Package: aghermann Version: 1.1.1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1493 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), 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_i386.deb Size: 522984 SHA256: aafa593b279ab0456cc61c315e19ae70d5f63c69b227c58b729b50b1c20baa84 SHA1: f405f3b2b2afe18a2a5c8646c74687d6dc453c4f MD5sum: ff406c0bd8994f12eb16b581b0dd4ac8 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 317666 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 39813644 SHA256: c542173a0658eed60a103582930fe4e3ab2acb503467cf9b45037f8b061cf72b SHA1: dce5804019b3cee3af2f762f0f48eff5e7b98b72 MD5sum: 0396f2196d814837ba8f2e5256351ce9 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: 0.25.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 270 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_0.25.0-1~nd16.04+1_all.deb Size: 75928 SHA256: ff50dc68379eac24bf35721c821f0eb37276c6248cea6a6b17cc9da9724eab75 SHA1: 190beeeb3bfdb9f42f17cb21d3a165403eea81e6 MD5sum: a81b2914b467169576d94b2e79c2aa1a 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 879 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) 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_i386.deb Size: 150248 SHA256: 40e746aacc7d7090573c096de2a1373b1b5d9d379e6f2f6919e412c93de3e752 SHA1: ea236b848f09a501e08ebd7d7600ccfb683e058a MD5sum: 0ad739c044e3ec87b2e6f0c10093eab6 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 25053 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk5, libfftw3-double3, libgcc1 (>= 1:4.2), 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_i386.deb Size: 3903356 SHA256: c8105c8995fa781116dbc33f1691603577019eaaf4dbf7dede0fa79e437d315a SHA1: e3f0deded089d990dcea4d1d11f22bf668e819cc MD5sum: 6cc895849e8a39efd42755eff764f171 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 17420 SHA256: 6ce3d671beaf8bcebf28f5eb7622603de582c747e51acff2f3e094565a96c57d SHA1: edb7c13a86b6843affd65ae76c894a960b5ee70c MD5sum: 7be3efc90a22ea9e72393598ac5edb1c 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: 1.2.3-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 52438 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.2), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.9), libosmesa6 (>= 10.2~), libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.7.0~beta1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), 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_1.2.3-1~nd16.04+1_i386.deb Size: 25612082 SHA256: 4a1771aa30099c2e7bb635cfc83eb57aafd06489a2eb1ce1c8119f37faaf9c29 SHA1: dcaefe2cdb7ce25c623350219dcb62f56f4f774b MD5sum: 0b49c3261e25efcd634a44ad655a54b3 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: 1.2.3-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120722 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.2.3-1~nd16.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.2.3-1~nd16.04+1_i386.deb Size: 118887276 SHA256: c644144f2e146e9edd76c87f4fa9a7781a42af3b017a57facd45229378100a22 SHA1: 721af4f01034bb26658e2a32c9ae605338f6a166 MD5sum: c130e05d0343e6cdb6a8fdd7ec22a816 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: b149adfaad88aa680bf240ec81fe43293051fd55 b6677dc3b6035fa2f04d8eb8e36403e18df64f32 Package: convert3d Version: 0.0.20170606-1~pre1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54940 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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_i386.deb Size: 8791816 SHA256: 72194704807aa5362faf55ad55e22a3153dd3706491ea5cae21310200719a34e SHA1: 6658f07b29314be41f3d22e70d35a1fb5318afb8 MD5sum: 3d6d6fd3d6510129fb7ca7fd9c41f526 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: 0.8.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.8.1-1~nd16.04+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.8.1-1~nd16.04+1_all.deb Size: 68160 SHA256: 748f3472ac9636910054db91e9ce693d91adafb07472b669d62048c06cdfd1a9 SHA1: 4ed84fbdc6cbdd2596fff4cfc7bcc91f675bc929 MD5sum: 5b221e28efdda7ac7ce83aee65fe54dc Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package provides the command line tool. Install without Recommends if you need only core functionality. Package: dcm2niix Version: 1:1.0.20170818+git8-gdd1d994-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 562 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libopenjp2-7 (>= 2.0.0), libstdc++6 (>= 5.2), libyaml-cpp0.5v5, zlib1g (>= 1:1.2.0) Homepage: https://github.com/rordenlab/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_1.0.20170818+git8-gdd1d994-1~nd16.04+1_i386.deb Size: 133760 SHA256: c5c0c3f6529869182eb0f4289aab9556e118aa6e3f400e289e05fb2774765494 SHA1: d918accd80dc9adb7aed53a2f801b57afbac7a67 MD5sum: 2dddb26f6112ef568154f88d7c5d5eb2 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 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_i386.deb Size: 37108 SHA256: b24472a15422a78b99a56ac627ada323efe14988934465ac44850c3334b0e2f6 SHA1: 8ebbf01f1bf74e9265cc370a92c6e5e966568db2 MD5sum: f6906cde7bcd7fe06514372f39ce123d 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: 0.10.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 119988 Depends: neurodebian-popularity-contest, python-fsl, python-props, python-wxgtk3.0, python-six, python-jinja2, python-scipy, python-matplotlib, python-numpy, python-opengl (>= 3.1~), python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: science Filename: pool/main/f/fsleyes/fsleyes_0.10.1-2~nd16.04+1_all.deb Size: 13080378 SHA256: 9a0a8443b72288773127a42de703b41fd54e55da118c455ef74fdf35e99efe3c SHA1: 20c58a18264ddb07773e0a2e0161a304a1c2cca2 MD5sum: f8c4bc29a4acbedb874ec27eb258706b Description: FSL image viewer Feature-rich viewer for volumetric (medical) images. Package: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6333 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_i386.deb Size: 1340522 SHA256: f1efe1f594e7e5907c478561377ef86986171accd2e610ee7d2ab20b7cbd36b3 SHA1: ab1f070237e1b16a8c6294530043348fd9fd2d6d MD5sum: 8ce5634a8b111dbe779f98d02a56b92a 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: 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: 6.20170815+gitg22da64d0f-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 160063 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20170815+gitg22da64d0f-1~ndall+1_i386.deb Size: 35958818 SHA256: 4516a9ecd23766fffb9762c23c7c3e1b4ad6d4dafe9c814925f44ca8281ba606 SHA1: 14d890df0222b04d4712641dbb6221883065edf3 MD5sum: 070f641507328219f86d90d48833bc23 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: 0.1+git94-g85a2afb-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 91 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron, dcm2niix Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1+git94-g85a2afb-1~nd16.04+1_all.deb Size: 19482 SHA256: 9b80115f5bfc054e8bca6757b9aa6bc87037a5b09925657342d1ea8990d40795 SHA1: ef3b88e3339c47789c9809cad2818b2c72219304 MD5sum: 5a292432de6b1d070ce7b11ecf5e3004 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-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: 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1), libboost-program-options1.58.0, libc6 (>= 2.4), 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_i386.deb Size: 126932 SHA256: fe1a5bb2bcd51a09980f77fc42e5d524b87f76258ba1c74ad83c989606b64ea2 SHA1: b5f96ee9ac1b15623d6c0cb8fb1ccd4964ccd2f0 MD5sum: 78a77bb541fdacd9951cdc841a435955 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: libcnrun2 Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 266 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), 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_i386.deb Size: 83586 SHA256: 6aec06de5b9dd82338bb69209dff538d399b25cd67eaaefe8f3cf488483bf71b SHA1: f0db5454c9977985b10393103467ca956efdc7b9 MD5sum: ce5997ffba81eddf69bb0fea6d87941e 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: i386 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_i386.deb Size: 21464 SHA256: a00a8eee2ba5a11304edb9792b9821ef00a63203cdf5e013d9e1d24c08aa0ae4 SHA1: 162e9527e9e7b6d4745aa6ad10f14967747afc6b MD5sum: 1eae3870b61ac2c315fc8d5f01447e96 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: i386 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_i386.deb Size: 40844 SHA256: ab507cf52c7ba253e7d1b237ce70f3a9f0c13151508d5349d3832f6be3dd8c92 SHA1: a88012ac8f72f2993bc7290a8f0d8a73f05d8ce7 MD5sum: cb719ea3b2efbde0ea4a6f59bba05604 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 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_i386.deb Size: 23784 SHA256: 9b9250169ad37f99ab5e0b108a3216f42eeaab97ce34ebbda49d42c195c198e1 SHA1: 3dec4b445fec15078cb2f306100b5f26d1b98632 MD5sum: 0404e7543471ba79bc8d07d003aa57c7 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 86 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_i386.deb Size: 70360 SHA256: f050c1d671034ec5c3f4fa42ae6bc3250cbf24ffc7ce2003003a408e4ee8ad57 SHA1: 81e1e426e4488107140225fd037c7722348a70ed MD5sum: a06259ca15c8809cdda8b07583a2f12a 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: c103a83e59b04eee0f72d82d1a4bee8aaf609c78 Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: i386 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_i386.deb Size: 13858 SHA256: dcea28270e5a40f38043edec0361ec292f8375a786daf1fb2a45089e612de2b9 SHA1: 17d19a5c842f578a545edd7f0d79af3add7400ad MD5sum: 669d69c9af48b3884ee34c97d9a14af2 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 348 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 84820 SHA256: 16351d9ca61424eb182345452a905ba9a6daf576ef6e975dfd22bfe637c3818e SHA1: 8e6bf178067663c2b925285e4fada006956b0c08 MD5sum: 47b42af1be62067996d7603b7aa20c02 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: i386 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_i386.deb Size: 141876 SHA256: 4cafee002201c1f182afa1b27a77dbebfef6462181f7ead535dc8c1faf2d1f51 SHA1: 8821c26453866aae7657ec2a3fd9ad45d3efd7ad MD5sum: 8d1516ffa614eac8dd24e40dd2600414 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 516 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_i386.deb Size: 148488 SHA256: e79b75b9fc6fe573a616d4c9851d5020d8315ec722ccaefeacd84424803d0b9e SHA1: 2618892136aaa2c0331b8f9e560b5d3e5d334bfd MD5sum: c3a8a3bc78f801fd22ea969c36d205bc 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1189 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_i386.deb Size: 337494 SHA256: acaa0ad372978a81b0acd4c97e50b537eb145dbc0c25c3addd1e3c816a54dc7d SHA1: 4885283e09e537515e77afa992c8c4078ff38612 MD5sum: eb7f192d1cc4080ff3cc97f8f71c6a8c 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 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_i386.deb Size: 73776 SHA256: f54af141b368592475dfc0b26e61792812e0e13ba4e8f559bce1693c11daf143 SHA1: dc653fb028a9b03920f19ad82a28c890efac2e6c MD5sum: 11be562bef7f81529eccf9c7f309897b 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1449 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 431544 SHA256: e06d70a2078f2f31d0d7a9f04a595bda09ba7cf6099c7d92eee95b32a422cc55 SHA1: e0ea58fecfa30a15245a44e6f9777af492369ad8 MD5sum: 2b13af0fa2cf32257904482cd6b6018a 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: i386 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_i386.deb Size: 80982 SHA256: cf0cfe94f2fea068d6f94721aac46744faa907a08d93cc0ac263a5af5260dd68 SHA1: 5ead5441cc59ea3872cff6ab97ab9848698421c2 MD5sum: 6c116100d42f34050048e5e2b2130e97 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 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_i386.deb Size: 38750 SHA256: c80fd2bc6a0b0317cc4dd4c01109d846bbb7d5265ef9ed8b3ad4c73bd3eb7f6f SHA1: 70892c184335d477fad2a494103f78315280e9d8 MD5sum: 77eff624ebf8e7fbcaee74bec7f309bc 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 199 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 71042 SHA256: 6f82fe2431d077ff80c383b1ad61c89b12106a7c2de05c84cd1b67b911ac3dee SHA1: 044943d05e433d8132e83d6ff379e2323e894557 MD5sum: 62f8a67e65ab139d7e71da1e0883f13d 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 171 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_i386.deb Size: 140578 SHA256: 58174408e8cc80e4edb466d413a53c28e1ce6f4902af36ee0beec0ea3194de4f SHA1: 52757e64d2d8c847bec8f99316355487f73d742b MD5sum: 9d80dc6754bcc21652fbb28b0fbac8bd 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: 79bbd18e4ebde8ef0917a9b9544f4cf8b16925bb 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 62 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_i386.deb Size: 30920 SHA256: 0e6bc391cea86953dfeed426e80e83894bf0a1bc7f5cbd772b9ea342969007c1 SHA1: 3ea2fb828f44ab169a9efa5579a415b4fb42644e MD5sum: de569043411de8db808339df5b4722b9 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: 0.5.27+ds-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3568 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), 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_0.5.27+ds-1~nd16.04+1_all.deb Size: 702520 SHA256: 742ebc282de7535a74e7d787fd0e107da41b0e7881d9c40cafafb2643b8084a2 SHA1: 7fb0dd9ef3f84d2d367163d9ceaa0576ee5fb18b MD5sum: 940943a9bb929b8ba71132a49555e0b3 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 902 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_i386.deb Size: 591534 SHA256: 07d46926196aab72c925e0e5be2c5ece733e1904c835a6e4869ae1f8d7ab19bf SHA1: 71f5150fc561be841c7118269ce3149094de4ac3 MD5sum: 30c09d67af272d7236ff9cd78e0785d5 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: 3.0.14.20170611.dfsg1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4403 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), 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 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.14.20170611.dfsg1-1~nd16.04+1), psychtoolbox-3-lib (= 3.0.14.20170611.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_3.0.14.20170611.dfsg1-1~nd16.04+1_i386.deb Size: 897648 SHA256: 15b7f6aeebf4f4bbd333f6bf13f083305dc76aa86d0464fdfef2eb8e4300388c SHA1: d4783f72531b081badae3d67b3293bcf9047e549 MD5sum: bed128fc9833c1d5839aec9337c4c45b 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 924 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 372310 SHA256: 18e167f0049e39df9291720ecd22cb5226b98a59da52527c7626234e8f3810a1 SHA1: 700459cb47abe49df6afdcbbbe7c8b4801084f3e MD5sum: 81c38ca4a550ecd224373a033cc5e9d7 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4510 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd16.04+1), libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 1350846 SHA256: 8dc9ee3e577b960cdaffc7777bc40d0c01e4e40fdbebfbcd04de33f6d6fb3b5a SHA1: a89d357fab39bcb7d269942ec830e87c7ad5893d MD5sum: 2973ccbc1f4acc8d2872524a55092cae 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: 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: 1.83.04.dfsg-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15088 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-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython 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_1.83.04.dfsg-2~nd+1+nd16.04+1_all.deb Size: 6133828 SHA256: 7bc5b24a1849eaf939d573157788037c0f1f6a6a54bc84c45b025780d09b207f SHA1: 60bb27e236f204f1f43c10b98e20170e50ac4f60 MD5sum: 269a0abc067dfa3a1d79234abf54295b 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: 3.0.14.20170611.dfsg1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254124 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_3.0.14.20170611.dfsg1-1~nd16.04+1_all.deb Size: 24439218 SHA256: 66f79c0bb1eeb4d02c190a72f52ed0d0a492d2d8ea1f7ceffe4de0959827205c SHA1: a57290547c39e911b2cce861dcb0ce0ce87ac720 MD5sum: 6b44b6da8f60fa70c20f96943c45434d 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: 3.0.14.20170611.dfsg1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3645 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.14.20170611.dfsg1-1~nd16.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.14.20170611.dfsg1-1~nd16.04+1_i386.deb Size: 727414 SHA256: e31d4929f019fc833467afe08bbc6ebe7d351ea597dd231f92954b6521f40101 SHA1: bd2ef9c4382ff34cf38d88a04953e58d6c794196 MD5sum: 548f0b844b8c19f292ad17a0243185dc 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: 3.0.14.20170611.dfsg1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 180 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_3.0.14.20170611.dfsg1-1~nd16.04+1_i386.deb Size: 74830 SHA256: cb9e3ff97226c8966ba040f2306ce788d8276eab6f3ff8bdfea546cffb74bc3d SHA1: cc5251e98ce9d5460d3dbb577e30441c65f19685 MD5sum: 39f30259561b6b18cee31a39ff84e8cf 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-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: 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-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-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: 0.8.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3738 Depends: neurodebian-popularity-contest, git-annex (>= 6.20170525~) | git-annex-standalone (>= 6.20170525~), patool, python-appdirs, python-git (>= 2.1~), python-github, python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage | python-keyring (<< 9.2), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0), python-wrapt, python-boto, python-jsmin, python-pygithub, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-requests-ftp, python-scrapy, python-vcr, python-yaml Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.8.1-1~nd16.04+1_all.deb Size: 727752 SHA256: 10f43746a0d85513150b4c607fc9c891ade7cca3f8a3f7deb691a82ee0c0a586 SHA1: 8d22ef36b66a15192a17d50bc0f04f9b29acb50d MD5sum: 1fd01c5c65f2e7f2dfe5e4c7518d64f2 Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling, publishing, and testing. If you need base functionality, install without Recommends. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 505 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+git33-gb43919a.1-1~nd+1+nd16.04+1_all.deb Size: 77560 SHA256: fb442364f1761b5203c259ef22654f0f4bb883a8eac5dba645ca88b0ec327125 SHA1: 809e0e779921d515682e8f3b543df9321b89650c MD5sum: 307b067807c7a48930ebcc46f0121e7a 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, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dipy Source: dipy Version: 0.12.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6926 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.12.0-1~nd16.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.12.0-1~nd16.04+1_all.deb Size: 3019600 SHA256: 37582de0ab2094ec94f9f2422d805259eff4b038b9d92d78d498e27493d0dedb SHA1: 385aa2f1b34f6fa45962a396814ad1f9b4c6e05d MD5sum: 519ef78f80c4d03e85ef664e1b86f192 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: 0.12.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14106 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_0.12.0-1~nd16.04+1_all.deb Size: 10507060 SHA256: 38635a4f7523bfb2b54a44935949b1399ae96bb91a6d5e332ee729c7381e1f89 SHA1: 8e6362f2d7c70d33b43476f8ace3c9be491a7a18 MD5sum: e7555c627a7a23b4bbe8a067e1a31019 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: 0.12.0-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9754 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.12.0-1~nd16.04+1_i386.deb Size: 1489466 SHA256: a650709d75319091c7dfc6c326885f9c2bab78a2735805f212c75361638f95b2 SHA1: 915e0d4a8e9d1c364d4f055fb88e70f5b2c417cf MD5sum: 44d16378e5443c69caee7c4feebb4307 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-fsl Source: fslpy Version: 0.11.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 467 Depends: neurodebian-popularity-contest, python-lxml, python-nibabel, python-indexed-gzip, python-matplotlib, python-numpy, python-six (>= 1.10.0), 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_0.11.0-1~nd16.04+1_all.deb Size: 96802 SHA256: 9d0dc46c855c2ab828feca334bd12560c9092622e4f5491779a4c54323bde32e SHA1: f14a921c9f71a5b8f61ca3608c34d34c9be6f48c MD5sum: 4b1169619f1f77565002c1f642c8344a Description: FSL Python library Support library for FSL. . 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: 2.1.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1629 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_2.1.3-1~nd16.04+1_all.deb Size: 300458 SHA256: c9323cb6fc035b2eb6fbac4ddaea4ebc90c983dd408cb8ef015bb2ccc0ecf673 SHA1: af6dbe1121a8063a81ad756915c906900bd4a53d MD5sum: dfc0a3d83e4eb3a3f7c62876ff5a3513 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: 2.1.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 979 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_2.1.3-1~nd16.04+1_all.deb Size: 126168 SHA256: 3759ef70d91c2a9a89b9de6dc98ef0000f86046021b14df489df8e77b42cbc53 SHA1: c3f5c062fb7f519106c5871d0f3ff77122cd820b MD5sum: d5b2fc3e86a3b2302f083d7b02ebb53e 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: i386 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_i386.deb Size: 46190 SHA256: 2df6a65b71952ab348c8c3d44e2e030dae82d2d3adca551694f02e55d5ad828e SHA1: ef649013359245288beaacc9b7ec98d3b9227f92 MD5sum: db181b007f161a80ce5dd4fca4667f4e 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-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-joblib Source: joblib Version: 0.10.3+git55-g660fe5d-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 488 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_0.10.3+git55-g660fe5d-1~nd16.04+1_all.deb Size: 116086 SHA256: f2afce84d554e1814e05e4df962dae90175aae9a02cac1816b078392afc9bdd7 SHA1: 964611d58a727d1177c0f427db00e6faea0a77e4 MD5sum: 52e4c90d4a25874dd9a1756dc1f0a67d 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-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 239644 SHA256: daf3122845169280e8e30633326244a8b5ef2c9d1e0fb5199c76abd3cf75c0ae SHA1: fa34f456c580b97672e21a1e27083c52d439a151 MD5sum: 936f2ff623a4f4ef8defe59f53a00e37 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-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-mpi4py Source: mpi4py Version: 2.0.0-1~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1560 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.10, python (>= 2.7), python (<< 2.8), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_2.0.0-1~nd+1+nd16.04+1_i386.deb Size: 326584 SHA256: bb3b907c15968ed6ce3e17e553c6ae4f040e442449438d0d2df99278dd3bda49 SHA1: a6a2a895f4dd8804ddaf0fedbd4c0b730cab41dd MD5sum: a4e4ac735c9934d73ea6f2cb31be8979 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3596 Depends: neurodebian-popularity-contest, python-mpi4py (= 2.0.0-1~nd+1+nd16.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_2.0.0-1~nd+1+nd16.04+1_i386.deb Size: 931836 SHA256: f49d56acb738fdd1f0d3f1a1da03d8444c30af43bc179292578e3a4572e32f2e SHA1: 6bfc08b16ce9dbe1307c5cdd690bc916f5180979 MD5sum: bf2a7759882982b2d9e9c72ed6c81dd9 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mvpa2 Source: pymvpa2 Version: 2.6.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8560 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.6.1-1~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_2.6.1-1~nd16.04+1_all.deb Size: 5101034 SHA256: 18927a3db579dcc461e507705b152cc183d57e595a4b405560a784a1baa28378 SHA1: a7b1abb6a0a907f8e8510ec1a72a6ef210fc0892 MD5sum: 205f79a00fd5c7898f4001e9f65ad675 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: 2.6.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36253 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_2.6.1-1~nd16.04+1_all.deb Size: 4648838 SHA256: 70e1af36e47816135b87bb22080a204ff1399f6557b4ee0fdcbe2ebc64f7b2d0 SHA1: e1794ad10ee26b1dc1544e9a7875818016b6917c MD5sum: 324b15487e159732a0a8d623356e4eee 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: 2.6.1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_2.6.1-1~nd16.04+1_i386.deb Size: 51634 SHA256: c6a02d223577cffe3fd64535b1fc7c089855ea1e1596cd8b352bc39f65d197a9 SHA1: 21b0058267362a34aef711dbf63d55c0328a048c MD5sum: 07aedd6f45543b3904dc06173a1158a7 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: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64211 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy 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_2.1.0-1~nd16.04+1_all.deb Size: 2161982 SHA256: e1c42772ae8c2c60f721d9002f9be42cc734ffdd2a0af7982ff72286cb0ccef3 SHA1: b3b4f34c4995b562befdf801cede8ca5e39cd4ac MD5sum: d7ec21b39d1014be8930de0cbdd8ae9f 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: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20346 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_2.1.0-1~nd16.04+1_all.deb Size: 2686026 SHA256: 6f0f3b598a2f8d45f9ef7266c1644d5fc094b7f6f3222bbc6810d6ceb90b6209 SHA1: bd2001cf891ed8b707ea486ef3f1ecb1756a8e04 MD5sum: 3943c2901476d4803c7916457420dd2d 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: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3545 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.1-1~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_0.4.1-1~nd16.04+1_all.deb Size: 781470 SHA256: 33d2482335b24f2d7011e778dcd02d55fdae909063434d5ffe8083e11a70743a SHA1: 49ddb079f28d33163d83b84f438e1b6d71f59ea8 MD5sum: bc7ceb7f5fc4d49c39910264c8f217c0 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: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10732 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_0.4.1-1~nd16.04+1_all.deb Size: 2629682 SHA256: 3a0f0cc4036630a705f075663548767f72e30366e01df9d00525ccbe6bcbdaa2 SHA1: 59ea62c2b3928698e65bc0ba3549f235c3c8d1d7 MD5sum: 748e2f23df7737789c6552468c6c40c7 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: 0.4.1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2726 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_0.4.1-1~nd16.04+1_i386.deb Size: 572146 SHA256: 80295f37c5d213f754e42096ccc6b93529fd9536f85956d21672674949f9bc80 SHA1: 8b8953f431bf8bf26c6432a927af41c81f940054 MD5sum: e6abd451d949b2c12d098b4c846a369e 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: 0.4.1-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3157 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.1-1~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_0.4.1-1~nd16.04+1_i386.deb Size: 449892 SHA256: 0946068c07fc0595d95807feaf628e6d062b321645e082ad5fc18527cfa94dc8 SHA1: 93887de1b389704f0489b4edc8c14bbde7894e8a MD5sum: c6d0ba661cd288cbc0cf4a41c6c2fe3a 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: 0.12.1+git4-gbc3a0b5-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9364 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib, python-funcsigs, python-future, python-prov, python-psutil Recommends: ipython, python-nose, graphviz, python-xvfbwrapper, mayavi2, python-mock Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.12.1+git4-gbc3a0b5-1~nd16.04+1_all.deb Size: 1534790 SHA256: d6d24f37e41d190609c5ab1d72c262ae412c6a41ec3e85160a0fec6e1705709d SHA1: 7648c0b0acf90c6e78db46d33f8690733d1d809d MD5sum: 2ae984321bf33797a772dc1c962b9d5d 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: 0.12.1+git4-gbc3a0b5-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 30429 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_0.12.1+git4-gbc3a0b5-1~nd16.04+1_all.deb Size: 12830732 SHA256: 3829a209775209162000cb503489a73e85eb6c8a9170db3dde0e6e933856da9d SHA1: cbeb8ee31ae76ee8ca5b1784c4e150a336ae35ae MD5sum: fa1d56284d197454a4567cfdb52bbcb4 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 476 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 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 130804 SHA256: 9fc806b626f6aa4ccb8aa86c6c22a7a7da8ce9f6578e591bd73a56e7ed60a954 SHA1: 0c69ec4247aa6dce07319eb2862dba3536514e34 MD5sum: f68d9735928e9f1d939f865a59342359 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 342 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 98960 SHA256: c307b39708be19546bce44fa8b1e0d8a1d91d44b3a993d50bca3df245ada7632 SHA1: 3227139331fc59bc757f993709122a4bb1acdbd8 MD5sum: 38544fff84edc37df9549e82c1e56068 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8251 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 1812822 SHA256: 17d6774e33296cd4e0492ee53b3dbb570319ae7f0e97398ec0d38ef83272d4d5 SHA1: 3958ca1295f467ae908532605a64946c670d6288 MD5sum: 0a4449bef3282064fb23f4378f76e598 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-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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1444 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 (>= 2.4), 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_i386.deb Size: 278894 SHA256: 923ebba439458ed2c1ee0bf80d5ed1851bd98b9e63752ea6eb07a2af3f30d151 SHA1: af2184490807cf11c558e341d951ef0015c64336 MD5sum: 22b36e8ca2235e328bb2f21863d1fd75 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~rc1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5414 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa 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~rc1-1~nd16.04+1_all.deb Size: 1124270 SHA256: 8255c905daf70d3107acab04cd8a7f54cec31888cedbef2e851863412908285d SHA1: b60a711b5846c46d3c0ef37a976850adafad4ac3 MD5sum: 39a0f8c4f6f30757e9192c960d5352d5 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 390 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4), 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_i386.deb Size: 74872 SHA256: 541730ea83e282ea8cddaa7039d2498f4f8e015b18d28e8bfedd803d758737ba SHA1: a7ace86de19639acc916820d6d30444175450d1d MD5sum: 1e7e25c5b02003cce9b61bbf17407b63 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 243 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd16.04+1), python-dbg, libc6 (>= 2.4), 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_i386.deb Size: 103418 SHA256: 7444b88f9733c85c62018a7223a88979f26a05c3f6bec2a6d9dc870cf23d549a SHA1: 6b4accda0d2075542f58d52457b2d5ccca209ded MD5sum: 4b091025d0a92420e55553a50078ee75 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: 7dab8fd2dec1c75e17c386072fd825a0c0cc0206 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-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: 0.19.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 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_0.19.0-1~nd16.04+1_all.deb Size: 83678 SHA256: c3360b4e17e2eb084f89a8dd6da890038469c0dde1422e6122ffd41fdd0a9238 SHA1: 438e2919621991c015acc1f99aeb57e7f5e705ba MD5sum: e5c816d4f7d7b4cdbed259d99b827cd1 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: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11102 SHA256: e53e9566f3e3305d5ec1a8b3ed6a12f61a5f0d3279112666903e47ce68c4498c SHA1: e2e8f56e31d6f67994297cf8ef87bd10077f81b0 MD5sum: 19367b5b0032f4ee89cd3f543ed27e5d 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. 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: 0.19.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6995 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.19.0-1~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_0.19.0-1~nd16.04+1_all.deb Size: 1450060 SHA256: c172dfe7e176cd7da4b65ac1f7f8cac95d361a916791f4541be4cbdec65d1c59 SHA1: 8689ede1f31234a9aa3257f77e173dfb9972a683 MD5sum: 57520eee7d43b453f81a092b41e59e2b 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: 0.19.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32862 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_0.19.0-1~nd16.04+1_all.deb Size: 5262564 SHA256: 289acddb1ee1cfde93a3bacd947c25ac05a230403943f45b5e0e030cbaf9a48e SHA1: e85c3bcb1f0de47ec966e7a1011b26ea0abaa31b MD5sum: e9f111520f8fe598ed796329fefbe8ff 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: 0.19.0-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6756 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_0.19.0-1~nd16.04+1_i386.deb Size: 1356250 SHA256: c5c445023046ec26a62575b22d2db2c570b83bc6493b560af4039f492f1f908e SHA1: 54e301c366dc359687d4cb05967b338005a4736e MD5sum: af88740790d75b8edc38d1130c814cd4 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1567 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) 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_i386.deb Size: 221178 SHA256: 1a2f8f7727b1f8d3069b82971e13dd73cef3ab961693f85a5b75eeadb14ee5c8 SHA1: 8f6044d4ad59905aaf9df2d0da7289643055fa18 MD5sum: ab79f52d280aa9033432dffefc2a955a Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.15.4-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1435 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.7), libcholmod3.0.6, libfftw3-double3, libgcc1 (>= 1:3.0), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4), 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_0.15.4-1~nd16.04+1_i386.deb Size: 508476 SHA256: 8b913028df438d841d19817e72a28cac3f12a5ca14775c3c9503833839e83c86 SHA1: 9a1c8b564f8a28b4030a72c66ee3c390dee3876a MD5sum: 8b73c4713ee2d9b1359257b8f6940a28 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 488 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_i386.deb Size: 87080 SHA256: 4760c6af91321baabaeb4158174964740a65941bdbedfb52447372c60ee201e2 SHA1: 97cdff78c4c2d4dc247c243c1f90c8667c8842b2 MD5sum: 358aaca9d9889e941d7ed99cfadc997d 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 119 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_i386.deb Size: 28144 SHA256: acde86261e1c92f30348e86f2c42b3332eb53a418660a2d91a02d0104cc94d95 SHA1: ca51dc3c2c156ad6dc3464b00f6b32d37bd12d8a MD5sum: 1233e0b63988ab587adcd5837ab3f960 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-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-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-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-fsl Source: fslpy Version: 0.11.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 464 Depends: neurodebian-popularity-contest, python3-lxml, python3-nibabel, python3-indexed-gzip, python3-matplotlib, python3-numpy, python3-six (>= 1.10.0), python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/f/fslpy/python3-fsl_0.11.0-1~nd16.04+1_all.deb Size: 96574 SHA256: 0a2884dd6399c971f41221c7e4228afa837e4c7b55e26bc36ff2b3bd12da4a50 SHA1: 7e9ebe9160177ee123816ff16ac86f4030b9e027 MD5sum: 353347bee1274811d87479cf200ad655 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: 2.1.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1626 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_2.1.3-1~nd16.04+1_all.deb Size: 300296 SHA256: 012f50cea7de4300759d4533fab885990fbc27e888f7fa27a9667a8eabc65481 SHA1: e0e0cf5d99b162ea095fd9e21b279edaf826e2d3 MD5sum: a1325de170fb21421b388d0174296519 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: i386 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_i386.deb Size: 46238 SHA256: 62fce95c4fa9e82754bc50477de0c6a631c717883fa92285b132c73ee888907e SHA1: 1ecc2b76efe3fdb4132ab469553545a089faf0b6 MD5sum: 92f842e8f6e98507768de05446cf38b0 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-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-joblib Source: joblib Version: 0.10.3+git55-g660fe5d-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 483 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_0.10.3+git55-g660fe5d-1~nd16.04+1_all.deb Size: 113338 SHA256: 03169b9c6a9216b6175927bd15a8e74d916423a0660784f3a31487cfe99da2f7 SHA1: 0fe2a1b3e1a9bee5f90370b4d9f2446921ef42fb MD5sum: 684986f976bb5e4671f007b0ab8f381d 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-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy, python3-pbr, libc6 (>= 2.4) 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_i386.deb Size: 239982 SHA256: d8f3a5a4bb3e05d1049996a5ed93046361b8765175f6eaec598823e7258a8ccd SHA1: 50fc85fa7e348d469afaabd98f941778af35a401 MD5sum: 33a5928c9ef2868abc96237486045bf2 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-mpi4py Source: mpi4py Version: 2.0.0-1~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1513 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.10, python3 (<< 3.6), python3 (>= 3.5~) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_2.0.0-1~nd+1+nd16.04+1_i386.deb Size: 322630 SHA256: 6669d53787a4e5083971862f0f2b89b50b95be6550f1472eed19c9e0c4024993 SHA1: eb93185bd8a85a54d65a37e56a343794cd7e8b8a MD5sum: 5a65d21ac8529e13e227d277839ad5c0 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4137 Depends: neurodebian-popularity-contest, python3-mpi4py (= 2.0.0-1~nd+1+nd16.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_2.0.0-1~nd+1+nd16.04+1_i386.deb Size: 1067992 SHA256: bfe992781bd7defc416e7638cb44cc8c5f68ba705af1c2a0780669a38111b43d SHA1: 492bb2ab63f57c77b1be7b6b0886fb353ba65f9d MD5sum: 2b36e6a86e7c561c8e993553289ece42 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python3-nibabel Source: nibabel Version: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64183 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy 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_2.1.0-1~nd16.04+1_all.deb Size: 2154656 SHA256: 9c760991a0a887cdd65153791a3722534203cdf66dc16029f99c2ef9fccec0cd SHA1: 5df7ed77d30ce807373999d8294e95f46bfa053c MD5sum: 2fa45514b87aa0c0e6e6c3252b76f3a3 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 467 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 125060 SHA256: b72b86fdfb2b8867ee3a959649225555540f4844069dd7a7aed025a26da2eee5 SHA1: 90900574d20cecf06642a4df5bbaee775f3dad99 MD5sum: 259cfe629032b02bb5358fe27149d622 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 342 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.5~), libc6 (>= 2.4), libgcc1 (>= 1:4.2), 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_i386.deb Size: 99054 SHA256: 411e3e71bda8ef58ca55fd952c677d1e2a4122a3b93b10efaeb7d944838cdd6b SHA1: 24492c41d47728e72ccb4ec7a36905215141516c MD5sum: 768d0028ceb06b1a98f05b72b12107bc 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8143 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 1782260 SHA256: 4ee0f87edb49b2958348794c2ac6eb1bb42eae774ac342656d2b028e3826ee01 SHA1: 660918614f86678f5185afd8fd3f9732034b7bb2 MD5sum: 279ab617667ef728f75576e900607307 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-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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 386 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.4), 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_i386.deb Size: 74786 SHA256: b703919cff169d89f239bf8c774756472bb48283571bb672417544cb3a087600 SHA1: 9ef45c2528df844bebb25d196d809680d0bb1d20 MD5sum: 9d190c98c43724e6d3a7f3852accf5b0 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd16.04+1), python3-dbg, libc6 (>= 2.4), 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_i386.deb Size: 103342 SHA256: f354506db47d2c178a6463db75634d74baede880863474d4920b497044db613a SHA1: df661eece00fefea2530505e8885a37ce283ec62 MD5sum: eba99d2d6ca3e3b10535ea37169c1b04 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: 3dc438e0c3b0f9f0b459a9385574c62030113ba6 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: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11162 SHA256: de89c30fb266478195674d595d12a1513db7e2956c8af953ce1f2720e45d4ad9 SHA1: 4c90cc7b7fc37bedacd44c403965b35de5a1751b MD5sum: ab68168bc1f5b17416eb4c2f602f33a3 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. Package: python3-sklearn Source: scikit-learn Version: 0.19.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6994 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.19.0-1~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_0.19.0-1~nd16.04+1_all.deb Size: 1449806 SHA256: dc59b6251bab62a74e0e965cdbd7db69079bef9bcfdc1d388068b2da3932d465 SHA1: 2aca43381d24b1ef3be00688d52a03af4b1eee56 MD5sum: edf6f6978c6fa00bdf9a9f75af32d53e 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: 0.19.0-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6253 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_0.19.0-1~nd16.04+1_i386.deb Size: 1264910 SHA256: 47de9487cff66205ad68a3de3de9658c37bbaec1dc7922b57cc998993a184642 SHA1: bcfc09918253ba86f794f77ddb525c5abe0c38aa MD5sum: a62275ae4cb2c16cfc97efc15742adb5 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 119 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_i386.deb Size: 28236 SHA256: b0d08b7d95eba77365e6d093c54af4d93b7a18bd77b358b007488636fd85f4f0 SHA1: e79e67bd79562009b3fe098a3d15eb49286725b0 MD5sum: 51e5a25b18b7797f9c3e3ecdf5b18564 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: i386 Maintainer: Debian Go Packaging Team Installed-Size: 10498 Depends: libc6 (>= 2.3.6-6~) 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_i386.deb Size: 2843042 SHA256: 66e28221c2624e00ed7486aea2001e9ee3642772f21f224fc153a93a2fc1e5ba SHA1: 63fa3d3cc336295d45b921981dcd235fe487ac63 MD5sum: edd5dedd27f7c1e243034b1e4abdfeb0 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+dbg1.1+dfsg-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 326 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+dbg1.1+dfsg-1~nd16.04+1_i386.deb Size: 155238 SHA256: 28624e41b64478f10f2d76619506df6ac128ada3a9bacc0afd2d34c7db06ef1d SHA1: 5d42d2d225f14f9bb8182d00108508a9321a38fe MD5sum: 44b2cf467609f2a0db0e18e6143cac73 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: 2.3.1-2~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2363 Depends: neurodebian-popularity-contest, libc6 (>= 2.16), python Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.3.1-2~nd16.04+1_i386.deb Size: 268758 SHA256: 477ce0595be7f8de4518fa7ada9a09d21adf64e6d86f9d00cccf9f0fcb1dd973 SHA1: 83f83d14ac315ae22f437e0a7b64e3a080a8a9e9 MD5sum: ca6cb01976c55b6fceef20fbc2bc8b6f 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: 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: 0.15.4-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3078 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.7), libcholmod3.0.6, 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), zlib1g (>= 1:1.1.4), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python2.7, python:any (>= 2.6.6-7~), 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_0.15.4-1~nd16.04+1_i386.deb Size: 942344 SHA256: 0374ee72e12ea2a611b2639069a96f70323d27e016d323f73f48fa61fcca1a13 SHA1: 2d9c784cc195db9a84666d61dbe3f24c7f230914 MD5sum: 8e4b4f60a5b91b2a4b02eec81f5ff55c 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: 0.15.4-1~nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 23712 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_0.15.4-1~nd16.04+1_i386.deb Size: 6207900 SHA256: baa56d452ee725a28e0f1ec87255eeea9255c01f43d533f1e8ad7079e1f5f3f5 SHA1: 623b2835675065f94f5bb9abde0ac1a8816a0825 MD5sum: db68c627306715b8feb9d39115ab762f 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. 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 535 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_i386.deb Size: 170462 SHA256: 8f207847198bec6d1083498bf424f33b195cb7447c7820cfab9559aaf528510b SHA1: 2fad39a30fac59fbc2c53928511dfa685451dae7 MD5sum: 2057b630b0c0625f0868692bce95fd4f 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17339 Depends: neurodebian-popularity-contest, libboost-python1.58.0, libboost-system1.58.0, libboost-thread1.58.0, libc6 (>= 2.7), libgcc1 (>= 1:4.2), 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_i386.deb Size: 5703764 SHA256: ebb8267558c74ea02cc8afc4be9921cf33bcd37c1df6412ae167b7c6e47f9a4a SHA1: 4740b8aa256ed67ee6ba7089ce4ae68ea169e11c MD5sum: 5aa1d3f2d7316c9b1244e06d15ceb2c3 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 46548 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_i386.deb Size: 45772554 SHA256: abb4e44ad117b6e92434ec9fd7ee1a7e5faa35c7cb1573715dfa0d9ea2d7d965 SHA1: cf8e13675d290930527e7b120ee266eaaea5d4dd MD5sum: 2c184c9af8edafb7e45ae61d787f58ea 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: 05781c434758df4b8402d74c581015789b4ee8f7 0c1317350e6f0c1bb3d0c2034a282bfd0daafe72 190f982c406e30918315487e70b95b73f9a02e37 21324dec4e1bf1f22ad32b2c60f3503f4067f156 372b7a7a932e9a701b1b3d614f1c2230d7e05903 3ac225a09cdba9ed962fff95019c98653981c3c0 50cd4a3c77ce7f073ca0ce54c0e12f36409eb9ef 51a085de6942720ebbd24c499b148b6501f9d239 581382ef5d099d28a2fb43b36d90983e4871dc9d 66fd2a42f7e4cb4d1b07c9b6f0ffb71f4a012e3d 71527ffb74d0170a04f6e99ea23567c0d7056914 7a61a123274d3cef58796c7c2acbd6bf2220af56 8664c3515f8f3f9593ec709ae407cd01ddc72f0a 88aa5af64b28e67aaee92c75a1563483ad62aa93 89f9a632f7935f0c96fe50fb0878c929dc13abab 8d4232b212809f88405ed0d9bc81d453b23a13b3 9063088bd12cba1d80a158c746b997cd6651c0e4 90b4c148dd49199bd52ff5cff3d0a4722c004d54 93103e3f26cb6b24308be5018f8a2cd66f00c04d 9485ea2e489dfdb5b03f27b61c3f19efa07888d3 9ce67df3502f228aa2ee930928ed9ea0c64de94a 9d5ae6e0fefcfc3da54a9ad2798a52b6c80f7c55 a34ff5dba9d1e9bbc0f1fa0d950bc14baecfe375 a455461bb0adedb339a53809b0fcfaf5e0356383 a4be70c9a7ea648efee42ca885edc19f1fa07e86 ab9b4d61be640bc9dac2683e9f623c564a6452ad ad72431abb8c0821acc144c7e0f14b23ab1fc6d7 ad7786a325330055e1ff545f59bdf9dc67e4d3f0 b02d5e44f7ccf2315f505d0e50d60d11864952da cbe524004a949a546efc51da053304ef3031f796 cd59b0b7f019e631003fbd0e143dc39c19fc6827 d1bb09da00fe44a7bc29bcd9ac41790fee08dcc5 e50679196a978741c5b21e8062f8d01cb417f703 ea01733d1cd2f1369136157fe37db8c81204a448 ea522e57fc6fcc2db3baaacd6ab1ef67d599fd24 ed7d20bf1e73e868922cbf9429ba108a5b5faf8f f446124dad7e29117670284d4f61e7da6f3ae871 f93139dc7926d78502b3179e375ace423f7d5e20 fbc0005c1d18155bf9d624c8898e8af1d939ce65 Package: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 50080 SHA256: 52adb68e9d82018dea964fc2379dbdebd7a5542c0d0f73716a69dd757e7d964b SHA1: 0c9153900f900b5bc52f1ec1033266288fd23099 MD5sum: bfc32a2243716481c3713ddfebf6b217 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3519 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_i386.deb Size: 889098 SHA256: 8a17d17e7f305b6cf58d3d0b95ad602c8160d2357182b4c00824f16b92fbf0a1 SHA1: d98f0672bc8091a9222d3bba3fc4f2e6104653f1 MD5sum: 2cfb9bf52fab2f412f784a1894952fdf 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: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_i386.deb Size: 74396 SHA256: edf5a859a468884f5f47ec9e9707b16a531ccfbaa0d6b6322e01698d1ac72f61 SHA1: 3d222700d951633a6c194e0cbdca19e4da7be398 MD5sum: 858bf00e216c7481083d12cf5a4cc2c1 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