Package: aghermann Version: 1.1.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1585 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:3.0), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl2, libgtk-3-0 (>= 3.3.16), libitpp8v5, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 5.2), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.1.1-1~nd16.04+1_amd64.deb Size: 514928 SHA256: b89f724f495b2351f9adc3482851ea5c6217cdd0411b253c9d334ad00a17e3fc SHA1: 5e29a5129e00211cdf429ba0db3e3fcd1cb85f57 MD5sum: 04118e6ce11df5c69257dd8fa440a60a Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: btrbk Version: 0.23.3-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 255 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_0.23.3-1~nd16.04+1_all.deb Size: 70918 SHA256: 7a613ae50cc61b506f1bf531528fa2d7c677e2abb1206d7c334db906f76b4858 SHA1: 08a2ae8cc13dad61bcec586faec577b0c4616024 MD5sum: e9565fdc7f21b8f3dd449c357c1e823e Description: backup tool for btrfs subvolumes Backup tool for btrfs subvolumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations, with ssh and flexible retention policy support (hourly, daily, weekly, monthly). Package: cde Version: 0.1+git9-g551e54d-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1019 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd+1+nd16.04+1_amd64.deb Size: 146038 SHA256: eb56362a6b3ce0989408660070e532c3daf16c3c2b3370fa3f0a72482b65d6ac SHA1: 2f18dadcc4d3237870e8d22c399dc1001e0ac009 MD5sum: 3e45cf198b6c729ae80dd94f03474114 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cmtk Version: 3.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27134 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk5, libfftw3-double3, libgcc1 (>= 1:3.0), libgomp1 (>= 4.9), libmxml1, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_3.3.1-1~nd16.04+1_amd64.deb Size: 3812882 SHA256: 7bd11292411aa5591adfd6b713c87ec3e9a7e65c3ad9c35167bd304f4dd33ee6 SHA1: 4cecbd124bdca46f244790b49e499a952b345a00 MD5sum: 5061e29e36890eb9b9b21599c0be0d24 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cnrun-tools Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.1.0-1~nd16.04+1_amd64.deb Size: 17520 SHA256: 696816b47a80ace49369085919d567aaa0811146e427c2381d790464c2b3a3ba SHA1: 9b25b44d79a5f4343edd4e5b1c1c0ecf972b34cd MD5sum: 9ea4b4b3841514f19d814316fa3b7e5b Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16238 SHA256: 924a250e1bd7ec5712ba4e4d1b2a205ad154b72c7d38a5ecbd2fc0fccea19429 SHA1: ba5cbaaa726fc483256e9f5290e0149d81075b95 MD5sum: fea7b065cc3515413551b14dca22889d Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16248 SHA256: 4bead7f7bbc458cb62193c47d509c5542ccd6a78587e7b31b1e8044f9dfb0fa6 SHA1: 6e4eafa61b7512a8c44323d03cc98552d85e02a4 MD5sum: b44e2b9c8a82520233d2300f279d7ef5 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16250 SHA256: e3ba0b70729b2cf5a31e7520a8139429bee9ef72e77e8d7e5b8d91be52d14b40 SHA1: 1be8c0ca974ff69b8119b248d6c21fa48ce2dbec MD5sum: a6b3362321345b33de7f9c94f313ee55 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 16242 SHA256: 1dd6eca6bc2317250e89af6c59c499f3b0bdd2caf7fde1edc3511dba3cc94046 SHA1: 6ab39f994bfa2d1e7f16f12a6f8d22e1b9900a9e MD5sum: 0628b2da9ac86ab37554bb2ea191b358 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: connectome-workbench Version: 1.2.3-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 52636 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.0), 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_amd64.deb Size: 25356218 SHA256: a7fe51f45f0e2bd358674ac383465c3b3ae679b4e43278e94b415d299bf1a721 SHA1: ca31cede98067c297be0f0876d5044b96c63a418 MD5sum: 1e2f1c4597b6afafdde797b6ebf52789 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 126627 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_amd64.deb Size: 123958676 SHA256: 1a7b1979c6a2c696b89dffa41f02bf21b3971a1e8edbf87786ba7a70de9e0ead SHA1: 9dc546da08b3091afeb75ac9520771baf890a433 MD5sum: 7f12a0b7c518e6646ac03f800cb9eda0 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: 736c8896849f66c8e9e7004b5f642d333faa85fc eff84d745cdb0066fdc72032eec60de215d6f5f6 Package: datalad Version: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.4.1-1~nd16.04+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.4.1-1~nd16.04+1_all.deb Size: 48188 SHA256: 11404c034862517933e44f648554a74b94498c96bb0274be473091a519e39705 SHA1: b728854c16679aaf446d677bd0897589fe9dcfa0 MD5sum: 308de7ffaa56e79d954c2c04308e9171 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: 1:1.0.20170130-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 280 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_1.0.20170130-1~nd16.04+1_amd64.deb Size: 116272 SHA256: 75d26b1c3d1a3b5f29ae2c3757a80db81941b22d53ca5e4350e0916070b5ab22 SHA1: 54d5ebd34b4d557c13680855a4bdd3749600cab7 MD5sum: 2dea5df0cd8ce1281e939aa9f6980b9c Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd+1+nd16.04+1_amd64.deb Size: 38404 SHA256: 4fb44a4b64ebac715085eedc85f4b47ec9b8e642670af3ea6aac74ad3a1b717d SHA1: c80b3c636dcaae3c569696434d7d3e0fddc25544 MD5sum: b591bd9be2b09aef38c2a05fd449a773 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: docker-compose Version: 1.5.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 267 Depends: neurodebian-popularity-contest, python-docker (>= 1.3.0), python-dockerpty (>= 0.3.4), python-docopt, python-enum34, python-jsonschema, python-requests (>= 2.6.1), python-six (>= 1.3.0), python-texttable, python-websocket, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: docker.io (>= 1.6.0) Homepage: http://docs.docker.com/compose/ Priority: optional Section: admin Filename: pool/main/d/docker-compose/docker-compose_1.5.2-1~nd16.04+1_all.deb Size: 76930 SHA256: 316cea0fe5c368a1842c83370416a42eb29e3932fefa0d1465a86bd5dd6d8e49 SHA1: daabface947f49a630be5939805f0aa9706a4ce4 MD5sum: caa54173f115f40f815c49117eee989c Description: Punctual, lightweight development environments using Docker docker-compose is a service management software built on top of docker. Define your services and their relationships in a simple YAML file, and let compose handle the rest. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8117 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 7059424 SHA256: 3f090fdf3072e4e5b6ac524be1fff62f6d940c0e49f39e0843ba76d43e5b7d2b SHA1: 3f7081f142023ddee661a2980ff92df8a18bf7fe MD5sum: b9da13b2959435f2ec53d8cfda008794 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.9.6-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1262 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_0.9.6-1~nd16.04+1_all.deb Size: 260528 SHA256: 91155f72f981d170e0d745795256269117674b3d67ce653f1fe597899b8b5db3 SHA1: f38596cf08ac090fdf4d5935fbd593112f7650b5 MD5sum: 3b40585b4826dfe207accfd2a49d8365 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: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6807 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.0), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 5.2), libvtk5.10, libvtk5.10-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-6~nd+1+nd16.04+1_amd64.deb Size: 1344678 SHA256: e63635f648e66f1ed1a8ce622bd7510aa5406dab67da1296ac9bf2ebe683dfc7 SHA1: 1ef5299926d994293e44554757b29d508c88482c MD5sum: 7a00919d11c047c4e4e3fd90add99cc8 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2930 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-6~nd+1+nd16.04+1_all.deb Size: 2227648 SHA256: d85f59cee9b040e9680c9817ee0e831d88dca517d2880029a7e9674aead08469 SHA1: 326b580203ce06c723591e460854d73845119293 MD5sum: 9b50fc95856220ca1a5876e4772eff2f Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1766 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.4.0-1~nd16.04+1_all.deb Size: 1669680 SHA256: 4a58773ebb4576609bd4161572178d94854997e74ff3145fb33e74ab97a987ff SHA1: e62edfdb9467c933ae868eb3630a0b9229c77b7e MD5sum: 2446d0cab9c54b99c87e2fee70e5cd85 Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: git-annex-standalone Source: git-annex Version: 6.20170209+gitg16be7b5cc-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 164697 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 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_6.20170209+gitg16be7b5cc-1~ndall+1_amd64.deb Size: 34686092 SHA256: d150cb1ab937d97d3c06ad8d49309a68f779f24c6fc52adaab68f234545c34ce SHA1: 9ac990d8acb26f56e0ca32ecbd9a4eb356549671 MD5sum: a13cb07502c15cec554e384ccd76330f 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: heudiconv Version: 0.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 49 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd+1+nd16.04+1_all.deb Size: 10286 SHA256: b869501f708fea57cfd20fd4325c042865373309c23439a3fc68da089e2821f3 SHA1: 1d3abeac3233e632cf971f22e066c6764272f9a3 MD5sum: 2981f738670efec821e5b4daeb773c86 Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: htcondor Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 12761 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.9~dfsg.1-2~nd16.04+1), perl, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:3.0), libglobus-callout0 (>= 3), libglobus-common0 (>= 16), libglobus-ftp-client2 (>= 7), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 6), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 9), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 11), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 5), libgsoap8, libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.13~alpha1+dfsg), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libltdl7 (>= 2.4.6), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libx11-6, zlib1g (>= 1:1.1.4) Recommends: dmtcp, ecryptfs-utils Suggests: docker, coop-computing-tools Breaks: condor (<< 8.0.5~) Replaces: condor (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: science Filename: pool/main/c/condor/htcondor_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 3637848 SHA256: 5d2141f7c912b73710e0d5e3d1c455b74d22419aaf70f2f61da854dac3abacd3 SHA1: 96c92b2571ffa429d8fab57988a9fca0e47663d1 MD5sum: 604be40c3448e9369705b6760163a6a5 Description: distributed workload management system Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package can set up an appropriate initial configuration at install time for a machine intended either as a member of an existing HTCondor pool or as a "Personal" (single machine) HTCondor pool. Package: htcondor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 31973 Depends: neurodebian-popularity-contest, htcondor (= 8.4.9~dfsg.1-2~nd16.04+1) Breaks: condor-dbg (<< 8.0.5~) Replaces: condor-dbg (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: debug Filename: pool/main/c/condor/htcondor-dbg_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 29808680 SHA256: 0f0e54ab4544c54c47bbf28aba2aa82d58b8852da6b59f824b27582fbe16acea SHA1: 3e8508d8b692a36a4eb3bcf16e951c776e67de73 MD5sum: bc1e3a9b7decb256253955e54347adff Description: distributed workload management system - debugging symbols Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for HTCondor. 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Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of HTCondor add-ons. Package: htcondor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6108 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.9~dfsg.1-2~nd16.04+1_all.deb Size: 1065712 SHA256: e19399294a01d36957e0481ff5a7548b187099d290ec5f968f110a127abb8230 SHA1: 94b6487128920243d3dc94a1943da0a3a3aabe2e MD5sum: 2bca3f07fbb7d1bfcf4f285102560861 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 39 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd+1+nd16.04+1_all.deb Size: 9092 SHA256: 3768f288d0fb7988e227131b3e41a31c00436992b06d2b18e8113e0db08835c0 SHA1: 65c2eeeeb2ec075ec99aecec567a613b9ed2343c MD5sum: 4ff78d0c6fe0960cbf435512258152c0 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 5088 SHA256: 5336188e50c28a623d14ce0305ec77a4efef641cdef4c53c5e52157daf080def SHA1: 3ec074921fdde47d6c380e07226bacd940068f41 MD5sum: 349af0ebe53b5ed02810a3874940a35c Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 419 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1), libboost-program-options1.58.0, libc6 (>= 2.14), libfftw3-single3, libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 121502 SHA256: 78302d6acdcf63e8083196cc0edd2f0a98d7204d8f816753b250d027125383a4 SHA1: 8f50df9dca9e2dbf195d8bb277ae7aea5a6131d7 MD5sum: 3f44b7ab42956260ceb8b5c4571295b5 Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: jasp Version: 0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 6981 Depends: neurodebian-popularity-contest, libarchive13, libboost-filesystem1.58.0, libboost-system1.58.0, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libqt5core5a (>= 5.5.0), libqt5gui5 (>= 5.0.2) | libqt5gui5-gles (>= 5.0.2), libqt5network5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5webkit5 (>= 5.0.2), libqt5widgets5 (>= 5.2.0), libstdc++6 (>= 5.2), libjs-marked, r-base-core, r-cran-afex, r-cran-bayesfactor, r-cran-car, r-cran-effects, r-cran-hypergeo, r-cran-lme4, r-cran-logspline Recommends: r-cran-ggplot2, r-cran-lsmeans, r-cran-plotrix, r-cran-rcpp, r-cran-rinside, r-cran-rjson, r-cran-vcd, r-cran-vcdextra Homepage: https://jasp-stats.org Priority: optional Section: science Filename: pool/main/j/jasp/jasp_0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd16.04+1_amd64.deb Size: 3572548 SHA256: d27d01df2811daa4ed83fd1974a306e13976fbaee65c4886a322cd9ec0597cd3 SHA1: 55aba358233394280dc01f6d88c8d3d9a483f441 MD5sum: 30ff940467a4adddce13f308d2b4ce8b Description: Bayesian statistics made accessible This is a statistics package with a graphical user interface. Its authors consider it "a low fat alternative to SPSS, a delicious alternative to R. Bayesian statistics made accessible." Package: libclassad-dev Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1424 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.9~dfsg.1-2~nd16.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 238644 SHA256: 771069e1091c3edfa6f04bdd913f97be744e18c34d1af50a48ba7a411bdb0ff0 SHA1: 1da0e2ab4efdb67f80b74b7f8733d081d5b5d732 MD5sum: af5b65814028b65fbd361d4a14975967 Description: HTCondor classads expression language - development library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the static library and header files. Package: libclassad7 Source: condor Version: 8.4.9~dfsg.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libpcre3, libstdc++6 (>= 5.2) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.9~dfsg.1-2~nd16.04+1_amd64.deb Size: 190090 SHA256: 4c4d77a15f17d724601cf716e469d7b79eb43297b55f47e0d09f4a496f1e1c76 SHA1: 837d8053eee9ac83e5ce38cae3815b29c4bab1db MD5sum: 05febdb72ac20a805505a3438517db6c Description: HTCondor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libcnrun2 Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 288 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.1.0-1~nd16.04+1_amd64.deb Size: 81750 SHA256: ab2507bba9fc94472bc3556029aa8aded42c2a114eecb3c8482325878aeb7277 SHA1: 044fc9dcef7d9383a30fcc66d6d059f9f276ad9c MD5sum: 51e5e9b1b5d5066069e7b926cc2f7450 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.1.0-1~nd16.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.1.0-1~nd16.04+1_amd64.deb Size: 21456 SHA256: e7717c4aa14384368315e7aef433db18cee3ca84767b6b47c9c44a716134e69a SHA1: 97b6a31218649f77d29f2663ebbf472858797eab MD5sum: 54e7caa3886938d0a2846fbc96a16c85 Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libdrawtk-dev Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 40838 SHA256: f5feeff6952ddeb62dd87daf609d42a85fd1256793c02cff655a28c5c1135527 SHA1: 25c2d35f4e1bcce2638318b5dd68f1779ac56b6c MD5sum: 732f85a397a9c47b3ecf6d33e0237aed Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), libfontconfig1 (>= 2.11.94), libfreeimage3, libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.11) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 22950 SHA256: a4ec511db2ae929dca64942b19dde14e37cc930fbba040f3540fc05c2350fb89 SHA1: ef54e9475cb903a84c59f9205712fe358ad3dbbb MD5sum: a9c93cacded8f138c4be6762e3626d06 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 78044 SHA256: 2c4fb8f4d282ef67ab0f9a567faa2500c17c5c84abfc554680619e038658e98a SHA1: 6fc79165c562d2cabf4a83e7d168a9f8e50d2813 MD5sum: 35283c42813f7ba96f1f23cd7f1b2276 Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Build-Ids: c41828d10c9804b856f1c119e946fc5911d6ba88 Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 13854 SHA256: fce1dcfd5beb5df399ccfb6498202a50a40e0064d01475991f1704a427d2170a SHA1: 02fdb706e684aa870a2a9e72a4c977d1446e85c9 MD5sum: 4381a6b43e5c57caa311110668c0ce39 Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1961 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 157932 SHA256: 2f24afbb9b3936557b75c9f69827bad728cd057e3a34aac31466f47d948cb216 SHA1: accfe2ca334b0b97c931424db47de6e435fae5f7 MD5sum: f81b7692ba25e05413fe88a248cc60a4 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libhdf5-10, libpugixml1v5 (>= 1.4), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 77426 SHA256: 4f6d5e547780343ed4e69c90cc6758d33dd63726c043cfb2f9aedb8e4fac976c SHA1: 534f1d6d4992eadf722ca065ddc80d68a863133e MD5sum: b833217e3b785a0eec90d15a348a51f0 Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 719 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 141804 SHA256: 94288ad8b34fc9e5153c428b991bb393ceb4639f25155e419474d6e7dc5d73ab SHA1: 3ea2e3e1d120cfe2ced2b587f4b52e9a3f6778cf MD5sum: 5f1fe237ba0bfa83ebbf919e677b3488 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 517 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 140886 SHA256: 609bc6cbce66ff9dfb18a6bf219eb48b0843e6668cb05464b95c4a0dec57a9a9 SHA1: b8866c2e347c0a7732ac1aa24453fdb4db5510b5 MD5sum: 75fdd8f2faf079608577afd2e9315aa4 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1274 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 328612 SHA256: c8f1275c4aacd25a2468ce435b019ffd5061444d29abb8288a60ff869e9bc12b SHA1: 8798dafcffac3fd5625874b3109acdcfa435e74d MD5sum: fc61b3041dbf76ab8dc9baff10c7c159 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 277 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74226 SHA256: 23c4508e06435a593df82eb7ce2ed01fb266f8a181cda9ceae84b95f61f82190 SHA1: 38662d93b0426d0f1fcb71df41cd78d4bd59ed8f MD5sum: 3984760e7a13df1cd289e15835d484ab Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1786 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdcm2.6, libstdc++6 (>= 5.2), libvtk5.10, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 445290 SHA256: a6f8e6f152d55de7e111d1725d33fc240ed5d63e543288fc46f23c57114c7dd4 SHA1: 489f5ae091cc6574ac92c344cad671eea9a48741 MD5sum: 2316cc705030caf3896c8e1dd4be9d2c Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 565 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd+1+nd16.04+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 81110 SHA256: 4834857f522b21905239609c60952b1baf8cd1032446672eca6954a03b6776cb SHA1: 4c3664ff72f9f8264fc222c34bc8ec8d8dc2cdb1 MD5sum: 329447cfc41445c3f1f55dc28448c1e5 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.1.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 121 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.1.0-1~nd16.04+1_amd64.deb Size: 38584 SHA256: f31e8033fb730dca87770aaf79f3eac103ca44048f87d8b9f95b80b193a94bc1 SHA1: ff26d2fa039288d579561c3a3a3da1e282475f11 MD5sum: a23b0e78c025f6efbe1327820ad6351d Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.4-2~), libglib2.0-0 (>= 2.41.1), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 68744 SHA256: e6edea5d6279b95758d3d8fcef82495d58ba2d0f79cdb52b50efcfd096a8dc36 SHA1: 37aa16f4e74dbbf39a3591d3d351dc18cf070c7c MD5sum: d8cfe7b9bc985019b8a2a6c250623148 Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd+1+nd16.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 160232 SHA256: f8215de9087fcd45d680f4c99bdbb04b68e9f52eb5bb7a08ecc352e41708753f SHA1: 2923ca8c1a2f24708c36bc3dcd0fab49f8bf8eef MD5sum: fe81542df04c8f3de1ac5730f5b41b56 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Build-Ids: 70b701f30b49c51e532be8647e4165bee8a3bae2 Package: mridefacer Version: 0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: neurodebian-popularity-contest, num-utils, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.2-1~nd16.04+1_all.deb Size: 637352 SHA256: 77d8497006f219516a5d682f4dcbc432cafef37779349576a55adc80daea7509 SHA1: f5e58b7c8b273455ab745b500c367c0747692c56 MD5sum: 11a7610ad8e894687feae0d8b5a6c618 Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd+1+nd16.04+1_amd64.deb Size: 31150 SHA256: 044e5be3e9c3d37d3d9b6d7277091323144dbcaf24a6fa473d2280d9649bf38e SHA1: 9a9e2c6319c86b91d886207a1dfb6609b10dc572 MD5sum: 5fe7ee1c9d627c00f7606510809930cf Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd+1+nd16.04+1_all.deb Size: 16814 SHA256: 22e5cc29f87c08ceb667084f2af3810aaefd1b5fc0828b2f0b0e29cb2a4dc46e SHA1: 90467c75aaba4e464a72ac39884410acc60cfc49 MD5sum: 60f499833563a70a8dc586c029092380 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 91 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.5~nd16.04+1_all.deb Size: 34692 SHA256: a782eeb34e4e6c636517778c4ff979c12e9a230fbcedb23c122e7002655b6451 SHA1: 9315d5405e9604f9b7d20f83240b5d9b4097c9c1 MD5sum: 918d375cf39b03b83676ed89631ea9dd Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: gnupg2 | gnupg, dirmngr Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.5~nd16.04+1_all.deb Size: 10378 SHA256: 43d94888c0bbb446b9f2a2d796441b71067126e5152efa50ae52bf6f0d70b829 SHA1: d8c7b1b10beaf2c54d021faddc31b0db56812875 MD5sum: e0c8f57ee231061ca4f5cbe445371af8 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.5~nd16.04+1_all.deb Size: 116402 SHA256: 338f1476f9040ead6f5c01c581e3a3b8ed847592f4fdd441d358f7a9188bcc79 SHA1: 3f92954e7fcb8dd6435b6a99da191290c314b689 MD5sum: c732398e4e41daae5a5a16883ef5c9d0 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.5~nd16.04+1_all.deb Size: 32768 SHA256: b607a59ddd213529a6b7074dcb368280f9f0f04a19e42dab4cdb5cbc919f0d58 SHA1: a04beb5d390f0d731f625291fec9831e24fe4931 MD5sum: 7de749bf47072b733c9696f9e5110c3e Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.5~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.5~nd16.04+1_all.deb Size: 12380 SHA256: 9206f3a429df0b39a73d49bea5cb2979721e3a00ab38ebe53e0cc08ffe5a0fef SHA1: da69b2b40f9dccd606151011bdf9680ac1fa9a8e MD5sum: c7ff04f1195fe0fe3d15bc072dce04f8 Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.5.25+ds-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3209 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.25+ds-1~nd16.04+1_all.deb Size: 656590 SHA256: 2ea6f2c1189058ecb138f1669f4bc9ed39ec29fcb4f38c42d52e2c32f338743b SHA1: c0ff19a0d363298d1307a3f36966f4546875b503 MD5sum: 8cafbd514d3422fc8f8eda9c8fbb5479 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4715 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), 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, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1), psychtoolbox-3-lib (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1_amd64.deb Size: 923202 SHA256: a5289da68895df36bc4d2c8943eaac400b6123ce40aad829b7db15631acc75c4 SHA1: 275cad6e74e39a0bc38fb746f8e4d4487dd346f8 MD5sum: 8c45f2bda5390b8209f626a2162b0661 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: openstack-pkg-tools Version: 52~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, autopkgtest, libxml-xpath-perl, madison-lite, pristine-tar Priority: extra Section: devel Filename: pool/main/o/openstack-pkg-tools/openstack-pkg-tools_52~nd16.04+1_all.deb Size: 52268 SHA256: ce9a5f309792b3a87d6f8c00259b993da4eae392c3cd59c2d63acb6640964cc5 SHA1: 9b2978d36e9fe7878444813081916d17fc5178d1 MD5sum: 421e6c2753576c0ad60b3b768f92362c Description: Tools and scripts for building Openstack packages in Debian This package contains some useful shell scripts and helpers for building the Openstack packages in Debian, including: . * shared code for maintainer scripts (.config, .postinst, ...). * init script templates to automatically generate init scripts for sysv-rc, systemd and upstart. * tools to build backports using sbuild and/or Jenkins based on gbp workflow. * utility to maintain git packaging (to be included in a debian/rules). . Even if this package is maintained in order to build OpenStack packages, it is of a general purpose, and it can be used for building any package. Package: p7zip Version: 16.02+dfsg-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 853 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Suggests: p7zip-full Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip_16.02+dfsg-1~nd16.04+1_amd64.deb Size: 339260 SHA256: afc271ce5ccbdfd2c37da631535b7fddef7df63d3dfbd64bc0a1895f2f868d9c SHA1: f42d0a4f91e4e3e6cce27b2e8c4ea8ad50337d62 MD5sum: b7ad4745b81248a4d91da2db8b3f2355 Description: 7zr file archiver with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip provides: - /usr/bin/7zr a standalone minimal version of the 7-zip tool that only handles 7z, LZMA and XZ archives. 7z compression is 30-50% better than ZIP compression. - /usr/bin/p7zip a gzip-like wrapper around 7zr. . p7zip can be used with popular compression interfaces (such as File Roller or Nautilus). . Another package, p7zip-full, provides 7z and 7za which support more compression formats. Package: p7zip-full Source: p7zip Version: 16.02+dfsg-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4235 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd16.04+1), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Suggests: p7zip-rar Breaks: p7zip (<< 15.09+dfsg-3~) Replaces: p7zip (<< 15.09+dfsg-3~) Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip-full_16.02+dfsg-1~nd16.04+1_amd64.deb Size: 1166002 SHA256: c3b43506d10c326e80eb194eba855922dbdf8f16e5a5b368b0283a0d5833da4a SHA1: e3dccde72ac6dde99a16779b41d426caf363ca24 MD5sum: c6a3222617b4e36bb983a6ec1ed235b7 Description: 7z and 7za file archivers with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip-full provides utilities to pack and unpack 7z archives within a shell or using a GUI (such as Ark, File Roller or Nautilus). . Installing p7zip-full allows File Roller to use the very efficient 7z compression format for packing and unpacking files and directories. Additionally, it provides the 7z and 7za commands. . List of supported formats: - Packing / unpacking: 7z, ZIP, GZIP, BZIP2, XZ and TAR - Unpacking only: APM, ARJ, CAB, CHM, CPIO, CramFS, DEB, DMG, FAT, HFS, ISO, LZH, LZMA, LZMA2, MBR, MSI, MSLZ, NSIS, NTFS, RAR (only if non-free p7zip-rar package is installed), RPM, SquashFS, UDF, VHD, WIM, XAR and Z. . The dependent package, p7zip, provides 7zr, a light version of 7za, and p7zip, a gzip-like wrapper around 7zr. Package: 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: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253898 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_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1_all.deb Size: 24285916 SHA256: c4dce0dcafdb0049aa7a5529382e4c93aca11d894b5dc0f82f656ecabac6ff05 SHA1: b304fd795258e4c5a4091d89dd110b12e8dd38b6 MD5sum: 626d651482a1819a821ed573fab0b98b 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: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3874 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1_amd64.deb Size: 741462 SHA256: 7794142ff925d182a4b469a922e82a689d467af0741a3198126466cb04d7cb5d SHA1: 0a9df9c02f2245c4b75fb0715e33dc59ded8434b MD5sum: e8c7383289c6b3c90e1e8ca9af60a02b 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: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 190 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_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd16.04+1_amd64.deb Size: 73410 SHA256: 08e299a857922ca845c74e6461158dce6e7c8ac3418f26a10d25b1949bcbcf96 SHA1: 6393f66012005d26633b64404c40d12359442f82 MD5sum: c462876ad5ce02fa280768e0f76788ef 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-datalad Source: datalad Version: 0.4.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3123 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), 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-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_0.4.1-1~nd16.04+1_all.deb Size: 608562 SHA256: 767e68387def0c9c175302900154aff5a1df7763b973b81d0947a138bfe6a3e0 SHA1: 763fb8027a698b288606bf82bb88f2ecc6e6d3b2 MD5sum: 98c7b14e09ed91646e23ea6f6bfafb4a 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-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-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: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1623 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_2.1.0-1~nd16.04+1_all.deb Size: 299428 SHA256: 87c878d93878bffbee6004d062170e8e55e9dd408207fef01fcf2cb8b1fb23a2 SHA1: 79b1f0ae35a2d0ee510df9d198d92a2e0b1501ee MD5sum: f8ebfee837d0fac3d3b03865b6586a1a 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: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 977 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_2.1.0-1~nd16.04+1_all.deb Size: 125774 SHA256: 6197b2b82659c4cbd60fcf8a0f55bcd4fa877b63fff42184eb01549c2132d52f SHA1: 9416fb585fd6ba47426f92c82b57bd2e2de1a573 MD5sum: 4124c297d4fff7a646de3962e792e84c Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-gitdb Version: 2.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 215 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_2.0.0-1~nd16.04+1_amd64.deb Size: 46170 SHA256: a26f68c0bdbfd532a7c9f2032cfeb7d2a3a4cc8a712741cae8d39469dcbe4b0c SHA1: c1a67e953ec0e887e67e87bbfc53c21bf5700b65 MD5sum: a81cf4e5e71fb8cc98d37ed7be460b84 Description: pure-Python git object database (Python 2) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 2. Package: python-github Source: pygithub Version: 1.26.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 632 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Conflicts: python-pygithub Replaces: python-pygithub Provides: python-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python-github_1.26.0-1~nd16.04+1_all.deb Size: 44830 SHA256: 066f7113c45087342009432eda00640d0a7fe268e6ae8d8df31df62f44adc80f SHA1: f70b5c50fa136dd5e6513f3c37712b8c33aa70eb MD5sum: 1d9d0c0285b697913307a360b531db43 Description: Access to full Github API v3 from Python2 This is a Python2 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python-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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237662 SHA256: f27225dae5ede49f6db3b33d738901167019d32da2e264225201a799191992be SHA1: a0e2612212fc60fe89fa6e89a18324cf58c5b322 MD5sum: 859d71b6198aaf4f79eb8efd737d75bf Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-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-mvpa2 Source: pymvpa2 Version: 2.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8535 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.6.0-1~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 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_2.6.0-1~nd16.04+1_all.deb Size: 5096012 SHA256: e9ae674abfd1f5928fa03a2c886a6260fed5a595f770c3e30161bd8e017bab9d SHA1: ca01cfecb96da2a10e093cca483ea770aa921e80 MD5sum: fffd32508252d0d3c7d244461fbe5bee 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: 2.6.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36117 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_2.6.0-1~nd16.04+1_all.deb Size: 4639730 SHA256: 083163aec79f87f85e68030d79f538f8467cd1417268a67e8f7f5bf1392436e3 SHA1: 291eaa2435bca16ae6a1b63840a9ee63104e0702 MD5sum: eea2f554f0ead75807f559354e4c6b1a 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: 2.6.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 142 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.6.0-1~nd16.04+1_amd64.deb Size: 50818 SHA256: 172c7eb782882099ee439ab359afb4728e674b1f4826202e2caf67118727a53c SHA1: 6c1958096e5e8d0202c9a97d3ce013c799808c4f MD5sum: effc302ec4374a8f6109537c3d17972e 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: 0.4.0+git26-gf8d3149-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3277 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.0+git26-gf8d3149-2~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_0.4.0+git26-gf8d3149-2~nd16.04+1_all.deb Size: 738188 SHA256: 5055e9ccf0463f9edc78aec5246bd68ef7bf8395b02f31df1726997a3df0a320 SHA1: 91ed2b61cb376ac857927a25816ebe01e92b37a6 MD5sum: b9c693770043bde500570a9e4ea5f280 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: 0.4.0+git26-gf8d3149-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10710 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_0.4.0+git26-gf8d3149-2~nd16.04+1_all.deb Size: 2649996 SHA256: 7996ac0e44000d3b24df81a48a9daf9e69197da02d5086d15501641f3b6c6965 SHA1: cb1976b8dd55b0763b9decb0cd7f2f3237b6a9ef MD5sum: d5e5ce94783fd8a0cda52318f12019bc 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: 0.4.0+git26-gf8d3149-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2613 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.4.0+git26-gf8d3149-2~nd16.04+1_amd64.deb Size: 621176 SHA256: 92c95901cc6b5cf92c9ca2d9bcba85c912170bd9908e745ad2befc7f2aa1d3c8 SHA1: 1383ef2fa51f7adc364566d20bb1d37882e432af MD5sum: 646e525711c4fd048b1b636f1a3adae6 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: 0.4.0+git26-gf8d3149-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3755 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.0+git26-gf8d3149-2~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_0.4.0+git26-gf8d3149-2~nd16.04+1_amd64.deb Size: 637622 SHA256: 7a4e8ba3a02ac851880654068c6dad862a758469d51754f5f8c0daf2fbc110f7 SHA1: 155fac3f0dfbe7457bf70cb1f5a88303fa7e117a MD5sum: 6b4e0254f11cc52ad3b50bcf58d7c360 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: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 421 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.6.1-2~nd16.04+1_amd64.deb Size: 143674 SHA256: 64a5747760572f3b4d73a42cbfbc1245f31d29ba88b2d3c28ef1d07465b040f2 SHA1: e9d33759be276e997302d0968c7ced7816e2cc80 MD5sum: 8ce6ef2f2a41dee7a1ad05ca0e6d0b78 Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 287 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-numexpr (= 2.6.1-2~nd16.04+1), python-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.6.1-2~nd16.04+1_amd64.deb Size: 111270 SHA256: 3feec45c05be47652576dfb3531e0d67c765ab9016f5bebbd1ad5edb6eeb9a9e SHA1: 10ddde40dadb0baaf98e561a4540468345ad6416 MD5sum: 15cbbce6d196b5963b69856d03ce9834 Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1323 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_2.3.0-2~nd16.04+1_all.deb Size: 199220 SHA256: b70affd1599e94a0a0930fb4497a75e7466ed0e7b4f1e4ad1be006c6327e75b2 SHA1: bc62307b04fb297c5e98a1e2a55ff2339524aae8 MD5sum: 90c38c6c2346aab02e8a77c47243a274 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25229 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.19.2-1~nd16.04+1), python-pkg-resources, python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.19.2-1~nd16.04+1_all.deb Size: 2601224 SHA256: 4978eb7a1162131513496cc527a75abccfaa6a78134cd36953851332d0f5d1d4 SHA1: 3dddfafe1a3ed0e51a58b99db89de40c947f1770 MD5sum: 1251275238a0c73645433537108e17e9 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58841 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.19.2-1~nd16.04+1_all.deb Size: 10193446 SHA256: 2e91ca3328337bba23af7932f10392add466bf3e8af30ce3caee88ce04f92531 SHA1: 2e966fb7962fc6a07395fd99b66df827a5af6fb7 MD5sum: 663270f93696187938afede7b3ce6294 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7608 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.19.2-1~nd16.04+1_amd64.deb Size: 1831276 SHA256: 941e71c9063c9fff8ff58bbd8d00fd25e742ce447ea68f3ea3c1553695eb5ae5 SHA1: b27e05cd45916c718e52001d8c5a02c251996535 MD5sum: 700a76df4bf1a0eb3a800313a5ce4fac Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 779 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-six, python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.4.1+git34-ga5b54c2-1~nd16.04+1_all.deb Size: 169084 SHA256: 67873a5e82cf0ed24e7af34d09203a7babb95f840b596f567764d80ceeee4566 SHA1: 97fde9a8651212cc78294fa626feec237a1b7bd0 MD5sum: d73aee7388dd52e26dfab42afe9643b2 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1408 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.4.1+git34-ga5b54c2-1~nd16.04+1_all.deb Size: 362406 SHA256: b16c06da21efe26063c34e3f330be8b18cbe0bca209f57812cb44fad621ef785 SHA1: 6b4cdff1e078b2ea9be829c4d92ee1d48d88e3a6 MD5sum: 1c7ecc644ad0a486f3ba5add4590b825 Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 441 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python-pkg-resources_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 141288 SHA256: b037bfbbddbe376e51050e582f7c81917a5466891d6d3629c27fb1217741fed6 SHA1: 2d6583f201e404099c1126acbd8bf172fe84a8d6 MD5sum: 23873c2cfca07961c552409c3a596e31 Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python-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: 2.0.2-1~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_2.0.2-1~nd16.04+1_all.deb Size: 20240 SHA256: 2f2cbd16ebdf9303b3f63c0dabc1d0cb2eae3d15bb106c9cf7909b260c9560b4 SHA1: fd723ed2ffdf2a961a70954a6dbdf77c3cdea09c MD5sum: 7d94224fbe37b88a456bc0034ce397b2 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: 2.0.2-1~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_2.0.2-1~nd16.04+1_all.deb Size: 46688 SHA256: 084d0a9e4882149dbbef0d18600ebc885f8cc725aa2aa72bca43a8d3ce414f76 SHA1: 1eed1e9afc09ba215f373b5a58ca248d95693529 MD5sum: 0b6ff044fc8b77c4f2fb1e7b09f0bb6f Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1460 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libode4, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 5.2) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_amd64.deb Size: 286430 SHA256: ff44ddb8f59b4fdd857e6eadaed6e9313e56685f2a71adc722094105ce169555 SHA1: 5e364e5bb62ff1ddafbbe127422709cf7302e5a5 MD5sum: 48837816129adc541de9665f48eb9d20 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 822 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_all.deb Size: 819350 SHA256: 2e955547503f670039815376e4ac8860679cb376009788bc07c133ad3cf0dc02 SHA1: 349b67ae265dd0cbb576d6f2cc991cb1b9582a46 MD5sum: d7b4b656eb6f9dacf1c258cfa9df35bb Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd16.04+1_amd64.deb Size: 74330 SHA256: f23ccdb46ba3c5262bec3cfa83765867c4a1735f741dd82e7cfc8040ad0d3ae4 SHA1: 5be82c04a410f37c530c18365a3afdbbd8c2d800 MD5sum: e0de083f7878b9e23237b2bab8f40f75 Description: Python interface to the Graphviz graph layout and visualization package Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. Package: python-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 307 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd16.04+1), python-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd16.04+1_amd64.deb Size: 113194 SHA256: 050382703d332347dcb069f765ee3d6af1e3e1ad7b4c5c2d2e057286cd81712e SHA1: 80c0f2eaffd808da75b230d227a19709b328ce97 MD5sum: d80abb8bb5687aee7fc0b2f9ba725fe7 Description: Python interface to the Graphviz graph layout and visualization package (debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python-pygraphviz. Build-Ids: 4b0c48008805be4ca40026fea6b599aa2e737e75 Package: python-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 312 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pygraphviz.github.io/ Priority: optional Section: doc Filename: pool/main/p/python-pygraphviz/python-pygraphviz-doc_1.3.1-1~nd16.04+1_all.deb Size: 67408 SHA256: c1224a2179507867f56f20c63434a263faa02bc206dc14e3aed3e1f7acd7076e SHA1: 2d1f19d174498015d80ca43a7a1a2b805a6532e7 MD5sum: 44c786b37a5b2e55cd781dd78c953f93 Description: Python interface to the Graphviz graph layout and visualization package (doc) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains documentation for python-pygraphviz. Package: python-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-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: 0.18.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 79 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_0.18.1-1~nd16.04+1_all.deb Size: 70642 SHA256: 8c5fe804659ee8d226716764621cdc23c0356e3f47acba70f059d9c55a58455b SHA1: cc5ab968328a4b90b836ff72901f5df87b3ffb23 MD5sum: 668c24b8dc0e62f1835ff2bfcdecca14 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: 0.18.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6609 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.18.1-1~nd16.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, 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_0.18.1-1~nd16.04+1_all.deb Size: 1391834 SHA256: fa253e81475d08caf5d3f81a39f341f8f6f608747553f4e63b5694172593be77 SHA1: 89b4a53bb27cd06708c72f279a3a0dd496519b65 MD5sum: 93ffde56abae9122367c7060598890a8 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: 0.18.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29461 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_0.18.1-1~nd16.04+1_all.deb Size: 4757876 SHA256: 9c46fd81c1e02e462db9e1613156dd59dc78d7948dc29c0c9a10e1ba49b9f3e7 SHA1: 4247f8eac4fb113c5cef59cae08fb45eb6d4f46f MD5sum: 44db0d8eaed0e39c514917728b7373f5 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: 0.18.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6087 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.18.1-1~nd16.04+1_amd64.deb Size: 1315280 SHA256: c83c5bec1c6e51da15db70fc54b17e1f52049f81c6dc15c81256172470116cc9 SHA1: b1cf37899706f43c141d5bd356cbd6c023655ae4 MD5sum: dbf3066eadcf88dfe19da1accd363a27 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-statsmodels Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15861 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-statsmodels-lib (>= 0.8.0~rc1+git43-g1ac3f11-1~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~rc1+git43-g1ac3f11-1~nd16.04+1_all.deb Size: 3333028 SHA256: 6628c6fa2d79a8f67e81522215303ba26e8d4a41cf5d9bf476694c3cd63a0b4c SHA1: aa25a52facf4acb543035bf24745bc30382593db MD5sum: ad05cc8bbd25dba38d302387719a8034 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~rc1+git43-g1ac3f11-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53299 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~rc1+git43-g1ac3f11-1~nd16.04+1_all.deb Size: 8399220 SHA256: d23868b7318a0fde44661eb36fbd892d2efc90a2404c26c8d5fcb9652eb5d8bd SHA1: 911b87e251cd8908061c97a3549220fe9ff6a4a1 MD5sum: 8c65e5a7792e9c66f054118bfff8c5d9 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~rc1+git43-g1ac3f11-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1781 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.8.0~rc1+git43-g1ac3f11-1~nd16.04+1_amd64.deb Size: 245504 SHA256: 8ea6454b88c59dd8a5084fc6094903f43d76391ca27f52f1203261c814be3446 SHA1: bbbc003c0be54e4653a436a457942f2be9e9d702 MD5sum: 68b5f75538e4d157e9e77c441f12015a 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: amd64 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 (>= 2.14), 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_amd64.deb Size: 493484 SHA256: 2f4b6fb250faffe39ab034e88b054dcb56e28fc82d7365975528cd270b68bcbf SHA1: 8753b3b883ee87f23b665869e9b1b486de7eb3b1 MD5sum: 676497441aceef2afb2d89af6d9dd1e5 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.7-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 197 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nibabel, python-numpy, python-scipy, python-pil | python-imaging, mayavi2, python-argparse Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.7-1~nd16.04+1_all.deb Size: 42524 SHA256: 167ae695f1ade8edcad4c6bc0056578813ffa33199fa3b6264f03db670b9b7ee SHA1: ae13b9b963c87bf893e68854855cdfc42fe958a5 MD5sum: ccfb36d4a0a69845263bf2dfc3565700 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-tqdm Source: tqdm Version: 4.11.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 179 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.11.2-1~nd16.04+1_all.deb Size: 49804 SHA256: ab5898263779a7cccbfa96e88d16e55225e7dc003c7b9f3f8b71709b00d371ff SHA1: 82cee46a654514928793380200cd0a810d72ae11 MD5sum: d46b0fb89d9409486b5b0c0772fbd164 Description: fast, extensible progress bar for Python 2 tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 2 version of tqdm . Package: python-urllib3 Version: 1.12-1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-six Recommends: ca-certificates, python-ndg-httpsclient, python-openssl, python-pyasn1 Suggests: python-ntlm Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3_1.12-1~bpo8+1~nd16.04+1_all.deb Size: 65338 SHA256: d15178f468f84a7b89caaf81b71c96897d5ae8242e664001531739624267e905 SHA1: 5d061603c38174218587941f515e58bd0bf49425 MD5sum: 5fb1f4092ef4fb6654af2107cd9b7db1 Description: HTTP library with thread-safe connection pooling for Python urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. Package: python-urllib3-whl Source: python-urllib3 Version: 1.12-1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, python-six-whl Recommends: ca-certificates Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3-whl_1.12-1~bpo8+1~nd16.04+1_all.deb Size: 92846 SHA256: 9719b066fa4881282495c799c2b8471ea1353e3c75437987272164e2b133d64a SHA1: 0caa3703bdc22530c3cb78bf74dc532f30e9cb7f MD5sum: fdcf56c01fcf742292840cc0c544b432 Description: HTTP library with thread-safe connection pooling urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. . This package contains the universal wheel. Package: python-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six (>= 1.5), python-wrapt, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43580 SHA256: d13dfc1adc96024f35330d4c72825e3f09b9767177330c804cc3575079e11498 SHA1: 38af2662eef11399c694c53bdca1e4159e830bc8 MD5sum: 212bc7388c199867c3f9d80be6d829c2 Description: record and replay HTML interactions (Python library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 2. Package: python-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 494 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 90490 SHA256: 72d4bc52366ba201df84aac1235c23b8b381f81113d7b854d673b15f17923672 SHA1: 87f9509347df7df8a1d83a6d18c1fb605416e4d2 MD5sum: 913cdb7893a354206416631b4a424e89 Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: 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-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-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: 2.1.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1620 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_2.1.0-1~nd16.04+1_all.deb Size: 299448 SHA256: 70e9ab07b486d1422922ccf43adc3c38e99eb9b31df3c9ff9b6abd98d9b1b196 SHA1: 5b86dbecb44eac7d3aff42145dafc338d42bf318 MD5sum: f38e13db59c51c900b1ff653e60da80f 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-gitdb Source: python-gitdb Version: 2.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 214 Depends: neurodebian-popularity-contest, python-smmap, python3-smmap, python3:any (>= 3.3.2-2~) Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python3-gitdb_2.0.0-1~nd16.04+1_amd64.deb Size: 46230 SHA256: 63ef8dd35fd3a685aa82eea798addbce67bcb0e0a865d8d7247236c22714bd5d SHA1: fd5b1a2bd79d5e2a5f406ea6c828369504866220 MD5sum: 3725dfaaee27fd67c5fbf3199f24baf3 Description: pure-Python git object database (Python 3) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 3. Package: python3-github Source: pygithub Version: 1.26.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 629 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Conflicts: python3-pygithub Replaces: python3-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python3-github_1.26.0-1~nd16.04+1_all.deb Size: 44896 SHA256: 9b0cb31263e2e0a368feb76d999e38d3cd3c4d12ab130cba07fac8c0b1357c24 SHA1: fadd6f4a75021a1d05dd975b06694c04750a2350 MD5sum: 430f2aca1c40484a5d7b20b85aa09726 Description: Access the full Github API v3 from Python3 This is a Python3 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python3-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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1315 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy, python3-pbr, libc6 (>= 2.14) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237590 SHA256: 3cbb50f7352930b20c44343c5db4893215525ba2e4369e11d24f526eb002d553 SHA1: 9de3bab95047a3e29eb367af3fbabff08a63e25d MD5sum: 0c9dbd6e2e513ff2b5045bc672c1783f Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-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: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 408 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.6.1-2~nd16.04+1_amd64.deb Size: 137796 SHA256: 05abaf015c54b12713298a2ca1af86476da782dc5485869e0ef03ebc6be9c584 SHA1: d6d07acfceb9f6d52baf1ae74e1d65176eccf320 MD5sum: 5a011eb038677a0c502e1488987a7fbb Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 291 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.6.1-2~nd16.04+1), python3-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.6.1-2~nd16.04+1_amd64.deb Size: 111626 SHA256: 1c7f0e9b22190369bf65b3df0a0fdc3c7608bfd53d797e8bcd296df6f03cd7d5 SHA1: 8961c12f5920ae9199645ca2eba676fa33cd2bf2 MD5sum: 690245e84333a1a6e293061b45074f33 Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1319 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_2.3.0-2~nd16.04+1_all.deb Size: 198366 SHA256: fdbf672443fd6a1fef2972081a62e73df077d6df43362d6bb9c4103d82bb2bff SHA1: 7da58edb8f3231d5a648b5ea1f8d82c778ec35b9 MD5sum: bd9936151cca80596c5a727f5cf04c02 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25227 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.19.2-1~nd16.04+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.19.2-1~nd16.04+1_all.deb Size: 2601416 SHA256: c84fc9fef43a496a971e61bd46680659228d9e9fd4ee29bc617455a24a407160 SHA1: f3b03bfd5354423bd3fb5be38eb35eb2bf79beb8 MD5sum: b0ae30aef1d47b5d32f5502c8b1eda78 Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.19.2-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7377 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.19.2-1~nd16.04+1_amd64.deb Size: 1807152 SHA256: 1fe61075b32c980373b59d4431b5373cb9f9aa955132cbef8fc08e741d5ff290 SHA1: e2766d864e1ba03bc5beb3e7ad6f3a5e62f1bc2b MD5sum: 1ba6ec7991907b564de4956466236be6 Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 778 Depends: neurodebian-popularity-contest, python3-numpy, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1+git34-ga5b54c2-1~nd16.04+1_all.deb Size: 169194 SHA256: f1918e6deeb48daa4b33e7556fe6e78a2d6557e5a72bfd12d9e45bc30a43adc0 SHA1: 411f03d31699f24bc3c71ea7f775c489837352fe MD5sum: 0866f30d9d2d1d10fcbb82945158218e Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python3-pkg-resources_20.10.1-1.1~bpo8+1~nd16.04+1_all.deb Size: 111924 SHA256: 37436362884361cbe450a55d71d3b5e0c137945715f545e7b7be7c9b84e64d51 SHA1: 3a081bf0d880a0241694983fee33109f2107d602 MD5sum: 8f25c359bdd869855af0c2693dfd8e1c Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python3-prov Source: python-prov Version: 1.4.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1235 Depends: neurodebian-popularity-contest, python3-dateutil, python3-lxml, python3-networkx, python3-six (>= 1.9.0), python3:any (>= 3.3.2-2~) Suggests: python-prov-doc, python3-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python3-prov_1.4.0-1~nd16.04+1_all.deb Size: 72570 SHA256: 6e2836dd7da34d0a68513ac450fb3cd6a13be3aa79e9f284b3ccd16596d97ed4 SHA1: 77cd01fd8a21b7f58be5e975f7f32f36742d4dd9 MD5sum: ca78f5a4c2b8d6093898c99c5a2e2043 Description: W3C Provenance Data Model (Python 3) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 3. Package: python3-py Source: python-py Version: 1.4.31-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.31-2~nd16.04+1_all.deb Size: 82310 SHA256: 744838b493212a784bb0d94d5dd5c54347475dd987b8d3f0d32f4c029881bf40 SHA1: bf95bda1b6fa38d0262fba6fab890efb332d22a0 MD5sum: 010f582c231efd751bfc1261da1aae6f Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pydotplus Source: python-pydotplus Version: 2.0.2-1~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_2.0.2-1~nd16.04+1_all.deb Size: 20322 SHA256: b19df8771f49c2b313d2a1acb1ecd2771576485c6ad9156596b50714764bdfef SHA1: 6410b7286d956011e3f522ce1db8d460294c4743 MD5sum: bacc9756268bd576896ea738f9e31359 Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-pygraphviz Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd16.04+1_amd64.deb Size: 74230 SHA256: 7b9d089e59246402abb2ea7d3f53d3980c5690c5e62bf36bbca368b70adeedc5 SHA1: bac254b4ed0d37a7522262db2e705e03d1b6683c MD5sum: d1dec895c46a6dadad3ef072ea0a2447 Description: Python interface to the Graphviz graph layout and visualization package (Python 3) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the Python 3 version of python-pygraphviz. Package: python3-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 309 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd16.04+1), python3-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd16.04+1_amd64.deb Size: 112902 SHA256: 3f39d007137d726cea8160deb887a136fafbf8a6bd93f3cc4eccbea69d10fe57 SHA1: e352618f5109a2cba7ac1360b5bce48744ee66b1 MD5sum: 3f8f68ff662419ea83d1b913b44b2c5b Description: Python interface to the Graphviz graph layout and visualization package (py3k debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python3-pygraphviz. Build-Ids: ce5403c869e1f24666b0cfa342ad462fcbc0bdcc Package: python3-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-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: 0.18.1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6608 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.18.1-1~nd16.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, 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_0.18.1-1~nd16.04+1_all.deb Size: 1391702 SHA256: f88e4aada943699c0d117b4d29e27612ca0c9de16896e5081d17abd69964191a SHA1: 6672ab0c871d0f3f45748c1027a5e80c2f5540f6 MD5sum: 8cc01abefc61543e9a8542ffe9399d44 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: 0.18.1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5660 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.18.1-1~nd16.04+1_amd64.deb Size: 1252368 SHA256: 34a2fe89a34847bf33b47f4393974933a4191cb4d51746fd3160170c153788fc SHA1: de8aad11ccf594c2b3fc70f327d6d7a72d763586 MD5sum: b4664f25fe62810de547097a508b8125 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-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: remake Version: 4.1+dbg1.1+dfsg-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 317 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_amd64.deb Size: 152010 SHA256: d3d10cdb44447752207c07a7078fe9ac3ce0881ea26ce295821aa81cf49636e6 SHA1: 9806270ecb964b12d7433a2633130a5f2b4fe4dd MD5sum: 321550f412d988377654feb48e1091e8 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: 2.2-2~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 967 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_2.2-2~nd16.04+1_amd64.deb Size: 138224 SHA256: 5b0ca7b0e8b65f1439f4948f5205408d6ff68fbe30907c5dd2d4ea76069a696d SHA1: e9c0bc052b17abb43a9f1c300c8d0e58092fdf01 MD5sum: b50d71b8862ffa60c92f57987dd6d7e6 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: solar-eclipse Version: 8.1.1+git0-g8f32b4b-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 13280 Depends: neurodebian-popularity-contest, libc6 (>= 2.23), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), libnifti2, libstdc++6 (>= 5.2), libtcl8.5 (>= 8.5.0), tcl8.5 Recommends: python Homepage: http://solar-eclipse-genetics.org/ Priority: optional Section: science Filename: pool/main/s/solar-eclipse/solar-eclipse_8.1.1+git0-g8f32b4b-1~nd16.04+1_amd64.deb Size: 1723816 SHA256: 9c7c4e2ced1b79824da0d873fe3f325331e59dcf700041354488e3e0570848e5 SHA1: bbd57715f0214ee32d0030f37e5f7ab58f05c9f9 MD5sum: 6aa156c8a83655a7e21f2347ab08599f Description: genetic variance components analysis software SOLAR-Eclipse is an extensive, flexible software package for genetic variance components analysis, including linkage analysis, quantitative genetic analysis, SNP association analysis (QTN and QTLD), and covariate screening. Operations are included for calculation of marker-specific or multipoint identity-by-descent (IBD) matrices in pedigrees of arbitrary size and complexity, and for linkage analysis of multiple quantitative traits and/or discrete traits which may involve multiple loci (oligogenic analysis), dominance effects, household effects, and interactions. Additional features include functionality for mega and meta-genetic analyses where data from diverse cohorts can be pooled to improve statistical significance. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19186 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 9781970 SHA256: 30cac74b9ad9db32f093eece5bae13d28ce4e1222878358f3afc6e6a67b55b67 SHA1: 4899f3ba6a1ff156b67ed1b324ae4a83ffbbab9e MD5sum: 093fd447d8b43ebafc21585625545b37 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73019 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 45497774 SHA256: bde3c93b9c1168ff6fa5b3269782006cf5613ba3f2b7b49abd5249d07600335b SHA1: af6dce85c4ee9079c720d544dfacfe2fc2cffa67 MD5sum: 494ca73671489f3feaf525e4295caff3 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9251 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 8934936 SHA256: 7f6f08608f31115b8e51d149f8560a2cfe399bd44562ff34bf2aeb24a9632bc9 SHA1: 31e802efc7a2237d47eb5a13d1d6f6a6f9ed7324 MD5sum: c96ec4b1e942cf1f8f8eb55b327d7c40 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: stimfit Version: 0.15.4-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3281 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 930402 SHA256: e388ee246ba37fb947808779bd3439a1e11359e414c62b15f8000e7f65453a66 SHA1: 44a7048def79950bf41d54cdb3aa81a9b5c75ba1 MD5sum: 8b3b93d3cfbfc44001c91868f0ae4605 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 30814 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_amd64.deb Size: 6642936 SHA256: b7395cc61459b90df2104c02fdc997ae5cf08f8dcf799372040cd6c6320130c4 SHA1: cbe16c397449fba7a9827c86628b20b343caa589 MD5sum: 377641451cab5f2221d861037e6c7c65 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: utopia-documents Version: 3.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18049 Depends: neurodebian-popularity-contest, libboost-python1.58.0, libboost-system1.58.0, libboost-thread1.58.0, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libpcre3, libpcrecpp0v5 (>= 7.7), libpoppler58 (>= 0.41.0), libpython2.7 (>= 2.7), libqt5core5a (>= 5.5.0), libqt5gui5 (>= 5.0.2) | libqt5gui5-gles (>= 5.0.2), libqt5network5 (>= 5.4.0), libqt5opengl5 (>= 5.0.2) | libqt5opengl5-gles (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5script5 (>= 5.0.2), libqt5svg5 (>= 5.0.2), libqt5webkit5 (>= 5.2.0), libqt5widgets5 (>= 5.2.0), libqt5xml5 (>= 5.0.2), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), python (<< 2.8), python (>= 2.7~), python2.7, python:any (>= 2.7.5-5~), python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_3.0.0-1~nd16.04+1_amd64.deb Size: 5601548 SHA256: a26e1c61ef7e56757f7a2d02495ab7318c7a08b43751f16001894d8e8210b91e SHA1: 25df3cac5572292ac41187fbedcdffdbfc158822 MD5sum: e9a1fd3b942a690be99980bfd2d5a613 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: 3.0.0-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48249 Depends: neurodebian-popularity-contest, utopia-documents (= 3.0.0-1~nd16.04+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_3.0.0-1~nd16.04+1_amd64.deb Size: 47176806 SHA256: 0584a70bf0c49a81c585455dc22375388263f0fb2b38a720411b78130fdf2e7b SHA1: 48a23ea8e567b3d8241d3989c8731eb02b23ace6 MD5sum: a7ecc986699c118d5e06aa60d06d4feb 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: 0be23e35f998f0adb268c59dd699925201bce709 0c57e58646b394c0e4982873798c9179146c953d 11050018e8f3235bf268942a07c7c9f1aca86e3b 1662e12d4a4a032a5d83216c2e5b6259401be863 1736af73539cc6f87c5582e2f0bdcfa3ce823a43 19fcce75d1d6fa80d4350002f24bb7d6d2316fa2 1ff1566572032b6e51ec08c2f990ccd913a843fc 27cc66eec8ba49504b04a3a90348d67f418548ca 2a4dafa078256f4ad0d7b57a950fb30d7de690fc 2ce838084892b6b5e901124dbe164698ca296888 34d105866804edfec2009b95d2957e616916884b 431019018be0d7f350f6c2268f59c034dca3b1de 44494c76fa03185f78ca3e5f04055269f67a47cb 46517bf724bcd540e85e4a0c22eb609b7bedfb08 4795690575058e0113160b143c2fd86c4b8b7ba7 4ad472a0b873eb97044743e82285a8ddfd5d523c 609f9ed1d731e790220f931d083470e2ed8e9055 6218aaffef90b08bc614e53399d30d9918881775 6ed2dec2548550e24351c35f7afa46ef8cbcfd4a 6ed639b2abc8b08f9dca8d47aff529637d30be76 701079059ef8158557ed8052ea9f6e12792cf336 7aa52f841fefd2311157bdffaa449e700124b586 8249a34d8427fce6edc9f77301ac7b4858ca2712 82e207de9ea6e172f15bb76c88ed22b23ad4b303 83befe4d8aa160221aefcffcd6575b1a5375f18c 84e7294c1b8bc9ce3e3f6b60478c18fdd10d408e 8c74716c7b4783fd030ca38157fe8b9b722f547b a0aa5e0701f3bb532b40f53eb21f257ee2add4a3 a36c033fbd90e2dacfd9ace9134867030db5a5f1 a4b332bece6159ede85c95ac92fa2820ea47a3a3 abb442154aee2080f29691fd3bccaedfbb6cdfde aecdc1d65d0958327244dbe7389c0376d2bd6d76 b24c51b2679a01477fba19ed44ac18c216d868b7 be2cce208320a972f3e6a05a470da7b4322cb8eb cd4a936b1cec3b2bdee0f6c775fee7d0acef6296 cd88bdf7b8ff35084ce24e5c295ce5b504601a5d ec68a7e3355df7e0ba71c399b11d75fb6a4693fa f9087073bd36167f01b3c83fae139c9b52aabbaf ff00c7ea5705b3eb8c822418218add8b9b8ffaa6 Package: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 348 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.2.1), libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 47934 SHA256: e6f7ac1d6920c0f57691c048d994c9e901daf9c718e6d44c2ca599f7a1595cc5 SHA1: ac39f456fe7fdf65d170e3aa9817c67d4b0c64bf MD5sum: 01520507139dfcc92a73d7239e11df86 Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5172 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1), vrpn (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 1077458 SHA256: f556bb2601abba9acfa62fe935a6d0c259ba1efee3868b658ec5999a58e9223a SHA1: d60d891faa6da3842f7132b841c499c3a8b931e7 MD5sum: 7259b2bb3fb5c5ec3dcf19296bb5ecea Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 292 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libvtk-dicom0.5, libvtk5.10 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74420 SHA256: 92f477592c081c6845f6543d159cbf8bc61fe9a546f7f76368e98389b8c4ce47 SHA1: 654070e833e6bae0221c6cad237485d14ae991af MD5sum: 077421e9c48bf947c2eb4aacd390092a Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools