fb511389140c06e6bc7d763b8506c840f4bfeff826468834f SHA1: d557ed14ac3dcfc1d3e3185437b8a28c852a6442 MD5sum: 07ba3320ddb3a4001a9efaf1405a73f5 Description: Python interface to Amazon's Web Services - Python 2.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python-chardet Source: chardet Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 411 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Homepage: https://github.com/chardet/chardet Priority: optional Section: python Filename: pool/main/c/chardet/python-chardet_3.0.4-1~nd16.04+1_all.deb Size: 80994 SHA256: 78ba0e0c7f95ccdd8307eed219451ae14f93cda37c266f3444c6086e4f07f3bf SHA1: b93381386404d27619816e0b47f8a31ee3b26ab2 MD5sum: 55c5e2f95c768b125e9a2930885effd9 Description: universal character encoding detector for Python2 Chardet takes a sequence of bytes in an unknown character encoding, and attempts to determine the encoding. . Supported encodings: * ASCII, UTF-8, UTF-16 (2 variants), UTF-32 (4 variants) * Big5, GB2312, EUC-TW, HZ-GB-2312, ISO-2022-CN (Traditional and Simplified Chinese) * EUC-JP, SHIFT_JIS, ISO-2022-JP (Japanese) * EUC-KR, ISO-2022-KR (Korean) * KOI8-R, MacCyrillic, IBM855, IBM866, ISO-8859-5, windows-1251 (Cyrillic) * ISO-8859-2, windows-1250 (Hungarian) * ISO-8859-5, windows-1251 (Bulgarian) * windows-1252 (English) * ISO-8859-7, windows-1253 (Greek) * ISO-8859-8, windows-1255 (Visual and Logical Hebrew) * TIS-620 (Thai) . This library is a port of the auto-detection code in Mozilla. Package: python-click Version: 6.6-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-colorama Homepage: https://github.com/mitsuhiko/click Priority: optional Section: python Filename: pool/main/p/python-click/python-click_6.6-1~nd16.04+1_all.deb Size: 56088 SHA256: 8dbc2f7d83fba1a437e4994369a3cdec2731e30b4de83b946abb57a5919aa8fe SHA1: f57be90c0bd4e0725b96ad25cb2c86e437b2b156 MD5sum: 9d9ea017b2cf4674ee2df5dfe4617743 Description: Simple wrapper around optparse for powerful command line utilities - Python 2.7 Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It's the "Command Line Interface Creation Kit". It's highly configurable but comes with sensible defaults out of the box. . It aims to make the process of writing command line tools quick and fun while also preventing any frustration caused by the inability to implement an intended CLI API. . This is the Python 2 compatible package. Package: python-datalad Source: datalad Version: 0.10.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4167 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_0.10.1-1~nd16.04+1_all.deb Size: 866426 SHA256: 34ac931732456cedfa90d56bc22636419b24188732638c3418e072f2ce6bfec2 SHA1: a8894d5aa1f987c33de197de85ebd9c92e1c3d4a MD5sum: e38277894afcc8773af14788709632c6 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: 0.6.2+git36-gc12d27d-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 506 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: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git36-gc12d27d-1~nd16.04+1_all.deb Size: 77856 SHA256: 07a61ada854ad5ef078507495b40bcf1ae6cd0b4eec6c54847865b8554f70453 SHA1: 8f37174739a525bdf76e0cafd2495a192c4e0b22 MD5sum: ab1d692626dddc8aa59cffb17dfcfc47 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-deprecation Version: 1.0.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 34 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/briancurtin/deprecation Priority: optional Section: python Filename: pool/main/p/python-deprecation/python-deprecation_1.0.1-1~nd16.04+1_all.deb Size: 8514 SHA256: 533809c12c01b5986512d84309b9dcfeec32aab1050c6881b7d1ee5c7c42b390 SHA1: eb558ba35152aae8a02d39eab361a38921fa1bf4 MD5sum: 9f0a1abc412cc817bfc33cfabf8b644b Description: Library to handle automated deprecations - Python 2.x Deprecation is a library that enables automated deprecations. . It offers the deprecated() decorator to wrap functions, providing proper warnings both in documentation and via Python’s warnings system, as well as the deprecation.fail_if_not_removed() decorator for test methods to ensure that deprecated code is eventually removed. . This package contains the Python 2.x module. Package: python-dipy Source: dipy Version: 0.14.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8631 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy (>= 1:1.7.1~), python-scipy, python-h5py, python-dipy-lib (>= 0.14.0-1~nd16.04+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~nd16.04+1_all.deb Size: 3055250 SHA256: a3a6323aabdf760cecb5f8f7e707bde720ea05659d0a414098b83c3ac7f5f8e1 SHA1: 37dd9dc0f6d72df09d4d083447c9077e5226feee MD5sum: 9c0719dcf13db9c523def3b071a79c4b 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~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16437 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~nd16.04+1_all.deb Size: 12497866 SHA256: 8973dc2bce0f0439699f5ba84f1ca15e6e4b996b60b2bf9eca592c14e7249a36 SHA1: dee7054c722af142e512042c49dcd84db9e915d9 MD5sum: eed63720fcdf573252531308882b2eb7 Description: Python library for the analysis of diffusion MRI datasets -- documentation DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.14.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11329 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.14.0-1~nd16.04+1_amd64.deb Size: 2167742 SHA256: 4d7ec433f5ca5e9dd03526b3aa7c93409aa203d46ca173a2a7d6a4cf9b0065f4 SHA1: 0e01ac39109334644afc40ca5edf2682208c9cec MD5sum: fafd3bfcbe6f48b977317edd86052c47 Description: Python library for the analysis of diffusion MRI datasets -- extensions DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-docker Version: 1.7.2-1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python-requests, python-six (>= 1.4.0), python-websocket, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/dotcloud/docker-py/ Priority: optional Section: python Filename: pool/main/p/python-docker/python-docker_1.7.2-1~bpo8+1~nd16.04+1_all.deb Size: 27114 SHA256: cf672dc82599d06380f63ec2b29efa7c1439ed54bcebdf7f810eed51edd5f197 SHA1: 2e97a63835aeb38fae5504be8830b9618a62525d MD5sum: e615eb319e74907ebd074ad677599dbe Description: Python wrapper to access docker.io's control socket This package contains oodles of routines that aid in controling docker.io over it's socket control, the same way the docker.io client controls the daemon. . This package provides Python 2 module bindings only. Package: python-dockerpty Source: dockerpty Version: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python-dockerpty_0.4.1-1~nd16.04+1_all.deb Size: 10952 SHA256: 3cba67f7413ae8865a000aba13ac5515a9978f1775d39020dd68f13010549fbb SHA1: 9eac24e87250203de569c904eeec7b2ea1e659b6 MD5sum: 97d1d3d43c73659e98560e6612ea3d6d Description: Pseudo-tty handler for docker Python client (Python 2.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 2.x version of dockerpty. Package: python-duecredit Source: duecredit Version: 0.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 234 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_0.5.0-1~nd16.04+1_all.deb Size: 49836 SHA256: 8f6b727151ec14685e5ec685c741f6a80c6e392914e444d2c8c625be85b00468 SHA1: 7f3ad805ef2aa096fd0348549186326edd60215b MD5sum: af07180f2cd5a642d3a14d34cc7fc61f 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~nd16.04+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~nd16.04+1_all.deb Size: 27666 SHA256: ed6288e21cc8fb69de94b68213830bae7f4a24383439a3abd059e9a55aeebd27 SHA1: f828ca0187182ad4094f88baca111138dd76dc70 MD5sum: d43bbfb781f83470f8b9beabe3afadcc 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-fasteners Version: 0.12.0-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, python-monotonic, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/harlowja/fasteners Priority: optional Section: python Filename: pool/main/p/python-fasteners/python-fasteners_0.12.0-3~nd16.04+1_all.deb Size: 13584 SHA256: 3c442f400f65e3c3a4f72f2f74a64c00c133dfcaf1fbc00f5f6ad33f73ccc022 SHA1: 3fcc4f4b994134181edbe2c47efa68d560515b23 MD5sum: 192247c42d4a250f2b9a982ebb3456a1 Description: provides useful locks - Python 2.7 Fasteners is a Python package that provides useful locks. It includes locking decorator (that acquires instance objects lock(s), acquires on method entry and releases on method exit), reader-writer locks, inter-process locks and generic lock helpers. . This package contains the Python 2.7 module. Package: python-fsl Source: fslpy Version: 1.2.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, python-lxml, python-nibabel, python-six (>= 1.0~), 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~nd16.04+1_all.deb Size: 84186 SHA256: 497b5722b87c224226515bc1bc610b814bea316c6c23b0a368e47cacd214995b SHA1: 640400431b06914255c12755b58d06711c493634 MD5sum: fc40ce6fac6b5b623f14c73723881b5c 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~nd16.04+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~nd16.04+1_all.deb Size: 75646 SHA256: 96a0e59342383de0460800da1a7aaf09867aee9d20fa28ab81fa0f592b807a1e SHA1: dd4294e0fdec5ca857ee08db664cbf2c0fac7d68 MD5sum: f6c45b02a4c84bcf44513ca559f82778 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~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 374 Depends: neurodebian-popularity-contest, python-wxgtk3.0, python-six (>= 1.0~), 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~nd16.04+1_all.deb Size: 68944 SHA256: 445df268d295023a3407427edb00c2d9869f11076cf157407e2382bcc16fe9d1 SHA1: b1e5f6160562be24a59ac073919aee86f1504f2b MD5sum: ddd29c0367daccaf7f40d78609972b44 Description: Python descriptor framework A collection of GUI widgets and utilities, based on wxPython. . This package provides the Python 2 module. Package: python-funcsigs Version: 0.4-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python-funcsigs_0.4-2~nd16.04+1_all.deb Size: 12746 SHA256: aa1594275088c19766b1ff28be4990783ecc4aad4b170a9a15fdab129d82765e SHA1: 7e6d04894fa13b3be7c6498bcc832877611b799b MD5sum: 2c202fea13d1545151b20b6b94dbd917 Description: function signatures from PEP362 - Python 2.7 funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 2.7 module. Package: python-funcsigs-doc Source: python-funcsigs Version: 0.4-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 121 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://funcsigs.readthedocs.org Priority: optional Section: doc Filename: pool/main/p/python-funcsigs/python-funcsigs-doc_0.4-2~nd16.04+1_all.deb Size: 23504 SHA256: 0faa043d8d03c5cec5db82b53c9aa38070bf5468f05d153f2052a4a25698ca67 SHA1: 964ef9081f948d5efd2bffb9ad20f032b7ea69ba MD5sum: 49d0850dc20522e3d5f6fa56aa05c6ae Description: function signatures from PEP362 - doc funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the documentation. Package: python-git Version: 2.1.8-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1653 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 2), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.1.8-1~nd16.04+1_all.deb Size: 304806 SHA256: 49778dfea42a6f510079e15fecc46334b17cf8f9175f73ef74e16c2c470d8c59 SHA1: d4224f7cd68eb0464b9e2a091ea2232bfb411efc MD5sum: c1415028064d804681aed1b0e678e97b Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.1.8-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 982 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.1.8-1~nd16.04+1_all.deb Size: 126804 SHA256: 697224b99cdf54cce984a851fa5e220f035f34a550e7c38657268ca904f26cad SHA1: 96e36a453f9bfa9a7961ef84bf43ca9947da0bc1 MD5sum: d52272b4d41c815ec690b645205eec0e Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-gitdb Version: 2.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 215 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_2.0.0-1~nd16.04+1_amd64.deb Size: 46170 SHA256: a26f68c0bdbfd532a7c9f2032cfeb7d2a3a4cc8a712741cae8d39469dcbe4b0c SHA1: c1a67e953ec0e887e67e87bbfc53c21bf5700b65 MD5sum: a81cf4e5e71fb8cc98d37ed7be460b84 Description: pure-Python git object database (Python 2) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 2. Package: python-github Source: pygithub Version: 1.26.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 632 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Conflicts: python-pygithub Replaces: python-pygithub Provides: python-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python-github_1.26.0-1~nd16.04+1_all.deb Size: 44830 SHA256: 066f7113c45087342009432eda00640d0a7fe268e6ae8d8df31df62f44adc80f SHA1: f70b5c50fa136dd5e6513f3c37712b8c33aa70eb MD5sum: 1d9d0c0285b697913307a360b531db43 Description: Access to full Github API v3 from Python2 This is a Python2 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python-httpretty Version: 0.8.14-1~nd16.04+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~nd16.04+1_all.deb Size: 20942 SHA256: deb9a88fe292bc82537b87f5a3ddcd6d395ca16a893dea8a9f3a117a2942b088 SHA1: 19f728590f85d682e9a84715ffef3cd7d85f9c39 MD5sum: bc1ea0d72b0c1d24d1a9851b0031cec1 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: 3.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 386 Depends: neurodebian-popularity-contest, python-enum34, 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_3.6.0-1~nd16.04+1_all.deb Size: 69974 SHA256: 531b352f7c6a7f5a3ffb31fe21909e9ef7ba1cd6192882bcff852fc8b464fcd3 SHA1: 0b67184aefc58fb6675817dce569897b9d9c02a0 MD5sum: 90247384b9834c164567214150c30898 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: 3.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1115 Depends: neurodebian-popularity-contest Homepage: https://github.com/DRMacIver/hypothesis Priority: extra Section: doc Filename: pool/main/p/python-hypothesis/python-hypothesis-doc_3.6.0-1~nd16.04+1_all.deb Size: 137930 SHA256: 3a633af68ee56811cfe94370a3f17b492d450593d76af8ea56c571b10185349b SHA1: 4819283511ddcc4509d79a970d37202d027a103b MD5sum: 26ca85398902b3a7785166aaf5aeeef0 Description: advanced Quickcheck style testing library (documentation) Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the documentation for Hypothesis. Package: python-indexed-gzip Source: indexed-gzip Version: 0.6.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 734 Depends: neurodebian-popularity-contest, cython, python-numpy (>= 1:1.10.0~b1), libc6 (>= 2.14), zlib1g (>= 1:1.2.2.4), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~) Provides: python2.7-indexed-gzip Homepage: https://github.com/pauldmccarthy/indexed_gzip Priority: optional Section: python Filename: pool/main/i/indexed-gzip/python-indexed-gzip_0.6.1-1~nd16.04+1_amd64.deb Size: 217126 SHA256: 238d65c402b6d0a883425eb0ef3a977bd07b979e30ae84849a8922f54b1ffcba SHA1: be264eee8ecaa338b59f46c72cb2ef8d2865c4e0 MD5sum: 9478a1bf2cc38d458122264afc30172a Description: fast random access of gzip files in Python Drop-in replacement `IndexedGzipFile` for the built-in Python `gzip.GzipFile` class that does not need to start decompressing from the beginning of the file when for every `seek()`. It gets around this performance limitation by building an index, which contains *seek points*, mappings between corresponding locations in the compressed and uncompressed data streams. Each seek point is accompanied by a chunk (32KB) of uncompressed data which is used to initialise the decompression algorithm, allowing to start reading from any seek point. If the index is built with a seek point spacing of 1MB, only 512KB (on average) of data have to be decompressed to read from any location in the file. . This package provides the Python 2 module. Package: python-joblib Source: joblib Version: 0.11-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 505 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-pytest, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.11-1~nd16.04+1_all.deb Size: 120838 SHA256: 66601984ce39127a542baafecdaa1448914a7b1c680291ad8d4e6a98f89bb5b2 SHA1: a58abd1d74d664e7bfb83bed3e3cb55f126e51a1 MD5sum: b37dc275927ab25d22fbee938101dc1f 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-jsmin Version: 2.2.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python-jsmin_2.2.1-1~nd16.04+1_all.deb Size: 21544 SHA256: 0246adb0afaf4dbbe0ce01017668a5d702a13ffcd2b07f05cdfb3613ceef5fa2 SHA1: 9e01dde8a81ad77de521112cb737bc8962975904 MD5sum: a855dba74b7e95f5a8f60b6e1ebaf677 Description: JavaScript minifier written in Python - Python 2.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 2.x module. Package: python-json-tricks Source: json-tricks Version: 3.11.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/mverleg/pyjson_tricks Priority: optional Section: python Filename: pool/main/j/json-tricks/python-json-tricks_3.11.0-1~nd16.04+1_all.deb Size: 24468 SHA256: c61fb48ab0b7ad722259f51149e83ff9387595d4b3da68642506bc18b1b14ed4 SHA1: 2b6e79b1362c1de54538d2a10441b4bcbcd95ca8 MD5sum: bb229ca6633199613f3a7add8cf35bb5 Description: Python module with extra features for JSON files The json_tricks Python module provides extra features for handling JSON files from Python: - Store and load numpy arrays in human-readable format - Store and load class instances both generic and customized - Store and load date/times as a dictionary (including timezone) - Preserve map order OrderedDict - Allow for comments in json files by starting lines with # - Sets, complex numbers, Decimal, Fraction, enums, compression, duplicate keys, ... . This package provides Python2 module. Package: python-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237662 SHA256: f27225dae5ede49f6db3b33d738901167019d32da2e264225201a799191992be SHA1: a0e2612212fc60fe89fa6e89a18324cf58c5b322 MD5sum: 859d71b6198aaf4f79eb8efd737d75bf Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-libxmp Source: python-xmp-toolkit Version: 2.0.1+git20140309.5437b0a-4~nd16.04+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~nd16.04+1_all.deb Size: 23384 SHA256: a7763142f4f7cb9183c2407e0e79b91d54a0b3e2066ba35d86a5ed73f7de6f25 SHA1: 8515a270da390b9dd8d2368d4331dbdb22713f9e MD5sum: d70fdb4d1e23284f50de7858c5db9b8f 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~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 242 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~nd16.04+1_all.deb Size: 38754 SHA256: 3e61c0748d6b2922a8af1f4e7d835f41220e87ed0466095a219ee235b7777cd5 SHA1: 83b0a7b5026ab8bf0d7ccda75d32cb330c88dd07 MD5sum: 725e1ad0436d3d4a563c0555b51ea5ad 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-mne Version: 0.13.1+dfsg-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9796 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui Recommends: python-nose, mayavi2 Suggests: python-dap, python-pycuda, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.13.1+dfsg-1~nd16.04+1_all.deb Size: 4506736 SHA256: 6a4586ccfa9cc3da1b92d02d335216fce957d0143ac8e6a5562436e94d7d304b SHA1: dafcfca4ccf723f376190679e8eee382e191b180 MD5sum: 08e3076cbe4a05e0d993e144ecf5f2e5 Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-monotonic Version: 1.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/atdt/monotonic Priority: optional Section: python Filename: pool/main/p/python-monotonic/python-monotonic_1.1-2~nd16.04+1_all.deb Size: 5440 SHA256: b6908a8b415774995c5414f3b5d42894254e9bad81e04be3a9f818acc982b54e SHA1: 017126b515c181df12f569e9367ec97ec32cc8b4 MD5sum: 6b097378e1043c8c89cc064f3f37b9f2 Description: implementation of time.monotonic() - Python 2.x This module provides a monotonic() function which returns the value (in fractional seconds) of a clock which never goes backwards. On Python 3.3 or newer, monotonic will be an alias of time.monotonic from the standard library. On older versions, it will fall back to an equivalent implementation: GetTickCount64 on Windows, mach_absolute_time on OS X, and clock_gettime(3) on Linux/BSD. . If no suitable implementation exists for the current platform, attempting to import this module (or to import from it) will cause a RuntimeError exception to be raised. . This package contains the Python 2.x module. Package: python-mutagen Source: mutagen Version: 1.38-1+nd1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 673 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-mutagen-doc Homepage: https://github.com/quodlibet/mutagen Priority: optional Section: python Filename: pool/main/m/mutagen/python-mutagen_1.38-1+nd1~nd16.04+1_all.deb Size: 138450 SHA256: 1ef6bf2d5307a02b24410f8c35d279398574c2b60034d5f38a7d56ee6901e191 SHA1: 8dc8d4a9ddc269af01da69fbe27906be5e0ed692 MD5sum: 9785761ada5d1f5c32dbc39fb245aa51 Description: audio metadata editing library Mutagen is a Python module to handle audio metadata. It supports FLAC, M4A, MP3, Ogg FLAC, Ogg Speex, Ogg Theora, Ogg Vorbis, True Audio, and WavPack audio files. All versions of ID3v2 are supported, and all standard ID3v2.4 frames are parsed. It can read Xing headers to accurately calculate the bitrate and length of MP3s. ID3 and APEv2 tags can be edited regardless of audio format. It can also manipulate Ogg streams on an individual packet/page level. Package: python-mutagen-doc Source: mutagen Version: 1.38-1+nd1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 966 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Recommends: python-mutagen Homepage: https://github.com/quodlibet/mutagen Priority: optional Section: doc Filename: pool/main/m/mutagen/python-mutagen-doc_1.38-1+nd1~nd16.04+1_all.deb Size: 124430 SHA256: 0aeecb4ff35ede1d4b0fbbf418f5de61240171c577c2c47e2beeda19c5973241 SHA1: aa74553be5bf71a2a32290a60342513221876d0a MD5sum: d496229c869f94406b8d768b64a09ab1 Description: audio metadata editing library - documentation Mutagen is a Python module to handle audio metadata. It supports FLAC, M4A, MP3, Ogg FLAC, Ogg Speex, Ogg Theora, Ogg Vorbis, True Audio, and WavPack audio files. All versions of ID3v2 are supported, and all standard ID3v2.4 frames are parsed. It can read Xing headers to accurately calculate the bitrate and length of MP3s. ID3 and APEv2 tags can be edited regardless of audio format. It can also manipulate Ogg streams on an individual packet/page level. . This package provides documentation for the mutagen package. Package: python-mvpa2 Source: pymvpa2 Version: 2.6.4-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8573 Depends: neurodebian-popularity-contest, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-mvpa2-lib (>= 2.6.4-2~nd16.04+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_2.6.4-2~nd16.04+1_all.deb Size: 5104792 SHA256: 4875ef846688f552bc78b4b8dc186fe4dfedd7327dc3616cb9826ca2ffb01236 SHA1: bae92c61888572d405bd167ab89ca67b3169f8fb MD5sum: 4c6d468449395bb7ba486a5bd384f62b 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: 2.6.4-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36295 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_2.6.4-2~nd16.04+1_all.deb Size: 4650248 SHA256: 197b49a94cbf9f22c9bac627a57c57524d7ea6a0f863e98019aa6ce2a8332f54 SHA1: b6cdcfbaee21f26c9f73b762248fe85e31dcec6e MD5sum: 0a7cf47c00aec34ddc2e998ec9ceb7fb Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.6.4-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.6.4-2~nd16.04+1_amd64.deb Size: 52176 SHA256: 28977a7bc7ceb3562cb59617bdc468fe721d120b27ecade2892683e04b438bdb SHA1: 9f3ffe6e86e174c9dc4022c4f6b446aa67401c0b MD5sum: 7d6cf18e1f63f3e00e11b6cbafbd5070 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 115 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd+1+nd16.04+1_all.deb Size: 28850 SHA256: 35e58bca96796988f7c3097c71ba0e078b6063215ce782dfb2461f30da939f7a SHA1: 37df2d9b9330ef7948d4bb86173b30a9eccaa0ca MD5sum: 6fbc209e0a5e48cd60f07cdbfc7aba56 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 2.3.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65171 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-six Recommends: python-dicom, python-fuse, python-mock Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.3.0-1~nd16.04+1_all.deb Size: 2586208 SHA256: 6200d3c4457d02519a146fc2920f32622f7fdf2325c884f396267d4b20d6933d SHA1: 23e0f36ce19acc437d87397cb7f13eac471183bb MD5sum: fcc5bac35e0b7006d6494d3523f597fb 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: 2.3.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20802 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_2.3.0-1~nd16.04+1_all.deb Size: 3374632 SHA256: b60fd9c0c945e33b8fee8ffb8dc099c600a2d8d316bba3a7bb41c8a4d44d7e67 SHA1: a510ac50e6fadd862d76c57564fcf7e76de997a3 MD5sum: 45ca162bad17c01fe302076c358b1a93 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-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2422 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6), python-nibabel (>= 1.1.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-scipy (>= 0.9), python-sklearn (>= 0.12.1) Recommends: python-matplotlib Provides: python2.7-nilearn Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python-nilearn_0.2.5~dfsg.1-1~nd16.04+1_all.deb Size: 731264 SHA256: 556fa551b0a378975a60af21259067980996ec5baef83b02c1c10d8ad461f800 SHA1: e6db7f5f06afd7c6986c6b9d7756cfb63ac3fae0 MD5sum: 604a86c38f7b85a5c13f8f103b4a8d63 Description: fast and easy statistical learning on neuroimaging data (Python 2) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 2 version. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.4.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3547 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.2-1~nd16.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.2-1~nd16.04+1_all.deb Size: 784436 SHA256: feb0932bebea5829dd4cc178d4466a699374ace640c25cb4667527ac8ecf837a SHA1: c3ad7c1737b1c0ea8f1541d17786e6354b76d957 MD5sum: 895e98e796267a2a162692ab2d2cb074 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10300 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.2-1~nd16.04+1_all.deb Size: 2640054 SHA256: 79b7d3f53761df2ffbb732b3a36c8955d81f36f2658a29899d69e80a4aae32ae SHA1: 63e76940aa81c5588bcdf21bc81aea719c3582eb MD5sum: e9c15fec54b2e0c0accacaaa1a74a32d Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.4.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2581 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.4.2-1~nd16.04+1_amd64.deb Size: 616658 SHA256: 92bb8efac39fb3e8cf1ca70891cbe4c6e3af53acba187431fefd68cda24e9ac3 SHA1: fc3bd0eda25f8a16942b3f3b8e7fdcecf13b5bd0 MD5sum: 5cc70a9506630f7e59c535d5665d04c4 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.4.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2737 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.2-1~nd16.04+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.4.2-1~nd16.04+1_amd64.deb Size: 672764 SHA256: 3ff4d0525775dfb7ea4cf36f21e83cc2d4f004fae7572f7e98ae3375ee59db59 SHA1: 9874f4a7d9f1007eb18880852c943e751fa7ee2c MD5sum: 2ad6495f9cbba8380673ab00e148e476 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipype Source: nipype Version: 1.0.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11103 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-numpy, python-dateutil (>= 2.2), python-scipy, python-traits, python-future, python-simplejson, python-prov, python-click, python-funcsigs, python-pytest, python-mock, python-packaging, python-configparser, python-traits (>= 4.5.0) | python-traits4 (>= 4.5.0), python-psutil Recommends: ipython, graphviz, python-xvfbwrapper, mayavi2, python-pydotplus, python-cfflib Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants, python-pytest-xdist Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_1.0.3-1~nd16.04+1_all.deb Size: 1888804 SHA256: e7b1b93a9a50ed5b97b8a4a0d6941205beb82e11a491ff0fd0d0e4a13b52a8a6 SHA1: c3da23f80b723920c88e74e316f57d3439f4c1d8 MD5sum: df6360e24060e9407085afde4128b0bd 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: 1.0.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40158 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_1.0.3-1~nd16.04+1_all.deb Size: 19002528 SHA256: 9ad8b7a4a01a39234dabe2a67f5eaecaf6a320f049b5c78c67f440e07e72a2b8 SHA1: a055d6893ef08efd01a03274f5c82c32474d2ec9 MD5sum: 549121917e8d38a26fbd3e1e7e9135f0 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-nitime Source: nitime Version: 0.7-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9377 Depends: neurodebian-popularity-contest, python-matplotlib, python-numpy, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.7-1~nd16.04+1_all.deb Size: 2553146 SHA256: 54569482245e3bf5eae0a48f6b2d893b640f450693a70911a96a1aaf5a7811ee SHA1: b0ca6ab172e04d8206d9b3e5df35bf3b41cf7f21 MD5sum: 3892f505c6932c69b3de3e752f5cfa1e Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.7-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7826 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.7-1~nd16.04+1_all.deb Size: 5699092 SHA256: cbe0e629d8af9f87d1c565e4590c2a2b888e576a92b2999bc51cd9521f98e1a5 SHA1: 29be357c1931a18aee0abed914a6d0592432c9fd MD5sum: 347cf7b23ed7dea21929ac201045e264 Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-numexpr Source: numexpr Version: 2.6.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 425 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python:any (>= 2.7.5-5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.6.2-1~nd16.04+1_amd64.deb Size: 145174 SHA256: 59c2771c42db4bc76f791fdae5e01a5fbf83f0c814773d0817e4c563d5522563 SHA1: a8c2ec8b7f7763c548290a9d8947e05379553d54 MD5sum: c7ac9c6fc3e2a7914042035d2e7d66b2 Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 287 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-numexpr (= 2.6.1-2~nd16.04+1), python-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.6.1-2~nd16.04+1_amd64.deb Size: 111270 SHA256: 3feec45c05be47652576dfb3531e0d67c765ab9016f5bebbd1ad5edb6eeb9a9e SHA1: 10ddde40dadb0baaf98e561a4540468345ad6416 MD5sum: 15cbbce6d196b5963b69856d03ce9834 Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-opengl Source: pyopengl Version: 3.1.0+dfsg-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5289 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-ctypes, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, freeglut3 Suggests: python-tk, python-numpy, libgle3 Homepage: http://pyopengl.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pyopengl/python-opengl_3.1.0+dfsg-1~nd16.04+1_all.deb Size: 502206 SHA256: c6f1c589672c7853ad0315795a69f847ff136d7f62bf0d193fd5a15700fa613c SHA1: fdb313a3f7f8856deb626df2e2a8138a19616ca2 MD5sum: 6d3d2268519ba7f557ba1fa1584dd9a0 Description: Python bindings to OpenGL (Python 2) PyOpenGL is a cross-platform open source Python binding to the standard OpenGL API providing 2D and 3D graphic drawing. PyOpenGL supports the GL, GLU, GLE, and GLUT libraries. The library can be used with the Tkinter, wxPython, FxPy, and Win32GUI windowing libraries (or almost any Python windowing library which can provide an OpenGL context). . This is the Python 2 version of the package. Package: python-openpyxl Source: openpyxl Version: 2.3.0-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1325 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-jdcal, python-lxml (>= 3.3.4) | python-et-xmlfile Recommends: python-pytest, python-pil, python-imaging Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0-3~nd16.04+1_all.deb Size: 199536 SHA256: 11635479c85c62cfe1190e1672fd06e44a9ce11126b29058b70cbb577a318fda SHA1: 3fdf7da3c8cfed9c62a980a227d27f2420d6807e MD5sum: dd7806981040a7e113d034693acd997b Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25229 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.19.2-1~nd16.04+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: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.19.2-1~nd16.04+1_all.deb Size: 2601224 SHA256: 4978eb7a1162131513496cc527a75abccfaa6a78134cd36953851332d0f5d1d4 SHA1: 3dddfafe1a3ed0e51a58b99db89de40c947f1770 MD5sum: 1251275238a0c73645433537108e17e9 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: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58841 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.19.2-1~nd16.04+1_all.deb Size: 10193446 SHA256: 2e91ca3328337bba23af7932f10392add466bf3e8af30ce3caee88ce04f92531 SHA1: 2e966fb7962fc6a07395fd99b66df827a5af6fb7 MD5sum: 663270f93696187938afede7b3ce6294 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7608 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.19.2-1~nd16.04+1_amd64.deb Size: 1831276 SHA256: 941e71c9063c9fff8ff58bbd8d00fd25e742ce447ea68f3ea3c1553695eb5ae5 SHA1: b27e05cd45916c718e52001d8c5a02c251996535 MD5sum: 700a76df4bf1a0eb3a800313a5ce4fac Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 779 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-six, python-numpy 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~nd16.04+1_all.deb Size: 169084 SHA256: 67873a5e82cf0ed24e7af34d09203a7babb95f840b596f567764d80ceeee4566 SHA1: 97fde9a8651212cc78294fa626feec237a1b7bd0 MD5sum: d73aee7388dd52e26dfab42afe9643b2 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~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1408 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~nd16.04+1_all.deb Size: 362406 SHA256: b16c06da21efe26063c34e3f330be8b18cbe0bca209f57812cb44fad621ef785 SHA1: 6b4cdff1e078b2ea9be829c4d92ee1d48d88e3a6 MD5sum: 1c7ecc644ad0a486f3ba5add4590b825 Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 441 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python-pkg-resources_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 141288 SHA256: b037bfbbddbe376e51050e582f7c81917a5466891d6d3629c27fb1217741fed6 SHA1: 2d6583f201e404099c1126acbd8bf172fe84a8d6 MD5sum: 23873c2cfca07961c552409c3a596e31 Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python-pprocess Source: pprocess Version: 0.5-2~nd16.04+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~nd16.04+1_all.deb Size: 83788 SHA256: 259c9557b6779afe5e30bf55c78aec59c98f3ef76f69ddede48dc801ac23fb43 SHA1: 472a65ca2314d807efdb93a31efba53b32e1d01b MD5sum: 70a87e18f8de21a567685badd18d2b2d 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~nd16.04+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~nd16.04+1_all.deb Size: 117640 SHA256: cb58c06763b1e763bfbdd1b04229f28b1e95757eb762ba26fd58c5b32805592e SHA1: 635cd8386e5cc0ab283ae447bedfe816ee30e0ad MD5sum: 0496927a902b3f920142edcd38033201 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-prov Version: 1.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1235 Depends: neurodebian-popularity-contest, python-dateutil, python-lxml, python-networkx, python-six (>= 1.9.0), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-prov-doc, python-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python-prov_1.4.0-1~nd16.04+1_all.deb Size: 72412 SHA256: 3e144e0a0760856a48b24d284fd4d6108a499f63cd99d83bcc09ea17613c93d8 SHA1: 6340eb932f0fdfa50fabb48723db8f775d781cbf MD5sum: 8d6d9dfb535595c3d219c87e24bc4bd3 Description: W3C Provenance Data Model (Python 2) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 2. Package: python-prov-doc Source: python-prov Version: 1.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 816 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/trungdong/prov Priority: optional Section: doc Filename: pool/main/p/python-prov/python-prov-doc_1.4.0-1~nd16.04+1_all.deb Size: 69138 SHA256: 046640dd0ce708f60592fe7049baaac44b3f4e9a5de273733d29e6359cceccfb SHA1: 44692dd8ccb838fda977b247aeb22965be531459 MD5sum: 0b63a3dbece70949384995f2644cf462 Description: documentation for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the documentation for the prov library. Package: python-py Version: 1.4.31-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.31-2~nd16.04+1_all.deb Size: 82250 SHA256: dd06fc78eb9eb64409c7b6de85b869c609e88300b4cea3c263bea0f7d5653d27 SHA1: b885dde7ca83a94a38105e7deadb39b61d208aba MD5sum: 508eae290a26634907683e8e0f11750d Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pydot Source: pydot Version: 1.2.3-1.1~nd16.04+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~nd16.04+1_all.deb Size: 20410 SHA256: 63bd00cc9701b5da3a888ebd99c96bab95f62b557b256ceddb93f34fce6a8f59 SHA1: 83f97a58d8e73bc0df74b35b93df8d71f68ea313 MD5sum: 785c376c3684712903fd238ba6ec6ad8 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-pydotplus Version: 2.0.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python-pyparsing (>= 2.0.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python-pydotplus_2.0.2-2~nd16.04+1_all.deb Size: 20380 SHA256: 39b27d471418f9c81855a45f723d39844052c83c40a1ff1806f2f54989a74216 SHA1: 6067dfa2d60382ae0aeeb5f41423cef6de4b4e18 MD5sum: e1ff9119f7ae7fba92f3bea83f89dca1 Description: interface to Graphviz's Dot language - Python 2.7 PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 2.7 module. Package: python-pydotplus-doc Source: python-pydotplus Version: 2.0.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 525 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-2~nd16.04+1_all.deb Size: 46822 SHA256: 80ee04b3206e1e638271ad5b870381128b38b12aa995c7d9237e4b38f672877b SHA1: 1680d00bc567d8e115bb693994cbad1f516aa426 MD5sum: 31848087f24154136a4c430e3106e491 Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1460 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libode4, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 5.2) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_amd64.deb Size: 286430 SHA256: ff44ddb8f59b4fdd857e6eadaed6e9313e56685f2a71adc722094105ce169555 SHA1: 5e364e5bb62ff1ddafbbe127422709cf7302e5a5 MD5sum: 48837816129adc541de9665f48eb9d20 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 822 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_all.deb Size: 819350 SHA256: 2e955547503f670039815376e4ac8860679cb376009788bc07c133ad3cf0dc02 SHA1: 349b67ae265dd0cbb576d6f2cc991cb1b9582a46 MD5sum: d7b4b656eb6f9dacf1c258cfa9df35bb Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pyglet Source: pyglet Version: 1.3.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7027 Depends: neurodebian-popularity-contest, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa, libgtk2.0-0, python-ctypes | python (>= 2.5), python-future, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: libasound2 | libopenal1 Provides: python2.7-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.3.0-1~nd16.04+1_all.deb Size: 1427658 SHA256: 3b99545a42bd5348136d2df2625de91a91b9d18d0f0c5785bee50eea1441606a SHA1: aeb386b87a6729dac196db991beaf4c2a71718e6 MD5sum: f58639e8f18f7393a5d0701883d2811b Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd16.04+1_amd64.deb Size: 74330 SHA256: f23ccdb46ba3c5262bec3cfa83765867c4a1735f741dd82e7cfc8040ad0d3ae4 SHA1: 5be82c04a410f37c530c18365a3afdbbd8c2d800 MD5sum: e0de083f7878b9e23237b2bab8f40f75 Description: Python interface to the Graphviz graph layout and visualization package Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. Package: python-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 307 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd16.04+1), python-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd16.04+1_amd64.deb Size: 113194 SHA256: 050382703d332347dcb069f765ee3d6af1e3e1ad7b4c5c2d2e057286cd81712e SHA1: 80c0f2eaffd808da75b230d227a19709b328ce97 MD5sum: d80abb8bb5687aee7fc0b2f9ba725fe7 Description: Python interface to the Graphviz graph layout and visualization package (debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python-pygraphviz. Build-Ids: 4b0c48008805be4ca40026fea6b599aa2e737e75 Package: python-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 312 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pygraphviz.github.io/ Priority: optional Section: doc Filename: pool/main/p/python-pygraphviz/python-pygraphviz-doc_1.3.1-1~nd16.04+1_all.deb Size: 67408 SHA256: c1224a2179507867f56f20c63434a263faa02bc206dc14e3aed3e1f7acd7076e SHA1: 2d1f19d174498015d80ca43a7a1a2b805a6532e7 MD5sum: 44c786b37a5b2e55cd781dd78c953f93 Description: Python interface to the Graphviz graph layout and visualization package (doc) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains documentation for python-pygraphviz. Package: python-pyperclip Version: 1.6.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 42 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), 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~nd16.04+1_all.deb Size: 9412 SHA256: 26e35e19d35c368d9b60d8ed168f65614e6b6bbc62172d6d183dc5f54280fa1e SHA1: f391b5db303066dbad91bafcfdf4a89705de1ee2 MD5sum: f09cfac57ce7c80561cea151aac1d727 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-pytest Source: pytest Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 605 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-mock (>= 1.0.1) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python-pytest_3.0.4-1~nd16.04+1_all.deb Size: 136446 SHA256: 4eac544d5793e2f59c640678d7c65261955ced7802e86863cfbc4a3c106ad781 SHA1: b3805eb51656f116e39fd66752ec1f39b7e13e4d MD5sum: 29c2a057ae9e61da6a2f763e592ae548 Description: Simple, powerful testing in Python This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 2 modules and the py.test script. Package: python-pytest-doc Source: pytest Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3939 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-pytest | python3-pytest Homepage: http://pytest.org/ Priority: optional Section: doc Filename: pool/main/p/pytest/python-pytest-doc_3.0.4-1~nd16.04+1_all.deb Size: 620420 SHA256: 5203020975510c490a97695c394b3ab272331e6a93e780b9e3202fd52e666caa SHA1: f6ff3f77f5ea42a8644ee30fcf1a5138dafe496d MD5sum: 3b598d5ab9a0dd8716ca8a91c870dab3 Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-runner Source: pytest-runner Version: 2.7.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 31 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/pytest-dev/pytest-runner Priority: optional Section: python Filename: pool/main/p/pytest-runner/python-pytest-runner_2.7.1-1~nd16.04+1_all.deb Size: 6122 SHA256: e32cbbf3bfb304bbc9c6a901571198457ff968fe74650c9d97a25b9b969dc6a7 SHA1: 60c152dafcd3f7e359e2e038625702c9a6d370c4 MD5sum: 1e5ed45580cfbf12d31130fb71e84b67 Description: Invoke py.test as distutils command with dependency resolution Setup scripts can use pytest-runner to add setup.py test support for pytest runner. . This package contains the Python 2 module. Package: python-requests Source: requests Version: 2.8.1-1~bpo8+1~nd16.04+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~nd16.04+1_all.deb Size: 67986 SHA256: 306c896e980cfc8919b8c16b0405d9532318d831452b92c9836ed0251abb15ed SHA1: 2cd529883b66acdaebe41ca8c93a2542f695eaf8 MD5sum: e44028d143ddd17295f7789105974770 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~nd16.04+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~nd16.04+1_all.deb Size: 319056 SHA256: 7ea89f759a4f88b54031523c58c568fcd12e099fb8142b6cf131d4a355f7675b SHA1: 76999e7ed545950bd1fe8232547c9e0994d1c83f MD5sum: 4398bb2a447ca10983b49d0e5a077ec3 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-scikits-learn Source: scikit-learn Version: 0.19.1-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.19.1-3~nd16.04+1_all.deb Size: 85568 SHA256: dfd00141e1729ed61b72ddf9a040a9199eb58d88567f2396f8d3496f312d1d4f SHA1: 0a0d04f94580274c01fe651776484340ff40aa99 MD5sum: 74598c38433d4097d3c26d369176f1a4 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-seaborn Source: seaborn Version: 0.7.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 766 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-pandas, python-matplotlib Recommends: python-statsmodels, python-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python-seaborn_0.7.1-2~nd16.04+1_all.deb Size: 128300 SHA256: 86a2a9f8c05f612d9894e9eb0a762e46af1ff746b26c0d50e6a6bcad4c0ebce4 SHA1: c3fa00cdc23d36db72e059d45d99d4149f1b8313 MD5sum: af65ebef49f9b4c1aca6f40e72a3838f Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 2 version of the package. Package: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 520 Depends: neurodebian-popularity-contest, python-pkg-resources (= 20.10.1-1.1~bpo8+1~nd16.04+1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-setuptools-doc Provides: python-distribute Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python-setuptools_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 202950 SHA256: 9db9a54136a49d35839778199b490639438e43271c08ce0743fb0760dfaf7469 SHA1: 9e93db246bb5d01d7acf9290dd8e12346b59fdfc MD5sum: 1e7b9797bfce6b0083a6c2d1615c71bf Description: Python Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: python-setuptools-doc Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1129 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: doc Filename: pool/main/p/python-setuptools/python-setuptools-doc_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 199256 SHA256: 6ebf63ca9734f4049aa848f2794d7d27a20a5a2d82899a13497124cb8fede833 SHA1: fa350942229b8c6cee34ea9a4675a0776a9c3b4e MD5sum: c413017bb2dd35fde176e997d4343f33 Description: Python Distutils Enhancements (documentation) Extensions to the Python distutils for large or complex distributions. The package contains the documentation in html format. Package: python-six Source: six Version: 1.10.0-3~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: https://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.10.0-3~bpo8+1~nd16.04+1_all.deb Size: 11738 SHA256: a16ef0744fa9490e2476f1744dcf0cba5a143f14f68cb4cdb64e7749bb0bb2aa SHA1: bfe91fb94d1d1bf0e3375ec11613cac158c49b13 MD5sum: 468a2063df5cea55065b488ba520cbca Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six and pypy-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 13318 SHA256: c8c2f26a64c9b1993f231546b6d5d3f4d0f8a4e96f0653c53060c6dde6b36d59 SHA1: 3abcec44fa903592ff069a138e1f57a4ddc7a93a MD5sum: ce48e44e76d54ab53124a9eb02b58690 Description: Python 2 and 3 compatibility library (universal wheel) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six as a universal wheel. Package: python-sklearn Source: scikit-learn Version: 0.19.1-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7020 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.19.1-3~nd16.04+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_0.19.1-3~nd16.04+1_all.deb Size: 1456278 SHA256: 5c8be8533b8db5f8bc6fa9bb8071628b0b7e5b1499b067530b22cead30fb2d3f SHA1: 15d911a029ee397cda7254d3f90001b39f602256 MD5sum: a924bd057634d1ed80475ee37338c890 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: 0.19.1-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32914 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_0.19.1-3~nd16.04+1_all.deb Size: 5268728 SHA256: b29b010b2b0ef509d0d3fbfc413fbbf85cde634f1057530470a24541e59bf8a2 SHA1: 4854c34793635cbe9516de8ebaf3771e50f745cd MD5sum: 9348fe8b067c7bb1908386eb7361a700 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.19.1-3~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7058 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.19.1-3~nd16.04+1_amd64.deb Size: 1633522 SHA256: 5b6af8b8a12b5d3062e4789f2c0b419984390efae837a4fafd125479edb33e33 SHA1: 447267f45f81afb2e2ddeb992d0488b7498e65a5 MD5sum: ce97ed8a65efb22a7ca84e46d3084abb Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-smmap Version: 2.0.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_2.0.1-1~nd16.04+1_all.deb Size: 20090 SHA256: 699c22f53c18a5c057f8fc5a8a95b9b5f45377d61c0aafd9d7aa37e9f0144851 SHA1: 42f1ffcb2dea935c2a89c044c1eee529ec64ff09 MD5sum: 7431762d66785a834a247a47df04e086 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 2. Package: python-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python-rdflib, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python-sparqlwrapper_1.7.6-3~nd16.04+1_all.deb Size: 22216 SHA256: ad338cb0ae4f323328124cc0ca75e8822622784570375fe07a2fa7686a26b2b6 SHA1: ca5fdf127bd16ad4a221f1e1bcdd9b772900d65b MD5sum: d074d7f980f64501cf433356823d0482 Description: SPARQL endpoint interface to Python This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 2 version of the package. Package: python-statsmodels Source: statsmodels Version: 0.8.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15922 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-statsmodels-lib (>= 0.8.0-1~nd16.04+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib, python-cvxopt Suggests: python-statsmodels-doc Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.8.0-1~nd16.04+1_all.deb Size: 3340100 SHA256: 133d42cbfbb1c1651f9b7913a39660a6c9cd0af10a18ab87c5398980e3d79174 SHA1: 3a7d1e327ff574cfd2906f74a18f82c24bf76b8f MD5sum: 8b330e6d8a3854e09fe5a61bed4f3a3a Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.8.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55368 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: libjs-mathjax Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.8.0-1~nd16.04+1_all.deb Size: 9810956 SHA256: 7663604107ba5269e57dc3c40759d0587466e771c27f977d463edee8261de208 SHA1: ce0165cf5425d34d981e95497725bca17a4c9a01 MD5sum: 9edbe8604cf20441a8907018b2dd535e Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-statsmodels-lib Source: statsmodels Version: 0.8.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1818 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.8.0-1~nd16.04+1_amd64.deb Size: 250232 SHA256: 0a828c62cbf83105da8d6e1e73d16eb6a441697f456d91900a7e4891558d71cd SHA1: e7dbe9d59f79504fcf8c9b1936ddb7427d3ee180 MD5sum: 4a3c23df50dfdd16e4ff81519ccae0af Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.15.6-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1493 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python2.7, python:any (>= 2.7.5-5~), libblas3 | libblas.so.3, libc6 (>= 2.14), libfftw3-double3, libgcc1 (>= 1:3.0), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libsuitesparse-dev, zlib1g-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.15.6-1~nd16.04+1_amd64.deb Size: 510402 SHA256: 6147ac371b95f1f1f0aee66486ba77734c239b62c473b4e082d3f87210cab2b9 SHA1: b8a2484c2fcf51b130bb9691ee284c12b0d0891e MD5sum: 6b9e7a376babbea2f6a72921dbfaa559 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.7-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 197 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nibabel, python-numpy, python-scipy, python-pil | python-imaging, mayavi2, python-argparse Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.7-1~nd16.04+1_all.deb Size: 42524 SHA256: 167ae695f1ade8edcad4c6bc0056578813ffa33199fa3b6264f03db670b9b7ee SHA1: ae13b9b963c87bf893e68854855cdfc42fe958a5 MD5sum: ccfb36d4a0a69845263bf2dfc3565700 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-tqdm Source: tqdm Version: 4.11.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 179 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.11.2-1~nd16.04+1_all.deb Size: 49804 SHA256: ab5898263779a7cccbfa96e88d16e55225e7dc003c7b9f3f8b71709b00d371ff SHA1: 82cee46a654514928793380200cd0a810d72ae11 MD5sum: d46b0fb89d9409486b5b0c0772fbd164 Description: fast, extensible progress bar for Python 2 tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 2 version of tqdm . Package: python-urllib3 Version: 1.12-1~bpo8+1~nd16.04+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~nd16.04+1_all.deb Size: 65338 SHA256: d15178f468f84a7b89caaf81b71c96897d5ae8242e664001531739624267e905 SHA1: 5d061603c38174218587941f515e58bd0bf49425 MD5sum: 5fb1f4092ef4fb6654af2107cd9b7db1 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~nd16.04+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~nd16.04+1_all.deb Size: 92846 SHA256: 9719b066fa4881282495c799c2b8471ea1353e3c75437987272164e2b133d64a SHA1: 0caa3703bdc22530c3cb78bf74dc532f30e9cb7f MD5sum: fdcf56c01fcf742292840cc0c544b432 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-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six (>= 1.5), python-wrapt, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43580 SHA256: d13dfc1adc96024f35330d4c72825e3f09b9767177330c804cc3575079e11498 SHA1: 38af2662eef11399c694c53bdca1e4159e830bc8 MD5sum: 212bc7388c199867c3f9d80be6d829c2 Description: record and replay HTML interactions (Python library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 2. Package: python-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 494 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 90490 SHA256: 72d4bc52366ba201df84aac1235c23b8b381f81113d7b854d673b15f17923672 SHA1: 87f9509347df7df8a1d83a6d18c1fb605416e4d2 MD5sum: 913cdb7893a354206416631b4a424e89 Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python-whoosh_2.7.4+git6-g9134ad92-1~nd16.04+1_all.deb Size: 290732 SHA256: 92a0eff9fdbfe4291844dee3e6df991f8cadf8d7f68390e6a786313f5a3c8989 SHA1: 88ad692740ab3d4e9b9aad304fb0cd2f88e11535 MD5sum: 170a5563e901639348a65d7259b85b66 Description: pure-Python full-text indexing, search, and spell checking library (Python 2) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python2 library Package: python-whoosh-doc Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2191 Pre-Depends: dpkg (>= 1.17.14) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Replaces: python-whoosh (<< 2.1.0) Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: extra Section: doc Filename: pool/main/p/python-whoosh/python-whoosh-doc_2.7.4+git6-g9134ad92-1~nd16.04+1_all.deb Size: 241712 SHA256: 12cb58145bf1ba52365ea308a7b0bb46a8af3daec44854cd63d9b711a33fbe7b SHA1: 59ddf9d1da701463188f7758ae1fd38ffcad4181 MD5sum: 885d8520f29c0118144c74e090dfd792 Description: full-text indexing, search, and spell checking library (doc) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the library documentation for python-whoosh. Package: python-wrapt Version: 1.9.0-4~nd0~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 121 Depends: neurodebian-popularity-contest, python-six, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4) Homepage: https://github.com/GrahamDumpleton/wrapt Priority: optional Section: python Filename: pool/main/p/python-wrapt/python-wrapt_1.9.0-4~nd0~nd16.04+1_amd64.deb Size: 27562 SHA256: d95f95f803f364db03edd98fe9de1aaceb2a135a4fb814f73d7e17524fd8c51a SHA1: f92755c149f8f1311a367751b13cf7e5c89c307c MD5sum: 74a14bea0e5028131c9ab049e787ed4b Description: decorators, wrappers and monkey patching. - Python 2.x The aim of the wrapt module is to provide a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions. . The wrapt module focuses very much on correctness. It therefore goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour. . To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled. . This package contains the Python 2.x module. Package: python-wrapt-doc Source: python-wrapt Version: 1.9.0-4~nd0~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 439 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~nd16.04+1_all.deb Size: 51402 SHA256: e707a7be420ef988e9faecf26c18534cf3d9e7a38ac0aea5a4553e47868045aa SHA1: ff328304d41bd1a2e74ca45a5ff9ff8c0f5a3d20 MD5sum: 6db6b288710374dc0d4ed655d4d3ff11 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: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 21058 SHA256: c93bdaf1b23b65d220a8c08b7043df874b281287d7145de0427dd1c2234f151d SHA1: 16ffed2622ee3e42555797e3f02591e8097e9419 MD5sum: 9fb059ae75b85aec11d96ed5c6c686ed Description: bash tab completion for argparse (for Python 3) Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 3.x. Package: python3-boto Source: python-boto Version: 2.44.0-1~nd16.04+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~nd16.04+1_all.deb Size: 741912 SHA256: 0171ac93c69bb4cd9bfeb65ba77dceb8eb52b6bf6a8da6049e26e8af0f3e78bd SHA1: 7ecdd63cf5a5e46600bd7dda14d1198b6db0856e MD5sum: e846f612f70e62f6ffa0367c2b73a12b 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-boto3 Source: python-boto3 Version: 1.2.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python3-botocore, python3-jmespath, python3:any (>= 3.3.2-2~), python3-requests, python3-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python3-boto3_1.2.2-2~nd16.04+1_all.deb Size: 58080 SHA256: 413d967eb1e92a29223c47517db82b3c216e2ccee47c0df766800113ea6bb482 SHA1: d1c429e14196e1d8fdac8a053e714cd6431a8cd3 MD5sum: 8fc1b3425641b60db58bf864bea336c9 Description: Python interface to Amazon's Web Services - Python 3.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python3-chardet Source: chardet Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 411 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Homepage: https://github.com/chardet/chardet Priority: optional Section: python Filename: pool/main/c/chardet/python3-chardet_3.0.4-1~nd16.04+1_all.deb Size: 80928 SHA256: ce06b0fb039b2c9b8e054ea352ea4f8f81d62692a4ca8c642f8904606f455997 SHA1: efb77eeccf18cee355a9471541460ba3551ce2c7 MD5sum: 7d125fcebd23f2fbe5e47e0f000fe77b Description: universal character encoding detector for Python3 Chardet takes a sequence of bytes in an unknown character encoding, and attempts to determine the encoding. . Supported encodings: * ASCII, UTF-8, UTF-16 (2 variants), UTF-32 (4 variants) * Big5, GB2312, EUC-TW, HZ-GB-2312, ISO-2022-CN (Traditional and Simplified Chinese) * EUC-JP, SHIFT_JIS, ISO-2022-JP (Japanese) * EUC-KR, ISO-2022-KR (Korean) * KOI8-R, MacCyrillic, IBM855, IBM866, ISO-8859-5, windows-1251 (Cyrillic) * ISO-8859-2, windows-1250 (Hungarian) * ISO-8859-5, windows-1251 (Bulgarian) * windows-1252 (English) * ISO-8859-7, windows-1253 (Greek) * ISO-8859-8, windows-1255 (Visual and Logical Hebrew) * TIS-620 (Thai) . This library is a port of the auto-detection code in Mozilla. . This package contains the Python 3 version of the library. Package: python3-click Source: python-click Version: 6.6-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-colorama Homepage: https://github.com/mitsuhiko/click Priority: optional Section: python Filename: pool/main/p/python-click/python3-click_6.6-1~nd16.04+1_all.deb Size: 56188 SHA256: cab0774b5e1413895b98a43ddb9aae5501b7d16cdbd4920e32364e920e6ce317 SHA1: 6ce3f2b88b4cdaeb7215da4bc6bdf6a6c44310c4 MD5sum: b10ccf20cad45fd576a95f98d438079f Description: Simple wrapper around optparse for powerful command line utilities - Python 3.x Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It's the "Command Line Interface Creation Kit". It's highly configurable but comes with sensible defaults out of the box. . It aims to make the process of writing command line tools quick and fun while also preventing any frustration caused by the inability to implement an intended CLI API. . This is the Python 3 compatible package. Package: python3-datalad Source: datalad Version: 0.10.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4167 Depends: neurodebian-popularity-contest, git-annex (>= 6.20180509~) | git-annex-standalone (>= 6.20180509~), patool, python3-appdirs, 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_0.10.1-1~nd16.04+1_all.deb Size: 866430 SHA256: 78ff6c6c7bfa74166c785656e301ab5633526fed60e265876d71daad599e24c8 SHA1: 5d315a74d01b825eadc8748273c15be234d996b7 MD5sum: 47e4ad8e32d870c54c4ba83e836f8b3c 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-deprecation Source: python-deprecation Version: 1.0.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 34 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Homepage: https://github.com/briancurtin/deprecation Priority: optional Section: python Filename: pool/main/p/python-deprecation/python3-deprecation_1.0.1-1~nd16.04+1_all.deb Size: 8596 SHA256: 7c4ce0e2a898f02430b72da190b1a1f2e974ee85d02e47e0d623dffb2c4a957e SHA1: aac1d0abc0b0d6efec934783cf40a591ab5a3678 MD5sum: 9ce1d906c604b7f6969d2faa5f47f07e Description: Library to handle automated deprecations - Python 3.x Deprecation is a library that enables automated deprecations. . It offers the deprecated() decorator to wrap functions, providing proper warnings both in documentation and via Python’s warnings system, as well as the deprecation.fail_if_not_removed() decorator for test methods to ensure that deprecated code is eventually removed. . This package contains the Python 3.x module. Package: python3-docker Source: python-docker Version: 1.7.2-1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python3-requests, python3-six (>= 1.4.0), python3-websocket, python3:any (>= 3.3.2-2~) Homepage: https://github.com/dotcloud/docker-py/ Priority: optional Section: python Filename: pool/main/p/python-docker/python3-docker_1.7.2-1~bpo8+1~nd16.04+1_all.deb Size: 27204 SHA256: 60788007aa403bdae6fb6b392cb8d61f891d4c1a7681fbb961b95bc4eb0e7845 SHA1: 9f340bb539e19d740fa08ddfdd0946cf4359552f MD5sum: b4bf94c8feaffb305d6c34999f113c27 Description: Python 3 wrapper to access docker.io's control socket This package contains oodles of routines that aid in controling docker.io over it's socket control, the same way the docker.io client controls the daemon. . This package provides Python 3 module bindings only. Package: python3-dockerpty Source: dockerpty Version: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python3-dockerpty_0.4.1-1~nd16.04+1_all.deb Size: 11020 SHA256: 573d709625a95da1a1e3574ea8da9da25fb0bb10fbf06253e29e48d1e7cb066e SHA1: cba110c5fa5c368521fd06764d24cf7383f2eb51 MD5sum: d6d8248ba19824c5e4ebaf1385e61ae1 Description: Pseudo-tty handler for docker Python client (Python 3.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 3.x version of dockerpty. Package: python3-duecredit Source: duecredit Version: 0.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 236 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_0.5.0-1~nd16.04+1_all.deb Size: 50062 SHA256: 234ba4405e3239bd4e409a9a04f55bdd571e7eebad9e5961f87c86795b09aa71 SHA1: f040a55ba952a28624501c3a51e4c2d57dd88832 MD5sum: abaa1e044235cb9607cd608816e8e41c 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~nd16.04+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~nd16.04+1_all.deb Size: 27746 SHA256: 8c50697d054f1b72a54acad605bde4404da7a554fcbe0fa8b3d0fad85ef1326d SHA1: cbe8d619d92b99d2b97fb8c4880d884ab6f2461e MD5sum: 2f26a7307dc23c5078e0050e603d7071 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-fasteners Source: python-fasteners Version: 0.12.0-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, python3-monotonic, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://github.com/harlowja/fasteners Priority: optional Section: python Filename: pool/main/p/python-fasteners/python3-fasteners_0.12.0-3~nd16.04+1_all.deb Size: 13662 SHA256: 5a1d1aaeb5c0444a164986a3519d66deb69ce536d1a243abbb85ea107de625b0 SHA1: c177b81b7b1f9f8c114f96b10a57dc5d1dfa8adb MD5sum: 503cd3ec14f470d691426e09a0afdeb1 Description: provides useful locks - Python 3.x Fasteners is a Python package that provides useful locks. It includes locking decorator (that acquires instance objects lock(s), acquires on method entry and releases on method exit), reader-writer locks, inter-process locks and generic lock helpers. . This package contains the Python 3.x module. Package: python3-fsl Source: fslpy Version: 1.2.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, python3-lxml, python3-nibabel, python3-six (>= 1.0~), python3-indexed-gzip, python3-numpy, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/f/fslpy/python3-fsl_1.2.2-2~nd16.04+1_all.deb Size: 84168 SHA256: 6e0994c55d683957f1fcc9740dec8a2408b253bc1709877f1b2e0d12cb1e3d98 SHA1: 40ccdf3c71401626bb658c8e76f96c7bd1f087d7 MD5sum: d834ac43034a2cd9e09e3d2ebaea9020 Description: FSL Python library Support library for FSL. . This package provides the Python 3 module. Package: python3-funcsigs Source: python-funcsigs Version: 0.4-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python3-funcsigs_0.4-2~nd16.04+1_all.deb Size: 12840 SHA256: 30ac14fecd0e1891912e0b3e81201fc8ed42978cfe3262adc77afb8698bc1997 SHA1: c10eb7d912d55099dbfe4d9652a1d23faf3226b3 MD5sum: cbd2d39553eb4ca7a3b1295af66d310a Description: function signatures from PEP362 - Python 3.x funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 3.x module. Package: python3-git Source: python-git Version: 2.1.8-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1650 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 2), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.1.8-1~nd16.04+1_all.deb Size: 304560 SHA256: 1be914bffd2206f8b7b706f4715bf829320d4b0ab3713f03d6023c56f6585989 SHA1: b8a935248419cdb5a516e501f6bed2f7118cca94 MD5sum: 7dc1e690c9a83fc6e25cca98f49512ed Description: Python library to interact with Git repositories - Python 3.x python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 3.x module. Package: python3-git-annex-adapter Source: git-annex-adapter Version: 0.0.0~pre1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 33 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160726~) | git-annex-standalone (>= 6.20160726~), python3:any (>= 3.3.2-2~) Homepage: https://github.com/alpernebbi/git-annex-adapter Priority: optional Section: python Filename: pool/main/g/git-annex-adapter/python3-git-annex-adapter_0.0.0~pre1-1~nd16.04+1_all.deb Size: 6812 SHA256: 1e263dca528e4bc3acc21ff5dbc30e5a42e8dad2c24cd6367c6005a02ff2f51f SHA1: cdb7531fe99462f3ee622889e496f7ef3088f98f MD5sum: 00c952ca16a9f427762477c0fde1eab4 Description: call git-annex commands from within Python This is a minimalistic interface to git-annex. Commands are executed using subprocess and use their batch versions whenever possible. Package: python3-gitdb Source: python-gitdb Version: 2.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 214 Depends: neurodebian-popularity-contest, python-smmap, python3-smmap, python3:any (>= 3.3.2-2~) Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python3-gitdb_2.0.0-1~nd16.04+1_amd64.deb Size: 46230 SHA256: 63ef8dd35fd3a685aa82eea798addbce67bcb0e0a865d8d7247236c22714bd5d SHA1: fd5b1a2bd79d5e2a5f406ea6c828369504866220 MD5sum: 3725dfaaee27fd67c5fbf3199f24baf3 Description: pure-Python git object database (Python 3) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 3. Package: python3-github Source: pygithub Version: 1.26.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 629 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Conflicts: python3-pygithub Replaces: python3-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python3-github_1.26.0-1~nd16.04+1_all.deb Size: 44896 SHA256: 9b0cb31263e2e0a368feb76d999e38d3cd3c4d12ab130cba07fac8c0b1357c24 SHA1: fadd6f4a75021a1d05dd975b06694c04750a2350 MD5sum: 430f2aca1c40484a5d7b20b85aa09726 Description: Access the full Github API v3 from Python3 This is a Python3 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python3-httpretty Source: python-httpretty Version: 0.8.14-1~nd16.04+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~nd16.04+1_all.deb Size: 21026 SHA256: cc5851b611a1d2f4290752e89734e89fb65e4891b5f87725344097736f390992 SHA1: a574a579b13c9d164461c73a20cc33544b3425a4 MD5sum: d78bc9189ce0609037ff939a0bc2e53a 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: 3.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 386 Depends: neurodebian-popularity-contest Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python3-hypothesis_3.6.0-1~nd16.04+1_all.deb Size: 70076 SHA256: 90847bb415568c3fdc9393162a4f13f5024f9bc78ea38900c0a791071b6f5ea5 SHA1: d2b3be72d531d2ed33413b37af651b7595a02869 MD5sum: ce51599e1281a64d1a9a356a149e864a Description: advanced Quickcheck style testing library for Python 3 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 3 module. Package: python3-indexed-gzip Source: indexed-gzip Version: 0.6.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 722 Depends: neurodebian-popularity-contest, cython3, python3-numpy, libc6 (>= 2.14), zlib1g (>= 1:1.2.2.4), python3 (<< 3.6), python3 (>= 3.5~) Provides: python3.5-indexed-gzip Homepage: https://github.com/pauldmccarthy/indexed_gzip Priority: optional Section: python Filename: pool/main/i/indexed-gzip/python3-indexed-gzip_0.6.1-1~nd16.04+1_amd64.deb Size: 216702 SHA256: 72c54f19dceb181c06a16d9521f2225ffbacd6b2495495f431b96c1b007d32c0 SHA1: 7badf11251c70687b39769a6cc59a9e9669c9555 MD5sum: bcd95fa16ce39cb9c2160dd862f0e585 Description: fast random access of gzip files in Python Drop-in replacement `IndexedGzipFile` for the built-in Python `gzip.GzipFile` class that does not need to start decompressing from the beginning of the file when for every `seek()`. It gets around this performance limitation by building an index, which contains *seek points*, mappings between corresponding locations in the compressed and uncompressed data streams. Each seek point is accompanied by a chunk (32KB) of uncompressed data which is used to initialise the decompression algorithm, allowing to start reading from any seek point. If the index is built with a seek point spacing of 1MB, only 512KB (on average) of data have to be decompressed to read from any location in the file. . This package provides the Python 3 module. Package: python3-joblib Source: joblib Version: 0.11-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 500 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-pytest, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.11-1~nd16.04+1_all.deb Size: 118060 SHA256: 708bd9a67011bc7470067ad8bdfe542e461b0a46ddaaeb4f97a964639b30caa7 SHA1: 3cd91b8694c39edf2909400bc801d35a0fa4c146 MD5sum: fab71d0c35313fdb3d5743ba7c1782d2 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-jsmin Source: python-jsmin Version: 2.2.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python3-jsmin_2.2.1-1~nd16.04+1_all.deb Size: 21612 SHA256: 3344d1c8edcf36faf774fdeafdbb2669d3c6df114603d9352a397bf7ed2d160d SHA1: db767406e3300c3f557df9c3feb51516e06c482e MD5sum: 8afeb5e7e7b9db0b819a30de472482a6 Description: JavaScript minifier written in Python - Python 3.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 3.x module. Package: python3-json-tricks Source: json-tricks Version: 3.11.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/mverleg/pyjson_tricks Priority: optional Section: python Filename: pool/main/j/json-tricks/python3-json-tricks_3.11.0-1~nd16.04+1_all.deb Size: 18856 SHA256: 20c5d2533cdff65d1f1a8c2b008d2e8ae7adaeec013ee6cc3c61b857f2ea9a8b SHA1: f90f2bddde5e42fce69877343d45d074843b1747 MD5sum: 8e4221a8bcc4308d2e8e59865064741e Description: Python module with extra features for JSON files The json_tricks Python module provides extra features for handling JSON files from Python: - Store and load numpy arrays in human-readable format - Store and load class instances both generic and customized - Store and load date/times as a dictionary (including timezone) - Preserve map order OrderedDict - Allow for comments in json files by starting lines with # - Sets, complex numbers, Decimal, Fraction, enums, compression, duplicate keys, ... . This package provides Python3 module. Package: python3-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1315 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy, python3-pbr, libc6 (>= 2.14) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237590 SHA256: 3cbb50f7352930b20c44343c5db4893215525ba2e4369e11d24f526eb002d553 SHA1: 9de3bab95047a3e29eb367af3fbabff08a63e25d MD5sum: 0c9dbd6e2e513ff2b5045bc672c1783f Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-libxmp Source: python-xmp-toolkit Version: 2.0.1+git20140309.5437b0a-4~nd16.04+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~nd16.04+1_all.deb Size: 23472 SHA256: 0c31f01d1535d115c6c84b56e8376d67705105964ce1ac2be1f79836c73b6a10 SHA1: d915a49d351427a6895491901a0a17c220a0f285 MD5sum: dda43428ea3d0b2f694b994d377fb174 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-monotonic Source: python-monotonic Version: 1.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/atdt/monotonic Priority: optional Section: python Filename: pool/main/p/python-monotonic/python3-monotonic_1.1-2~nd16.04+1_all.deb Size: 5496 SHA256: 8d2907a26b95b897f08003a9266d049a0384c42f4db44dd96df14462b34a866e SHA1: 6f77ee14d3af665867f0fd7d32fcaf333ef6479d MD5sum: 11e8aa7ee18e386213b2e51a9e4ae494 Description: implementation of time.monotonic() - Python 3.x This module provides a monotonic() function which returns the value (in fractional seconds) of a clock which never goes backwards. On Python 3.3 or newer, monotonic will be an alias of time.monotonic from the standard library. On older versions, it will fall back to an equivalent implementation: GetTickCount64 on Windows, mach_absolute_time on OS X, and clock_gettime(3) on Linux/BSD. . If no suitable implementation exists for the current platform, attempting to import this module (or to import from it) will cause a RuntimeError exception to be raised. . This package contains the Python 3.x module. Package: python3-mutagen Source: mutagen Version: 1.38-1+nd1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 654 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-mutagen-doc Homepage: https://github.com/quodlibet/mutagen Priority: optional Section: python Filename: pool/main/m/mutagen/python3-mutagen_1.38-1+nd1~nd16.04+1_all.deb Size: 132318 SHA256: c298ce34020c4c2343d83dfce4ee787c5d23900539387a67d3dacf366a43ce76 SHA1: da183f7db41781e9130bb556f36198a8b3d2a2c6 MD5sum: 2127ba2e94205a7296d9d88a01f14ba9 Description: audio metadata editing library (Python 3) Mutagen is a Python module to handle audio metadata. It supports FLAC, M4A, MP3, Ogg FLAC, Ogg Speex, Ogg Theora, Ogg Vorbis, True Audio, and WavPack audio files. All versions of ID3v2 are supported, and all standard ID3v2.4 frames are parsed. It can read Xing headers to accurately calculate the bitrate and length of MP3s. ID3 and APEv2 tags can be edited regardless of audio format. It can also manipulate Ogg streams on an individual packet/page level. . This package is built for Python 3. Package: python3-nibabel Source: nibabel Version: 2.3.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65157 Depends: neurodebian-popularity-contest, python3-numpy, python3:any (>= 3.3.2-2~), python3-scipy, python3-six Suggests: python-nibabel-doc, python3-dicom, python3-fuse, python3-mock Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.3.0-1~nd16.04+1_all.deb Size: 2582766 SHA256: 884388483a467f52d2bb9275d022870ccf1adb66de22eff4c2ca0e1c28016624 SHA1: 6ccb4ed4d4fd720de0cf337a900632865b13d52a MD5sum: 9bca1d7d4a3b66299b31bf6332ff671b 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-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2158 Depends: neurodebian-popularity-contest, python3-nibabel (>= 1.1.0), python3:any (>= 3.3.2-2~), python3-numpy (>= 1:1.6), python3-scipy (>= 0.9), python3-sklearn (>= 0.12.1) Recommends: python-matplotlib Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python3-nilearn_0.2.5~dfsg.1-1~nd16.04+1_all.deb Size: 685224 SHA256: 50d5820df0e96c898a62291baf032c83862b57bdcd5b144618143bd9ef79a719 SHA1: 11e003ff9cbe8bab038c64bbb46277793027021d MD5sum: e477063ef5c537c9b2cf5e48ce3e8981 Description: fast and easy statistical learning on neuroimaging data (Python 3) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 3 version. Package: python3-numexpr Source: numexpr Version: 2.6.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.6.2-1~nd16.04+1_amd64.deb Size: 139196 SHA256: 5a22d353ce524b80eb091ab5d0603e18d1b3bb16a800b0428c3f8372cd796c77 SHA1: 6938109914346b4f32e993818d9e15e58de84294 MD5sum: 07641fdd5c1c519a50769df822cbc4bb Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 291 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.6.1-2~nd16.04+1), python3-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.6.1-2~nd16.04+1_amd64.deb Size: 111626 SHA256: 1c7f0e9b22190369bf65b3df0a0fdc3c7608bfd53d797e8bcd296df6f03cd7d5 SHA1: 8961c12f5920ae9199645ca2eba676fa33cd2bf2 MD5sum: 690245e84333a1a6e293061b45074f33 Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-opengl Source: pyopengl Version: 3.1.0+dfsg-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5289 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, freeglut3 Suggests: python3-tk, python3-numpy, libgle3 Homepage: http://pyopengl.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pyopengl/python3-opengl_3.1.0+dfsg-1~nd16.04+1_all.deb Size: 502442 SHA256: 70d36f1d4930e6b529dc5e338a93b80c397b5c2e18702b7aaeb652473865c9c3 SHA1: 04fcb1dfc2af7e36e299d3367512cea231f9ab32 MD5sum: 152c0535f97dee9f6fac13ab6ff1487d Description: Python bindings to OpenGL (Python 3) PyOpenGL is a cross-platform open source Python binding to the standard OpenGL API providing 2D and 3D graphic drawing. PyOpenGL supports the GL, GLU, GLE, and GLUT libraries. The library can be used with the Tkinter, wxPython, FxPy, and Win32GUI windowing libraries (or almost any Python windowing library which can provide an OpenGL context). . This is the Python 3 version of the package. Package: python3-openpyxl Source: openpyxl Version: 2.3.0-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1321 Depends: neurodebian-popularity-contest, python3-jdcal, python3:any (>= 3.3.2-2~), python3-lxml (>= 3.3.4) | python3-et-xmlfile Recommends: python3-pytest, python3-pil Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0-3~nd16.04+1_all.deb Size: 198654 SHA256: da4c1478271e65cf9a3d6a2f0db24751a0609c052ca2bf73f5315dd895a613ce SHA1: 1c9f69acbcd5b9eb1d3f68b4c0d92029359c05be MD5sum: 7bc7b08384af486e80c08f9b879c63f3 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25227 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.19.2-1~nd16.04+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: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.19.2-1~nd16.04+1_all.deb Size: 2601416 SHA256: c84fc9fef43a496a971e61bd46680659228d9e9fd4ee29bc617455a24a407160 SHA1: f3b03bfd5354423bd3fb5be38eb35eb2bf79beb8 MD5sum: b0ae30aef1d47b5d32f5502c8b1eda78 Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7377 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.19.2-1~nd16.04+1_amd64.deb Size: 1807152 SHA256: 1fe61075b32c980373b59d4431b5373cb9f9aa955132cbef8fc08e741d5ff290 SHA1: e2766d864e1ba03bc5beb3e7ad6f3a5e62f1bc2b MD5sum: 1ba6ec7991907b564de4956466236be6 Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd16.04+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~nd16.04+1_all.deb Size: 169194 SHA256: f1918e6deeb48daa4b33e7556fe6e78a2d6557e5a72bfd12d9e45bc30a43adc0 SHA1: 411f03d31699f24bc3c71ea7f775c489837352fe MD5sum: 0866f30d9d2d1d10fcbb82945158218e 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-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python3-pkg-resources_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 111924 SHA256: 37436362884361cbe450a55d71d3b5e0c137945715f545e7b7be7c9b84e64d51 SHA1: 3a081bf0d880a0241694983fee33109f2107d602 MD5sum: 8f25c359bdd869855af0c2693dfd8e1c Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python3-prov Source: python-prov Version: 1.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1235 Depends: neurodebian-popularity-contest, python3-dateutil, python3-lxml, python3-networkx, python3-six (>= 1.9.0), python3:any (>= 3.3.2-2~) Suggests: python-prov-doc, python3-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python3-prov_1.4.0-1~nd16.04+1_all.deb Size: 72570 SHA256: 6e2836dd7da34d0a68513ac450fb3cd6a13be3aa79e9f284b3ccd16596d97ed4 SHA1: 77cd01fd8a21b7f58be5e975f7f32f36742d4dd9 MD5sum: ca78f5a4c2b8d6093898c99c5a2e2043 Description: W3C Provenance Data Model (Python 3) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 3. Package: python3-py Source: python-py Version: 1.4.31-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.31-2~nd16.04+1_all.deb Size: 82310 SHA256: 744838b493212a784bb0d94d5dd5c54347475dd987b8d3f0d32f4c029881bf40 SHA1: bf95bda1b6fa38d0262fba6fab890efb332d22a0 MD5sum: 010f582c231efd751bfc1261da1aae6f Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pydot Source: pydot Version: 1.2.3-1.1~nd16.04+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~nd16.04+1_all.deb Size: 19824 SHA256: 829d4e5bf11173d39878c35698bcef6aa77f8164285a58720b606c147b194552 SHA1: fd63bda12d780d29ff2618957089c22f46dda800 MD5sum: 3fb90f2381d52beb708662da6c71195d 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-pydotplus Source: python-pydotplus Version: 2.0.2-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python3-pyparsing (>= 2.0.1), python3:any (>= 3.3.2-2~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python3-pydotplus_2.0.2-2~nd16.04+1_all.deb Size: 20456 SHA256: 42d5c7c970226e81b0f17ae4652ff648d7383cf9e8808de91edf38e7cf2757fb SHA1: ab2277f582dc53d8671d48f1a223e9c5b5e58912 MD5sum: 641530aaadacf9937216ef63e4f45625 Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-pygraphviz Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd16.04+1_amd64.deb Size: 74230 SHA256: 7b9d089e59246402abb2ea7d3f53d3980c5690c5e62bf36bbca368b70adeedc5 SHA1: bac254b4ed0d37a7522262db2e705e03d1b6683c MD5sum: d1dec895c46a6dadad3ef072ea0a2447 Description: Python interface to the Graphviz graph layout and visualization package (Python 3) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the Python 3 version of python-pygraphviz. Package: python3-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 309 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd16.04+1), python3-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd16.04+1_amd64.deb Size: 112902 SHA256: 3f39d007137d726cea8160deb887a136fafbf8a6bd93f3cc4eccbea69d10fe57 SHA1: e352618f5109a2cba7ac1360b5bce48744ee66b1 MD5sum: 3f8f68ff662419ea83d1b913b44b2c5b Description: Python interface to the Graphviz graph layout and visualization package (py3k debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python3-pygraphviz. Build-Ids: ce5403c869e1f24666b0cfa342ad462fcbc0bdcc Package: python3-pyperclip Source: python-pyperclip Version: 1.6.0-2~nd16.04+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~nd16.04+1_all.deb Size: 9522 SHA256: 8dbaa68233c8c28cee899661c326dbe0e5ab902bac775fc0ca2122b03b3189ce SHA1: ff47289725f0bb6a2f96e43f71c76416600574ad MD5sum: e28924537b16308555d2062bf62c3626 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-pytest Source: pytest Version: 3.0.4-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 604 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3:any (>= 3.3.2-2~) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_3.0.4-1~nd16.04+1_all.deb Size: 136296 SHA256: 7351bf0f466638febe71c34923db203a23b2f20f7777ec28352378f8eb82f76e SHA1: 3c82f55dff3306fbdaec22eea08d2fa78c1b754b MD5sum: f05f902283edf2562c655a36187a643a Description: Simple, powerful testing in Python3 This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 3 module and the py.test-3 script. Package: python3-pytest-runner Source: pytest-runner Version: 2.7.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/pytest-dev/pytest-runner Priority: optional Section: python Filename: pool/main/p/pytest-runner/python3-pytest-runner_2.7.1-1~nd16.04+1_all.deb Size: 6138 SHA256: c0d765fdbc263503b35ddaf7b5542aa5d96478d9454452d5562da8153342fc98 SHA1: f336e89023459de8693b4a12cfb7203559adc7c0 MD5sum: 761f7237281476ff3a8c53174cec36dd Description: Invoke py.test as distutils command with dependency resolution Setup scripts can use pytest-runner to add setup.py test support for pytest runner. . This package contains the Python 3 module. Package: python3-requests Source: requests Version: 2.8.1-1~bpo8+1~nd16.04+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~nd16.04+1_all.deb Size: 67746 SHA256: ac6b753621a743a0bc80f56fcc7e031f1b9a981da60ee933cc5c249d68d88465 SHA1: 157fbd7d0c97a904fd4c4d7ad6acdc4dea9fc319 MD5sum: 4a17ba8733800086ea871f737b00566b 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-seaborn Source: seaborn Version: 0.7.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 766 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-pandas, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.7.1-2~nd16.04+1_all.deb Size: 128352 SHA256: 66bf9c26034f0925ba87e88ec57da2182501b5e6122faf5ffaf7f3dc37aed194 SHA1: f178a36166ba2524b7b5d4d373264263bf6a1d01 MD5sum: ea11b84936961fce0ee1045b416c1038 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 3 version of the package. Package: python3-setuptools Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 431 Depends: neurodebian-popularity-contest, python3-pkg-resources (= 20.10.1-1.1~bpo8+1~nd16.04+1), python3:any (>= 3.3.2-2~) Suggests: python-setuptools-doc Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python3-setuptools_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 121894 SHA256: 9c7fe7ae89e029a3c69597b27157f54739cfd6407f8b9e46396eb69e07c00943 SHA1: de63fb4b7eb655da6330a12b36514cc99301ef8f MD5sum: 58a2cbd8fd310c0a198285f421fe9a0e Description: Python3 Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: python3-six Source: six Version: 1.10.0-3~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: https://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.10.0-3~bpo8+1~nd16.04+1_all.deb Size: 11806 SHA256: da2c97c0ec6c668ab58dca583dc734673a2080d8ab71f6332b39bb4158ea31bd SHA1: e37946ce2c3203629370872514a485b92009df80 MD5sum: 1eecca62d1b45557f19e4e7ca8ceb295 Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six and pypy-six. Package: python3-sklearn Source: scikit-learn Version: 0.19.1-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7019 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.19.1-3~nd16.04+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_0.19.1-3~nd16.04+1_all.deb Size: 1455932 SHA256: 24712646da7d8560f4ca8bd3eaa2e5fbcd5f7234aee71acae56741471e11f398 SHA1: 53560a05791ff7b67c0ba21808c975e564a9ea13 MD5sum: a462a5a56b176fd7af2759fbeabe6ecf Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.19.1-3~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6175 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.19.1-3~nd16.04+1_amd64.deb Size: 1463606 SHA256: 0469c49c1769cc2f3de3b0636b674eb52616204a5f6b0805501b195aeecfc9da SHA1: cd537f131ec8df3ae78cb42bdcb364b77a721fb8 MD5sum: 45861e61d73c0de58fa35977cbe7201b Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-smmap Source: python-smmap Version: 2.0.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-nose Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python3-smmap_2.0.1-1~nd16.04+1_all.deb Size: 20176 SHA256: 1cb1b9b738cfb35ca19ff27fd377111c1eac7aa7e41303d477b7e16ce546875f SHA1: 353febe116a610d81ed286782fea5b7c930cef2e MD5sum: 7bd6b73d32e59b25816632eaab44ba76 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 3. Package: python3-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 86 Depends: neurodebian-popularity-contest, python3-rdflib, python3:any (>= 3.3.2-2~) Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python3-sparqlwrapper_1.7.6-3~nd16.04+1_all.deb Size: 20736 SHA256: 00f1f4dccddb10c7dc20864c2c1f3d1dd5d28e4f8a6688d64d0369c660546a81 SHA1: 7cee8efdc2c8913ab01e21b747340d64bc510998 MD5sum: 7fccb9cc5ce739fda709fe4a13a62dbb Description: SPARQL endpoint interface to Python3 This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 3 version of the package. Package: python3-tqdm Source: tqdm Version: 4.11.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 181 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.11.2-1~nd16.04+1_all.deb Size: 50092 SHA256: ef6ef312041d0af9d825d0c6e600ee946e19f1bbfd2ca633bd20c5165dea9ed3 SHA1: 7dcd58cbe44933ed9c3cac9ddbb07855739e661f MD5sum: 9c3ab503bab47c52297b45f2fe8803f6 Description: fast, extensible progress bar for Python 3 and CLI tool tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 3 version of tqdm and its command-line tool. Package: python3-urllib3 Source: python-urllib3 Version: 1.12-1~bpo8+1~nd16.04+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~nd16.04+1_all.deb Size: 65460 SHA256: f64733ffe86e9e4fbec330998afddd392db1a86b1c64059687b989d8f99af98f SHA1: a737acfc24ced71f1de94337feff3698b46593b7 MD5sum: 2120aceab8d183efda1e1033d8d10398 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-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python3-six (>= 1.5), python3-wrapt, python3-yaml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python3-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43654 SHA256: 18be5074cff6cd48dd691e1921cc15a96ad10de55944bad110958f0842ca8628 SHA1: 4de90dcf566f64fceaaa00a00af8fe588e105295 MD5sum: 4bb489a1b4d0759306109fcd31ec7e58 Description: record and replay HTML interactions (Python3 library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 3. Package: python3-whoosh Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python3-whoosh_2.7.4+git6-g9134ad92-1~nd16.04+1_all.deb Size: 290836 SHA256: cc05e669b1140db18ec728f1d3660733d90e5169fe036d0a383b7b2e9dfbb844 SHA1: 64faab26c358bac01ecf9851b4106ec0b8fbf220 MD5sum: 3656d0b3d443816dd647213af474dd04 Description: pure-Python full-text indexing, search, and spell checking library (Python 3) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python3 library Package: python3-wrapt Source: python-wrapt Version: 1.9.0-4~nd0~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 121 Depends: neurodebian-popularity-contest, python3-six, python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.4) Homepage: https://github.com/GrahamDumpleton/wrapt Priority: optional Section: python Filename: pool/main/p/python-wrapt/python3-wrapt_1.9.0-4~nd0~nd16.04+1_amd64.deb Size: 27556 SHA256: d45f2693b941f6ba7b5550f2d7076a9d9ceb3603a57d3cc0165f3664a5285cfb SHA1: f4366c716f0dc9d5f02b2ca94005ab30112e3cb2 MD5sum: c4aafd2ee8d9bcacca72077931df4136 Description: decorators, wrappers and monkey patching. - Python 3.x The aim of the wrapt module is to provide a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions. . The wrapt module focuses very much on correctness. It therefore goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour. . To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled. . This package contains the Python 3.x module. Package: rclone Version: 1.36-1~ndall0 Architecture: amd64 Maintainer: Debian Go Packaging Team Installed-Size: 11599 Depends: libc6 (>= 2.3.2) Built-Using: go-md2man (= 1.0.6+ds-1), golang-1.7 (= 1.7.4-2), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-blackfriday (= 1.4+git20161003.40.5f33e7b-1), golang-github-aws-aws-sdk-go (= 1.1.14+dfsg-2), golang-github-davecgh-go-spew (= 1.1.0-1), golang-github-go-ini-ini (= 1.8.6-2), golang-github-google-go-querystring (= 0.0~git20151028.0.2a60fc2-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-ncw-go-acd (= 0.0~git20161119.0.7954f1f-1), golang-github-ncw-swift (= 0.0~git20160617.0.b964f2c-2), golang-github-pkg-errors (= 0.8.0-1), golang-github-pkg-sftp (= 0.0~git20160930.0.4d0e916-1), golang-github-pmezard-go-difflib (= 1.0.0-1), golang-github-rfjakob-eme (= 1.0-2), golang-github-shurcool-sanitized-anchor-name (= 0.0~git20160918.0.1dba4b3-1), golang-github-skratchdot-open-golang (= 0.0~git20160302.0.75fb7ed-2), golang-github-spf13-cobra (= 0.0~git20161229.0.1dd5ff2-1), golang-github-spf13-pflag (= 0.0~git20161024.0.5ccb023-1), golang-github-stacktic-dropbox (= 0.0~git20160424.0.58f839b-2), golang-github-tsenart-tb (= 0.0~git20151208.0.19f4c3d-2), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-go.crypto (= 1:0.0~git20170407.0.55a552f+REALLY.0.0~git20161012.0.5f31782-1), golang-golang-x-net-dev (= 1:0.0+git20161013.8b4af36+dfsg-3), golang-golang-x-oauth2 (= 0.0~git20161103.0.36bc617-4), golang-golang-x-sys (= 0.0~git20161122.0.30237cf-1), golang-google-api (= 0.0~git20161128.3cc2e59-2), golang-google-cloud (= 0.5.0-2), golang-testify (= 1.1.4+ds-1), golang-x-text (= 0.0~git20161013.0.c745997-2) Homepage: https://github.com/ncw/rclone Priority: optional Section: net Filename: pool/main/r/rclone/rclone_1.36-1~ndall0_amd64.deb Size: 3007896 SHA256: 411f7f77ac00f6acb4d56085b8b7885c67dd40c559eec7ea5878124056caaf65 SHA1: 750dd2b0df62b311b2127a6360f29cc381cf514c MD5sum: a67712b0ea9da6855adea4cbd071999e Description: rsync for commercial cloud storage Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers: . - Google Drive - Amazon S3 - Openstack Swift / Rackspace cloud files / Memset Memstore - Dropbox - Google Cloud Storage - Amazon Drive - Microsoft One Drive - Hubic - Backblaze B2 - Yandex Disk Package: remake Version: 4.1+dbg1.3~dfsg.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 321 Depends: neurodebian-popularity-contest, guile-2.0-libs, libc6 (>= 2.17), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_4.1+dbg1.3~dfsg.1-1~nd16.04+1_amd64.deb Size: 152736 SHA256: 0f6476cd5126d25db64cc1cc490a0bc80cb9e5e8979f85888493664736975a71 SHA1: 197b06008f2856d6b088966e500ce1465176ba45 MD5sum: 50400217fc4281d26256dd7284eac38c Description: GNU make fork with improved error reporting and debugging Modernized version of GNU make utility that adds improved error reporting, the ability to trace execution in a comprehensible way, and a debugger. Some of the features of the debugger are: * see the target call stack * set breakpoints on targets * show and set variables * execute arbitrary "make" code * issue shell commands while stopped in the middle of execution * inspect target descriptions * write a file with the commands of the target expanded Package: singularity-container Version: 2.5.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2407 Depends: neurodebian-popularity-contest, python, squashfs-tools, libarchive13, libc6 (>= 2.14) Recommends: e2fsprogs Homepage: http://www.sylabs.io Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.5.1-1~nd16.04+1_amd64.deb Size: 338292 SHA256: 57f1c8de463fb8e6dd425f05ea74d96946df6280b86358c9831b466233184c6c SHA1: aa3e566c9fc1e3aca9de69ea4b5cc458e7d0c29f MD5sum: 989358b2fb976a0b17b5bd5395bc446a Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: solar-eclipse Version: 8.1.1+git0-g8f32b4b-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 13280 Depends: neurodebian-popularity-contest, libc6 (>= 2.23), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), libnifti2, libstdc++6 (>= 5.2), libtcl8.5 (>= 8.5.0), tcl8.5 Recommends: python Homepage: http://solar-eclipse-genetics.org/ Priority: optional Section: science Filename: pool/main/s/solar-eclipse/solar-eclipse_8.1.1+git0-g8f32b4b-1~nd16.04+1_amd64.deb Size: 1723816 SHA256: 9c7c4e2ced1b79824da0d873fe3f325331e59dcf700041354488e3e0570848e5 SHA1: bbd57715f0214ee32d0030f37e5f7ab58f05c9f9 MD5sum: 6aa156c8a83655a7e21f2347ab08599f Description: genetic variance components analysis software SOLAR-Eclipse is an extensive, flexible software package for genetic variance components analysis, including linkage analysis, quantitative genetic analysis, SNP association analysis (QTN and QTLD), and covariate screening. Operations are included for calculation of marker-specific or multipoint identity-by-descent (IBD) matrices in pedigrees of arbitrary size and complexity, and for linkage analysis of multiple quantitative traits and/or discrete traits which may involve multiple loci (oligogenic analysis), dominance effects, household effects, and interactions. Additional features include functionality for mega and meta-genetic analyses where data from diverse cohorts can be pooled to improve statistical significance. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19186 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 9781970 SHA256: 30cac74b9ad9db32f093eece5bae13d28ce4e1222878358f3afc6e6a67b55b67 SHA1: 4899f3ba6a1ff156b67ed1b324ae4a83ffbbab9e MD5sum: 093fd447d8b43ebafc21585625545b37 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73019 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 45497774 SHA256: bde3c93b9c1168ff6fa5b3269782006cf5613ba3f2b7b49abd5249d07600335b SHA1: af6dce85c4ee9079c720d544dfacfe2fc2cffa67 MD5sum: 494ca73671489f3feaf525e4295caff3 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9251 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 8934936 SHA256: 7f6f08608f31115b8e51d149f8560a2cfe399bd44562ff34bf2aeb24a9632bc9 SHA1: 31e802efc7a2237d47eb5a13d1d6f6a6f9ed7324 MD5sum: c96ec4b1e942cf1f8f8eb55b327d7c40 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: stimfit Version: 0.15.6-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3347 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.14), libfftw3-double3, libgcc1 (>= 1:3.0), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.2+dfsg), libwxgtk3.0-0v5 (>= 3.0.2+dfsg), python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python2.7, python:any (>= 2.7.5-5~), libsuitesparse-dev, zlib1g-dev, python-wxgtk3.0 | python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.15.6-1~nd16.04+1_amd64.deb Size: 948144 SHA256: 8509bed77d56c79ad5747a754d43f8c7e0ecd497e85b7c9840f1826adb5a80b0 SHA1: d76fcf51e5160c22749730662c30b7f0ae83f2d1 MD5sum: ef900dd00a6d65865e3a2bdf523f370d Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.15.6-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7736 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.15.6-1~nd16.04+1_amd64.deb Size: 7462238 SHA256: c3203ff0dfc2d2e1cadd8dd8fcac1166f5587cfd9d39f0fdd4d5fd89078ea9cf SHA1: b81603d42c686cef6acd692b6b5976f9807359e5 MD5sum: 2917d12990d1d75e4f4aa3ca4bf81318 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. This package contains the debug symbols for Stimfit. Build-Ids: 0bb2ecc80fc11e621692aa8f1c67130ff1b3e57b 24536c79134588657fd9a5ccbe7bc2af716a0afe 2a2620ad83b19fcdf156f2de781f5e1e4e438ab4 d16358afc0ededa96f3c5ad64e7eb21f0669f0d4 d81c24d5908825a9b958c915138e9ab31d239531 f1f103cea16b6517f112e2b0cfdeb97b358ee31c Package: ubuntu-keyring Version: 2010.+09.30~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd+1+nd16.04+1_all.deb Size: 11702 SHA256: e6052ad683b7b3eac5152f3790fcf69f3340f2526d81e9e394a6c4b11fbb26c0 SHA1: 288fe25a2be199481113954438cd17bc01060293 MD5sum: f432078db30b3298f5dbac78eaad7c06 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: uftp Version: 4.9.3-1+nd1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 526 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libssl1.0.0 (>= 1.0.1), debconf (>= 0.5) | debconf-2.0 Homepage: http://uftp-multicast.sourceforge.net/ Priority: optional Section: net Filename: pool/main/u/uftp/uftp_4.9.3-1+nd1~nd16.04+1_amd64.deb Size: 176048 SHA256: a81014b613a18fbff62b4a9c04f77783f5a2aeba0e2bf9b823b60d4d553a21e3 SHA1: 139c66e6d8a5f5bca48a96daf4cf25354cfd1bad MD5sum: 5bf855761448546f778263a372718eb8 Description: Encrypted multicast file transfer program Utility for secure, reliable, and efficient file transfer to multiple receivers simultaneously. This is useful for distributing large files to a large number of receivers, and is especially useful for data distribution over a satellite link where the inherent delay makes any TCP based communication highly inefficient. Package: utopia-documents Version: 3.0.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18099 Depends: neurodebian-popularity-contest, libboost-python1.58.0, libboost-system1.58.0, libboost-thread1.58.0, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libpcre3, libpcrecpp0v5 (>= 7.7), libpoppler58 (>= 0.41.0), libpython2.7 (>= 2.7), libqt5core5a (>= 5.5.0), libqt5gui5 (>= 5.0.2) | libqt5gui5-gles (>= 5.0.2), libqt5network5 (>= 5.4.0), libqt5opengl5 (>= 5.0.2) | libqt5opengl5-gles (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5script5 (>= 5.0.2), libqt5svg5 (>= 5.0.2), libqt5webkit5 (>= 5.2.0), libqt5widgets5 (>= 5.2.0), libqt5xml5 (>= 5.0.2), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), python (<< 2.8), python (>= 2.7~), python2.7, python:any (>= 2.7.5-5~), python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_3.0.2-1~nd16.04+1_amd64.deb Size: 5615146 SHA256: 82c6718afe7118cddcea304c1c60a67c5f170a33dc01c657f77c67d5c44fa5ef SHA1: f64821bb26232fe54738dde15f3e13c9ad1b44e1 MD5sum: 9cc6b49bff294d69bf8f81645d774006 Description: PDF reader that displays interactive annotations on scientific articles Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. It makes it easy to explore an article's content and claims, and investigate other recent articles that discuss the same or similar topics. . Get immediate access to an article's metadata and browse the relationship it has with the world at large. Generate a formatted citation for use in your own work, follow bibliographic links to cited articles, or get a document's related data at the click of a button. . Various extensions provide links to blogs, online data sources and to social media sites so you can see what other researchers have been saying about not only the article you're reading but its subject matter too. Package: utopia-documents-dbg Source: utopia-documents Version: 3.0.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48389 Depends: neurodebian-popularity-contest, utopia-documents (= 3.0.2-1~nd16.04+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_3.0.2-1~nd16.04+1_amd64.deb Size: 47312530 SHA256: 3b33dcadd81f8d271beaca7e9862cb38db6c5847ca1d46e039427958557274d3 SHA1: 1f6532ed783e47f9f2b46331763839dc7ffb5cf1 MD5sum: a701a22a8be2df86dd1885d32e377408 Description: debugging symbols for utopia-documents Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. . This package contains the debugging symbols for utopia-documents. Build-Ids: 0163d24bc3ebd1c3f0755606b8b5f2209987257a 083cb374028b27cf2f4ed680d16f996ab3cc333d 0a422b53248e356d05bb29492948363a72e1d1c9 35a0b34541a0e4526ba4fefd5401fb39b17a3840 382aa36614a30c8a412d35dada9f8844a7e0d3b4 39fe18ddaca8a22fc10e75b3706c243fd6a10e91 3b4207a4f13987151f56821ec1344feb82b1f7ae 3d399ff3e5fdfe6cf7e803791a9c4faa38f25d49 499db856096f6a937df0702f99dc2ef2b2717f70 4a42f546d31773a41598db11af943063a87d478a 4c1c602707fefc8ac79b5c461dd5dbc6337b7688 537e00a82c60c2e42001efdc9f669372168f2ce1 64c244300f8df1e16ca1d0343bc020ee98e71f59 73b26e79b5909db1ee873069834457cd88f06308 7c80429249b113bc922074ac676730f219922580 819f05d377d06ec3a4919cdf6387e0c7a1481d29 8ab81aca7da8dda8171b156d02b2717b3d680e81 981fb279a47e332f77fc99adfbb7cd5ad56bcb36 a00b4346815dbfe0d41955fa611706385b066994 a3aa77364f16885c73848e34f1f7308c1bcf9719 a428ad7d254b0954b51e3c9142920255e2642b2c a511517d38f9a26a23788b414ebde854aab9fe61 b7fae740892516ccc20c5ba07141bbe746dde1b2 c2c2d931797f15a0723e0d4aa5ebe7488030bd75 cb4aac6c8ad35fe673d18e146047def6ab414266 d1e2025203703c499784d7ea83266004a500d63c d75862ae0aa263b02e9e657c960663fe66622592 d80556429899b85eec50cc102ea2ece36cd284af da6101c3ba5088d76022613490ef82b8adc7132a dba392ff6e809c8d11eda0c6bd100a41330fd4df df1b9e879307018921ced7a90fcdfeb628f09cfd e2e8fe3fd8610f9ffcfcd7973d8621b728083768 e845b8a1c715a8a65746c9f0f74ccc933dbc0333 e9c436bb7848d72672558c2bf3b1f0dcf0e690ef ec2ddefb1bf5a692b17a946a1695d6048e69af45 f381ec7fa1993b60e66d1d50bdd2eb4d0e778709 f9563f932ea173c95e95b037fc7611c509489dc2 fb198eba6dad0d73117e6390dda8dd3ee0bee8bd fbbd56901c564dabfd6ad2079851afa55f7459fe Package: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 348 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.2.1), libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 47934 SHA256: e6f7ac1d6920c0f57691c048d994c9e901daf9c718e6d44c2ca599f7a1595cc5 SHA1: ac39f456fe7fdf65d170e3aa9817c67d4b0c64bf MD5sum: 01520507139dfcc92a73d7239e11df86 Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5172 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1), vrpn (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 1077458 SHA256: f556bb2601abba9acfa62fe935a6d0c259ba1efee3868b658ec5999a58e9223a SHA1: d60d891faa6da3842f7132b841c499c3a8b931e7 MD5sum: 7259b2bb3fb5c5ec3dcf19296bb5ecea Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 292 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libvtk-dicom0.5, libvtk5.10 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74420 SHA256: 92f477592c081c6845f6543d159cbf8bc61fe9a546f7f76368e98389b8c4ce47 SHA1: 654070e833e6bae0221c6cad237485d14ae991af MD5sum: 077421e9c48bf947c2eb4aacd390092a Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools