Package: aghermann Version: 1.0.6-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1501 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl0ldbl (>= 1.9), 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), libunique-3.0-0 (>= 2.90.1), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.6-1~nd15.04+1+nd15.10+1_i386.deb Size: 527790 SHA256: cedcf548f47fc09ffe3844d78f5cd3be39088f154c91ce42185978fa80d27ca1 SHA1: 22ba0a341754f99baeb0b901fb2fb530aa4c34c8 MD5sum: f5c203a9ddb504bc1d71ca81d9b6c834 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: bats Version: 0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: neurodebian-popularity-contest Homepage: https://github.com/sstephenson/bats Priority: optional Section: shells Filename: pool/main/b/bats/bats_0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 14512 SHA256: 6881fb51498874279b777b47edf727399a415a395d2680fc9ce2982ca4d62931 SHA1: 544960ea5fd3dbc490f0b8f6b7aacdc64759e076 MD5sum: 5eaaf67aeab77cb9788aef572aae6d42 Description: bash automated testing system Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. Bats is most useful when testing software written in Bash, but you can use it to test any UNIX program. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 724 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 256914 SHA256: e62db57ce0d573cf7e9ba6c39cf2d24192deb4006e24b1aa56ad14152f8c6226 SHA1: f6a793f384c73a0839fe83eb6e5e45be1c1ae472 MD5sum: b657293de77e29a794488695a26f7a8b Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: btrbk Version: 0.23.3-1~nd15.10+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~nd15.10+1_all.deb Size: 70920 SHA256: a4b6ee478aa5a3543fc853f817458546339c22bcf37cebd0b600aadcc1f7054c SHA1: d5ca7da62f20567345c5c4307d81dd7d2bd659e9 MD5sum: 130de16ffe35f95337b8372577d44bbe 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: btrfs-tools Version: 4.1.2-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3639 Depends: neurodebian-popularity-contest, e2fslibs (>= 1.42), libblkid1 (>= 2.17.2), libc6 (>= 2.8), libcomerr2 (>= 1.01), liblzo2-2, libuuid1 (>= 2.16), zlib1g (>= 1:1.2.0) Homepage: http://btrfs.wiki.kernel.org/ Priority: optional Section: admin Filename: pool/main/b/btrfs-tools/btrfs-tools_4.1.2-1~nd15.04+1+nd15.10+1_i386.deb Size: 529750 SHA256: eaeb9a2e8bacb3cabdaf78ccbf6b420daf1256bfcb65f107a8611a99084fc071 SHA1: 298c379e574783e1b0e3639c3dbeb69145daab85 MD5sum: 9a42edcea69a155d7e2327beb1e34901 Description: Checksumming Copy on Write Filesystem utilities Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains utilities (mkfs, fsck) used to work with btrfs and an utility (btrfs-convert) to make a btrfs filesystem from an ext3. Package: btrfs-tools-dbg Source: btrfs-tools Version: 4.1.2-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5094 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd15.04+1+nd15.10+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd15.04+1+nd15.10+1_i386.deb Size: 4238262 SHA256: 0d9efe85c437384726b1215a2a24911bb37949b7c9d8818922b4453d5bf06869 SHA1: 9136916d535bee4880c887b774c6cc22b6a7314b MD5sum: 439a5fe284623d39990c5f8aea964a5c Description: Checksumming Copy on Write Filesystem utilities (debug) Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains the debugging symbols. Package: cde Version: 0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 903 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 151236 SHA256: 0ebcde49377373c0cec19acd9fb4a7c1279755a3fd8b9beffdeb0f5d0662dce1 SHA1: 202f02f2b1a9007e0bde7f7481ae5c36951c0203 MD5sum: a361f5a642a2b245e5dfe7e8d0952865 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 25056 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk2v5 (>= 3.6.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), 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~nd15.10+1_i386.deb Size: 3900742 SHA256: 09149354fbcb61de75a121e221f1657622a75fbd258d11262774582d3159d6ce SHA1: 94814700c1032605eaf5e15d3495e640c9391083 MD5sum: 9434f848ad4c70226e4ff4a7133cc6f4 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: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.3-1~nd15.10+1_i386.deb Size: 17608 SHA256: f1fbc2b696d0510dd12cf7fda0b51361290894081294d3edb85cb6b18e067b5d SHA1: 0d2b093731bf8c38673d8dc3689a9d28257082d0 MD5sum: eb4c7a5414e56bd7143f21a8324bc6f2 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15696 SHA256: 9446cf3dc32428e31abba6f37f8ee70e4c72b623421e7b720734cb91a8423d2f SHA1: 50cb948a2ef0e59005fc394ece350ee2d2d015cd MD5sum: e8f39c3fea6a6fb2d9738d19dd2acda3 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15706 SHA256: c6739597f455d15f2d66e36a86527ec4848bf6efacfa5e167cba5cf68c49c111 SHA1: 4fb6d0d470ec33d187f36339c681327ee893ee80 MD5sum: db768bde0769b36c2d98ba681f6e9c93 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15704 SHA256: a3bb994ee3797ad5762fbeefd4c9bf172db5aa8adf43b4e018b0edbb4bf26798 SHA1: 5751d282c0fc3bdd1d953562a157d09a50a8f810 MD5sum: a5f950875317d283ff02c6188eff4b4f 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15706 SHA256: 4c54ed054045eb3703e0894e1f8457b97a60d68798c3bc7d60aa8304850f46bb SHA1: afa7450cc412a8289853bb2d2e06e0ab101061ac MD5sum: 0fd9590de47f6118ced61dafb416b94e 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 52430 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.1.1), 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~nd15.10+1_i386.deb Size: 25593798 SHA256: f44b3c44ee4ad022209051b7cf93ffecb7277e1c5137968d595e78959b350d69 SHA1: 093cc4e7555d079514d4423b83e27f14e5001bdb MD5sum: 0d010f9e7c1c11737268c84d8d45411e 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120762 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.2.3-1~nd15.10+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~nd15.10+1_i386.deb Size: 118806802 SHA256: a8c34d881909b9cb77c420372731c92e2ecf21940345d36b1706a518b654eab0 SHA1: 62f40de7ff5dd3d19620b230a1c4fe701a7034c1 MD5sum: 9949e8080c8f86239dfa6266b180d540 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. Package: datalad Version: 0.3.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 75 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.3.1-1~nd15.10+1), python Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.3.1-1~nd15.10+1_all.deb Size: 43802 SHA256: 53189e3a7fbd1204f6461179a7924bb1a0947924b8b929becf4c1a8ae626bb50 SHA1: c2ee4fcf6cf1fdea6da49184742222be56917857 MD5sum: 2bb2513d9d4a9fef0490b7b8f4a5d986 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: 20160921+git16-g0339407-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 227 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_20160921+git16-g0339407-1~nd15.10+1_i386.deb Size: 97458 SHA256: dbb02ff7a3aa894c18ccb1f28b91d120c901fa49e20c5a336b882cc0b9580b08 SHA1: 120fbee15c393d5c02872b656cef24ad82b2d24d MD5sum: c47715235c8ad0d9a12a5d13647ef983 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~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), 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~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 37288 SHA256: dfee2d62a8b21f45486fd0b2c5a442910dae14e76707ffb567b9b17439a17606 SHA1: 06f0dbaa7d4fb3c93f289e3cd7aa335d7b680047 MD5sum: f004ec2ca398fdd609a45e2e1b35f54e 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: fail2ban Version: 0.9.5-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1227 Depends: neurodebian-popularity-contest, python3, 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_0.9.5-1~nd15.10+1_all.deb Size: 254450 SHA256: 96c4391d7ea3d2c46d450cd4c718f69be479d4201b786e7e87c33d64b062ed79 SHA1: 89807f1fea757fe6d8e8b5666381d2b22273c0f0 MD5sum: cf6f1991d43d85bdc3bd78507972ffd3 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: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd15.04+1+nd15.10+1_all.deb Size: 1182 SHA256: 60b6d2c21158c4b47d2345eed3adfce849ecddb95da5e5f6eab8147e1702e10b SHA1: 56bcaf82bfd7a9b340454c6740d80b6853fe800d MD5sum: e72f3aca5118a4c29a8b436cc7095d92 Description: GNU implementation of the IPMI protocol FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This metapackage depends on all separate modules of freeipmi. Package: freeipmi-bmc-watchdog Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 45170 SHA256: f954f6a13827e02cb456f8b7853797c0fb7f62247f0ef4245eac0c8d9800155b SHA1: 3463eebbbe23bb3328cc97941e33d6a75852ba24 MD5sum: 13c674760db2880505efa06ebb488a9f Description: GNU implementation of the IPMI protocol - BMC watchdog FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a watchdog daemon for hardware BMC watchdogs. Package: freeipmi-common Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 344 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest Suggests: freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-common_1.4.9-1~nd15.04+1+nd15.10+1_all.deb Size: 189340 SHA256: 8c8771e9f18e42173b0e14bab4ca2f15ec66624697b7f2742331e2a3db33e670 SHA1: ac695cc3eeeedfa7c22d9153d669a72bbc905ebd MD5sum: 1c4ac4e1b0f954c734cb90717604f6db Description: GNU implementation of the IPMI protocol - common files FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package provides configuration used by the rest of FreeIPMI framework and generic documentation to orient the user. Package: freeipmi-ipmidetect Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 39722 SHA256: 2ae6f6d3bb6d4b3f1a05d66e5171ccaaa64f662d201ece4ccd594e8f98903723 SHA1: 7e000609c6ab2829412547c6f19b16f2888bd0d2 MD5sum: 0dbe5e90d6202a4512cd783bbaeff683 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a tool and a daemon for detecting IPMI nodes. Package: freeipmi-ipmiseld Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 215 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 81510 SHA256: ba91bd5a287199d91e5dcd4a12af2d5115324b191d71119dff4fe847ff2d2065 SHA1: 06a95d3dc6bc3c9228b4ac09e83034243e49d5fe MD5sum: 6619562353fe9e7f54c6699ff89621d0 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains ipmiseld which takes the system event log from the BMC and imports it to syslog Package: freeipmi-tools Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3035 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.9-1~nd15.04+1+nd15.10+1), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Suggests: freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-tools_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 621360 SHA256: 4751473665e4be39ad27ddcc33e563849d34eafec68cae8fc0d8668f03d034a7 SHA1: eb7423b8f5a6100999f72eb509ae6ad354e1b64d MD5sum: e968fcf1f9041883ce40115e488d5c44 Description: GNU implementation of the IPMI protocol - tools FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains assorted IPMI-related tools: * bmc-config - configure BMC values * bmc-info - display BMC information * ipmi-chassis - IPMI chassis management utility * ipmi-fru - display FRU information * ipmi-locate - IPMI probing utility * ipmi-oem - IPMI OEM utility * ipmi-pet - decode Platform Event Traps * ipmi-raw - IPMI raw communication utility * ipmi-sel - display SEL entries * ipmi-sensors - display IPMI sensor information * ipmi-sensors-config - configure sensors * ipmiconsole - IPMI console utility * ipmiping - send IPMI Get Authentication Capabilitiy request * ipmipower - IPMI power control utility * pef-config - configure PEF values * rmcpping - send RMCP Ping to network hosts Package: freenect Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.5, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.5.3-1~nd15.10+1_i386.deb Size: 8638 SHA256: 0d8849549cbd84991fbc3a56014e88f8b6c39cb5b57f326e6410bc5623109ac8 SHA1: 76aac5ecc0935cd7eb6cd20984837be5f0a47d92 MD5sum: 8ec8f8719b29a89ec36d15b03eb3ecc6 Description: library for accessing Kinect device -- metapackage libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the metapackage to install all components of the project. Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 74 Depends: neurodebian-popularity-contest, python, 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~nd15.04+1+nd15.10+1_all.deb Size: 14008 SHA256: 7914c84001d5d40395cd90f595918f2d555e064191eb0c82e12482b8f9342b51 SHA1: 29f0aa4897a3ab0df34c0714b15c4edb0ca36a9c MD5sum: d276326178c61759af9fbda0e55984fe 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6332 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.10+1_i386.deb Size: 1320528 SHA256: ee3dabc4fa0d5cd6f96675fe47878459deb713a4c630dbb68d9c3c4ac2063a85 SHA1: 6ab9c36a3580ff9eae1d31b8024824f904095a81 MD5sum: e8e86aa91fa5efda4f2836f0822b15c2 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~nd15.10+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~nd15.10+1_all.deb Size: 2227766 SHA256: b6b234616692811051ceae1797aa66564b4f8758dcf25bbb5dccfb3507415ec5 SHA1: d52e90e3b672521dfca81e1c7b31d5b4280f289c MD5sum: 2122c874f07d05bd8ac82f19908baba9 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.4.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1767 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~nd15.10+1_all.deb Size: 1669844 SHA256: 6b9f4730136baf6dd9d823a4cc7f5eae5a8e89626c061299d1dc12bcd771868f SHA1: 761a105102f92060c44a05310e529ee818388d71 MD5sum: 264264d63451e48e9d91c802e4a5b5fd 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: 6.20160923+gitgd1dabb3-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 422532 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: graphviz, bup, 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_6.20160923+gitgd1dabb3-1~ndall+1_i386.deb Size: 29796568 SHA256: adf379c8d71b63214d4d73ff4b4d116e65c596a6ce6a4dadfb220d7879810bfc SHA1: 336792efc24f7aecd8870ca0800707dd1770b057 MD5sum: 5507160c7310d2907e319d89ce0051da 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-annex-standalone-dbgsym Source: git-annex Version: 6.20160126+gitg65f4442-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 39 Depends: git-annex-standalone (= 6.20160126+gitg65f4442-1~ndall+1) Homepage: http://git-annex.branchable.com/ Priority: extra Section: debug Filename: pool/main/g/git-annex/git-annex-standalone-dbgsym_6.20160126+gitg65f4442-1~ndall+1_i386.deb Size: 9134 SHA256: 3ff64a3074f84e31588a7fa065be9213c9cd1cd01d2cb872d1798887285c53d7 SHA1: 094995a0da75ca3805883454b37dcac6602e2633 MD5sum: 4469eb146705aca1d596c5c0349963fb Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 8f6f3d23dd9d1fb3f208bf0b95fc198d8d444fc8 8f6f3d23dd9d1fb3f208bf0b95fc198d8d444fc8 Package: heudiconv Version: 0.1-1~nd15.04+1+nd15.10+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~nd15.04+1+nd15.10+1_all.deb Size: 10308 SHA256: 30d0e4ed576cac2717b74d400973e01a200ece9ed614077c3ff559ab0c11fb6e SHA1: 660b1b59c76680b903c6185b7b433335e4e2cf5d MD5sum: 10f70c3a99e585206dee3f9403d8f7fe 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 12774 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1), perl, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 3), libglobus-common0 (>= 15), 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), libgsoap7, 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 (>= 2.4.2), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libvomsapi1v5, 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_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 3748342 SHA256: 8e4098ab6e8eb344486d7a9ca83bc0a7a0b92565d36a9d30e7ba05ff47571118 SHA1: 884f30aec5f5d24e7277b882ba52d818c019d370 MD5sum: bb79746da7b684acfa782a56e98f1dda 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 34417 Depends: neurodebian-popularity-contest, htcondor (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+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_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 32797050 SHA256: a65819828f9f90356f3847c4de37d32c81ab447b43868493a97c4fa390246fdc SHA1: c8983423732497623a33a83167ffc637046c3a8a MD5sum: ef75c944560eb1118a20f5a54b31ac43 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. Package: htcondor-dev Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1403 Depends: neurodebian-popularity-contest Breaks: condor-dev (<< 8.0.5~) Replaces: condor-dev (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/htcondor-dev_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 324850 SHA256: 2e9121fbdfb8ce3dc9996e7b3b7aad988f00cc776bea378983738df1d173288c SHA1: 9bcdc3c99e98ab2c4338dbf9cc633beaab4c4fcd MD5sum: 6b07c8f50505181b3b05073bf00fa4a4 Description: distributed workload management system - development files 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 headers and libraries for development of HTCondor add-ons. Package: htcondor-doc Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6028 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_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 1064326 SHA256: 89ecfcfb0bccc5ca4ad19fba4b3c84087f4054b9cee40d88ca16dafd992459ee SHA1: 0b354dfa51fd2ad34160d005eca34a38ea5264f2 MD5sum: 1473b4fe1f7412efebd325a5822e6093 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.11.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 436 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil | python-imaging, poppler-utils | mupdf-tools | xpdf-utils (>= 3.02-2) Recommends: mplayer, pdftk, perl, xdg-utils Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.11.1-1~nd15.10+1_all.deb Size: 175612 SHA256: 85edf5251e3ca7fe619122697298346cbc81189c385325c1040321e1541cbe90 SHA1: d842248cbfecbfb42164fbe71368bbe42ca1ee08 MD5sum: 72a27ab94bb28731dd2606d51a7425f9 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd15.10+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~nd15.10+1_all.deb Size: 5020 SHA256: 1563317403e6ea4aafcfde81fbe117b6dfac65716db2be3a595efaaead95b6cd SHA1: 02f380f8792758da55e050c656e7373602983023 MD5sum: 929d61c356c458f97fb2dfa6014e68d0 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1), libboost-program-options1.58.0, libc6 (>= 2.4), libfftw3-single3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd15.10+1_i386.deb Size: 127106 SHA256: e7f5513b1044bef94c318ab486eb2c865bd12dc2fdadcc42d851385247b52975 SHA1: 215a43054b2b362ef5159c0093e22add8accb9fc MD5sum: bac7bffee897b86ef1ec4d9d9a888427 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: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1407 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 321234 SHA256: 52d831774169b9c59d7ffc9fe9745045bcb6215c06030b943617aed11c6088cf SHA1: 0d2e10eb71e890318d137eaa5a257333b72eb5ac MD5sum: a1c756071599a64c0759adc635c3db31 Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig1 Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 862 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 287814 SHA256: bfaebb165bff7880844447be3873ef7c540a78fcf018afe567c6a9935b48f200 SHA1: 2d0c36e9706aab36b0d4070e659005c70e63e23a MD5sum: 5cf7c7f412792bdb68e2508bffea5399 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig1-dbg Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 70346 SHA256: 107fee1f0a5412cc51e7ea08542acde57e10e58f93e85c9fa8af040d1443989f SHA1: c78102fef930f7bc697b3c41daef8c24b626cbea MD5sum: b9df9a871f9fc267216f7ac01061f3d3 Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libclassad-dev Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1156 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+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_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 244594 SHA256: 555f6af61419dcf009e53bdecad4945813b7e7bf5caf5389796dd89079494c83 SHA1: 5cc725c898abc86e68284ab563bc62adf52c60f5 MD5sum: 8b8eddad34b8e94b55df9ec05d506018 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 596 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpcre3, libstdc++6 (>= 5.2) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 202982 SHA256: 4d117f313c0fbe00e4ef39c596774d476dac51598ebe617ee1efb8c6e97947ea SHA1: 5c067c5d330331e52ec27f4f6b4689a4e1c92476 MD5sum: 48f89557359aba952219e4a50469a85c 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: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), 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_2.0.3-1~nd15.10+1_i386.deb Size: 79606 SHA256: f608d061c9fc7c42c16432c08f3008bdf20e17934acc63731d656ef4211f5fa2 SHA1: bba9e55ecceba0c7963b7e74e6292720b3e35bcb MD5sum: 03f8912bfbf86985a2ca938f83a1eefb 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: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.3-1~nd15.10+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.3-1~nd15.10+1_i386.deb Size: 21236 SHA256: c7068c5952150ed24a23ebdb784fdb97188c6b2f387c858f08f0424f75b5cff1 SHA1: 97bd5de34156868d88d955777376fd7490cf76c2 MD5sum: a996c8bc22d42238efafa2c09ca502e6 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: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6522 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libfreeipmi16 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 897828 SHA256: e0dfe6680106a49669bde643d143734a3057b859f1463317197b1be83abbe45b SHA1: 8b7db93ee31cda32094aa7e8b7531e01f5be35eb MD5sum: 436e385144c763272dd3c5badf867b71 Description: GNU IPMI - development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libfreeipmi. Package: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4219 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt20 (>= 1.6.1), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 743950 SHA256: 09f548e48661d014dfd2264d6f6023781fa95b93cc42e39c94c7e604d86da89f SHA1: a88f16f9bb1682b0258e2809fbe67ff458477479 MD5sum: 6ca2c213d9682160ad9cb6adb0a54291 Description: GNU IPMI - libraries FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . OpenIPMI, KCS, SMIC, SSIF, LAN drivers, and an IPMI API in a C Library. Package: libfreenect-bin Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 219 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.5 (>= 1:0.5.2), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 5.2) Breaks: libfreenect-demos (<< 1:0.1.2+dfsg-1) Replaces: libfreenect-demos (<< 1:0.1.2+dfsg-1) Homepage: http://openkinect.org/ Priority: extra Section: utils Filename: pool/main/libf/libfreenect/libfreenect-bin_0.5.3-1~nd15.10+1_i386.deb Size: 54774 SHA256: f24a854698a1eb13465b0deb49af413462262354851ad8435bbb97954f3b872c SHA1: 13a9eeda5404a9f25d3e4750a343b699b956e809 MD5sum: 56e16fffbcb59ea634e75a78ade1c80c Description: library for accessing Kinect device -- utilities and samples libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package includes utilities and sample programs for kinect. Package: libfreenect-demos Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.5.3-1~nd15.10+1_i386.deb Size: 8662 SHA256: 9c7aa7a4a1a9f740f7200b75e868cab23b7835bafe870356d97689900a36ae6a SHA1: 363a1bc02f08c8905e2af6292314d107dda03437 MD5sum: a0e809607693081bc13daded68598d67 Description: library for accessing Kinect device -- dummy package libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package is a metapackage to do the transition from libfreenect-demos to libfreenect-bin. This package can be removed after installation. Package: libfreenect-dev Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.3-1~nd15.10+1), libusb-1.0-0-dev (>= 1.0.18~) Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.5.3-1~nd15.10+1_i386.deb Size: 19426 SHA256: 9fbba71e92f95124ffed3820e25ec2dd20c41d3dd3770479f63596c7761a4d9e SHA1: f5d4ee3aca112d9957a4f58499744926d8986e4c MD5sum: 29043653576c1d320643884f1adb4dc4 Description: library for accessing Kinect device -- development files libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 829 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.3-1~nd15.10+1_all.deb Size: 133898 SHA256: f48d3817a02c25b6076eb52fcc7a5abbdf90b9f7278992a7cc5a7c9dcece67ea SHA1: ee48acb9c6070a8eaae4884cc160b3e584114879 MD5sum: e3a1bc6631d8f8785711280c567cd197 Description: library for accessing Kinect device -- documentation libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the documentation of the API of libfreenect. Package: libfreenect0.5 Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 134 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.12) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.5_0.5.3-1~nd15.10+1_i386.deb Size: 45446 SHA256: 392a2a04287d14be4a71e56946bdd4e121ff1b7853d5f55d4ea4034a62cf2939 SHA1: c0e4a80f69abc5c35657726c01fabd0ebfe73cf7 MD5sum: aa6e06962f2daedf2d334fcb4a756808 Description: library for accessing Kinect device libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the shared library of libfreenect. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 447 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmiconsole2 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 104830 SHA256: 059a7a3dbc09b009f0241b4e7f724ea0dc6f29ae82665cb04a7afe90c9f57783 SHA1: 8be8ec933a59c68ab8373313b5b73e593a85f784 MD5sum: 2f615ac4a9ba48c457949d029df66480 Description: GNU IPMI - ipmiconsole development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmiconsole. Package: libipmiconsole2 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 317 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 87622 SHA256: 28c55c2d3eb47e723321259f0df988f65390b42fc580b54f3f44b114b88287df SHA1: 631d624e75290b44a5f6cf36b863ebc743b4eda9 MD5sum: 00b15491158816a52593f94370e457d7 Description: GNU IPMI - Serial-over-Lan library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for Serial-over-Lan (SOL). Package: libipmidetect-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 110 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmidetect0 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 33310 SHA256: 24cea7db4549e899a0c0942677d5ce5aa022c0403b8514423732d7b22710c6ca SHA1: 5802d519f354c0da83269caff7b062ccefbadb92 MD5sum: e3f5f61da5b684441077b4df9297265b Description: GNU IPMI - ipmidetect development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmidetect. Package: libipmidetect0 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 26976 SHA256: 1302ef2920103d6624889ea6ab8799141e74de9c0730154d4737b42523bed4e2 SHA1: 80600c88a4f52c0ad5be86e3131cd4ab8436bfca MD5sum: 24ff2e3464b5ace6f253f368b4739cdb Description: GNU IPMI - IPMI node detection library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for IPMI node detection. Package: libipmimonitoring-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 297 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmimonitoring5a (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 63350 SHA256: 6b441527e1f107f0dc7b255ba16cab519989486a4f4d197476e6f0854993cb05 SHA1: 443c2b2cc0e6c80d9aee3f77161ce4d99135d33f MD5sum: df1ff3af53d928b585b0ca9a7cd53397 Description: GNU IPMI - ipmimonitoring development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmimonitoring. Package: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 45378 SHA256: ff33ba44eed55089b8b2baded6b04e70a126f564a22eb0e3ed3aee76dd4d3831 SHA1: e027d9e00b482d9a65d036ecdda6a2ad9519c6ee MD5sum: dd35b7a8c9e1db3aed21924fda1f5400 Description: GNU IPMI - Sensor monitoring library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for sensor monitoring. Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd15.10+1_i386.deb Size: 13796 SHA256: fff7b3c5892723e20ccb1836eaff3535b41273a858732ddbf214529be826d9f6 SHA1: da284bb70a5928a31a351f811beced24fb480b49 MD5sum: 777d5524e0be6e99165aa7e098c17baf 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1987 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd15.10+1_all.deb Size: 158280 SHA256: e2638885c6f67fa4fe3805ce145d47836afe4837cb23cfe9160feab83b270744 SHA1: b7d385208ffa71c26321c7b8c6d5b0d47c9df36b MD5sum: 3d81a093867c814aba2efe0714148ee7 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 349 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libhdf5-10, libpugixml1v5, libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd15.10+1_i386.deb Size: 84760 SHA256: 38cff1d9b5232a48c64a51880d5f61e681019449d78f180162169b6322fb0da2 SHA1: f53e533cbda2d6bcb9f14128f26df8d56cc22953 MD5sum: 9626c0c966f3756cfaccfb9f93957fca 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: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.04+1+nd15.10+1_i386.deb Size: 73610 SHA256: ad6448a718be80be0184563ca2f0b8dba7b5819863ec08929e682ed49143a87f SHA1: 966856ff809e2ea214cd50d322f8136584c2711b MD5sum: 6e9fe1818c19e1d032cbc86d0d3f6b4e 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~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1450 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.4, 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~nd15.04+1+nd15.10+1_i386.deb Size: 434042 SHA256: 08243dd91fce8a2c380c427e782f1e37db6e8d4852522b6ffc97140701cafc1d SHA1: ca4f758f23041c13bf72c9565c6cd5428da738e0 MD5sum: f70d9797d08e746cbc3037894d65bcbb 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~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 565 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd15.04+1+nd15.10+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~nd15.04+1+nd15.10+1_i386.deb Size: 80842 SHA256: 28c06815bad594661b326a96ae3fa120d82aa7e15b68de93c8678b2ec5437aae SHA1: 6507b903f8b7fcc27f5074d29e83cc75e3e6f9b2 MD5sum: 9b91b22e2b6775c96bbf5b38773f1600 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: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 107 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_2.0.3-1~nd15.10+1_i386.deb Size: 37922 SHA256: df1bf4f83434b67f5401e4cbdbaecace920c93e8b6880fcba0a3948a4478ec2c SHA1: 450a3d25fc1d8fee01bbba379a82526e9fb15d72 MD5sum: 72cabae6093992c11e50485569738467 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: matlab-support-dev Source: matlab-support Version: 0.0.21~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 17 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.21~nd15.04+1+nd15.10+1_all.deb Size: 7574 SHA256: c4ba8aa092fdd78ee931578a1ef13d097c0f11b0c0a26d1bd721c8bc26fc0b0b SHA1: 408915ff3fdbdc3379b8b317e606bb3902b1b167 MD5sum: 7afdad825ab8ac1b1baf462865536314 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mriconvert Version: 1:2.0.8-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5323 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.2+dfsg), libwxgtk3.0-0v5 (>= 3.0.2+dfsg) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.8-1~nd15.04+1+nd15.10+1_i386.deb Size: 826056 SHA256: 2e592861d495785f5952dc9e9e72fa60c668e7610a4c1b738540953a18cc8c46 SHA1: 27060ebb5ea78e000711f6347aa41da0995bbd47 MD5sum: 5b61b8392d6afaa36412ee9ff1c6b185 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 12753 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Recommends: pigz Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 2108170 SHA256: b5497bd299d760b6180d7420be1b849df585aa685569250c931ca0961ef19e58 SHA1: 421aee912182cad14d1f46875104d4b1a2b0c869 MD5sum: b68378404c78134da66e040cecf3a532 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1694 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 1658508 SHA256: 8135e0e979a53f598e15999779129c5891566fca7691dc51878804e594eb6309 SHA1: 4c8d7ec1a93894e61be7c6723235c31bf027e187 MD5sum: 1a2dfd5641a5429fcdda4af3ff4fcfac Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1022 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 577428 SHA256: 4d9c8d3ec4d9446b555e7f2949108061bdc1827a1c77928cc1c3d260e53e35bd SHA1: 60ec2b395eb76953884e28d6fb1c4b0d43ae5183 MD5sum: 570e54c34d0bc3a576c4fb8117711d70 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mridefacer Version: 0.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: neurodebian-popularity-contest, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.1-1~nd15.04+1+nd15.10+1_all.deb Size: 637094 SHA256: 85c3220393ef2dc9eeb6d7777bc4e63f769e6833080cdb6b91f2a964ab1cdd5d SHA1: c56285b2c25d28a511bbf07c3afe08a0b9e0ff34 MD5sum: f31372a79b07849a37ab4489d5152b46 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: ncdu Version: 1.11-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libncursesw5 (>= 5.6+20070908), libtinfo5 Homepage: http://dev.yorhel.nl/ncdu/ Priority: optional Section: admin Filename: pool/main/n/ncdu/ncdu_1.11-1~nd15.10+1_i386.deb Size: 39606 SHA256: 2c1f2d7bda487445a613f254170429055889ce9db642b0b14bcb80eec330a4bc SHA1: 0a9e3d50efbbea639e63a667c7d3bc4aaad4cfea MD5sum: fd05f276790f105e64ff57fd0a78bc0b Description: ncurses disk usage viewer Ncdu is a ncurses-based du viewer. It provides a fast and easy-to-use interface through famous du utility. It allows one to browse through the directories and show percentages of disk usage with ncurses library. Package: netselect Version: 0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 62 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 30936 SHA256: d41285938985ba643ea4da2d2749ea9480fef3f04a1715487ca537ac53b6e9ac SHA1: 1daf7de93404dabb09ff51d6a7d02c4d9a814b3c MD5sum: 109c0acf1202fb7d8b33a9edd47272d1 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~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+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~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 16878 SHA256: 17eaf7e30e8d133bfc96ce4836eaa927a14b1d52f9e245f20c56d9243260a1cb SHA1: 7ad6cc055aa912d0eb77b5084d8369855d5523cb MD5sum: 2cdbfd381825e0b50128b3f0a06f36b0 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~nd15.10+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~nd15.10+1_all.deb Size: 34670 SHA256: a2e597e2290c05d8397bbd041c0ed2211a9a41cbe51f6664fae1c8662bba48bd SHA1: 3b62762fd516b0604f8c4a8155d495bc5c84424b MD5sum: e1c3c9c5ccfd3cccf9fff08372019a3f 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~nd15.10+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~nd15.10+1_all.deb Size: 10366 SHA256: 4843cb2048093baf721cb53ea933716db14c680ffd62bd291706eddd62db03d9 SHA1: b40f6c50ea596a14c9071abd84b823274ef18b2d MD5sum: 357012987c1b8a9068697fe920a06a07 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~nd15.10+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~nd15.10+1_all.deb Size: 116360 SHA256: 0e39859f7100a5a65defa67145d7952768f2d263464e95ce52bc88e125278b24 SHA1: e4dcf055f0f70c9952c453070af81163f481c351 MD5sum: 9a2d050e10ae38536441a4702c25378f 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~nd15.10+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~nd15.10+1_all.deb Size: 32744 SHA256: 434ee16b7d6eaffa1f5425e9adbb95d785c8b34e8b4feffaaf4878a31c63a961 SHA1: b9fe99da28a7c2a7a106841e1fe0b2506a42114e MD5sum: 8bfaacd2717f385e6a338dcf5d06cabe 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~nd15.10+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~nd15.10+1_all.deb Size: 12370 SHA256: bf36f8b1991bdca742a1e65b57ff7d0705e22ac1b40d61359796eec31ddbc2de SHA1: 375986fd69413c6aa6551cdafbcd3318e88cd655 MD5sum: 3a8350c82607bd6cc1ebff61c0e3aac8 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: 0.5.23+ds-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3071 Depends: neurodebian-popularity-contest, g++-6 | g++-5 | g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | 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 Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.23+ds-1~nd15.10+1_all.deb Size: 635392 SHA256: 406f8b1dbec057d7714a118311253e88d234aad95d3f74eea3e01dc3543f75e5 SHA1: 9f16c1e7a27d66080f7473c2bea23b90fa71ad5e MD5sum: a403da330a231af7fb7fef534cc4df71 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-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liboctave3 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 20442 SHA256: 4feba21e4dc6ee020d9007774be06730934efa95e60d4bada459cd1cc5c2326d SHA1: 41233bc97cfe9f21250241d9e5182e0a75d35b79 MD5sum: b06a547a241e0a724ed1e25a184e22fd Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4305 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), 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 (>= 0.8.0+git20071002), 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 (= 3.0.12.20160514.dfsg1-1~nd15.10+1), psychtoolbox-3-lib (= 3.0.12.20160514.dfsg1-1~nd15.10+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_3.0.12.20160514.dfsg1-1~nd15.10+1_i386.deb Size: 874584 SHA256: 7c5cc7ac8ea86458063fc0b6a93f6ef818acbdb7e83f323e876b2656ca36b547 SHA1: f933346afd3c3c74869d251b360bc44026cbad57 MD5sum: 5b9315f253c289ed5a0f07f25e975770 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~nd15.10+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~nd15.10+1_all.deb Size: 52282 SHA256: fb227d135c699191f46b5c6e01e94de6371e98e9530e345e26229ae59a55adc9 SHA1: 69d76b680502acc089d2176d125325fec31c0919 MD5sum: 90cbae6c8fef09eaefb2b70c7e394b8b 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 927 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.10+1_i386.deb Size: 371962 SHA256: ea86f4834732bee3a368d1bc2d677aaa2ebff02103bf9a979c5642d251258f0e SHA1: a8b9ea5f4b7cddb14e5de2ec6fb6001c96c5058a MD5sum: af5837d45c45666574f4a1cbe6ad7c41 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4509 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd15.10+1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.10+1_i386.deb Size: 1350516 SHA256: f4a97e4b281e387a919518e43cb0a1c6dc54dbd2004db8a58c408b0c073252d4 SHA1: 42702b26bbc0693e5d81fb2dcefc59ef3da1f738 MD5sum: 08ad44f4ff162b048c1cbca8a0c65737 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: psychopy Version: 1.83.04.dfsg-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15135 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~nd15.10+1_all.deb Size: 6139344 SHA256: bc911feed2a42fd4ff3ea339af8a06ceab8a7a65246088e2976c0286604dfc5c SHA1: 359c10be3294aab7375f5362a6c9cf15b4647d65 MD5sum: c562a6677631236165fd33641ab943c6 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: 3.0.12.20160514.dfsg1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253492 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_3.0.12.20160514.dfsg1-1~nd15.10+1_all.deb Size: 24203912 SHA256: 9d3805c306f170968de2b35c5c2e9da0c8e800b6f629751f90d22a93c9389f93 SHA1: ff4ac8234f5ccaa5a985856128d9dcc253b08775 MD5sum: 9c4ebda1da7cda19935aa24f552f97c1 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: 3.0.12.20160514.dfsg1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3570 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.12.20160514.dfsg1-1~nd15.10+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.12.20160514.dfsg1-1~nd15.10+1_i386.deb Size: 720024 SHA256: 9bbabfc13b57b1414a61d21fa4f63a4e1741f071ee34199581d1e055b36c7967 SHA1: 5308615e99766b8ba16c51a9f103296bcc03f578 MD5sum: 3486d63647c12c7c349618ff5ab892f4 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: 3.0.12.20160514.dfsg1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), 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_3.0.12.20160514.dfsg1-1~nd15.10+1_i386.deb Size: 74428 SHA256: 11bb768f1244b24c486c77972b0a068db10157e4e0df008827dc81439760ae12 SHA1: 34402413cab3915a5a0add56be7f5d5da175ca90 MD5sum: 92041a7cd0f4e1c2914b4c765c9e16eb 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: python-argcomplete Version: 1.0.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, python, 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~nd15.10+1_all.deb Size: 24548 SHA256: f7f752ddd5216e4e54219fbb7dfa743509d504bff9b94692c6c8d094cf70d2d6 SHA1: 0ba7fef1876c4ff20ce75950de751808d72eea5e MD5sum: 5cbc851db5b0ee7f45a9f1bdfde24345 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-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.4), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 44478 SHA256: 4fb44cd5802b5ec13a6cd84fd5a7f708741f742a90fe2133007ed1e8abb52407 SHA1: 966f5028beda79ce49980e94a18293140d87e86f MD5sum: 87ce5c4abeb6d7d3f18e4cbe9da333da Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-boto3 Version: 1.2.2-2~nd15.10+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~nd15.10+1_all.deb Size: 58428 SHA256: fd3aae29e7fde4d794485c3394b335372fd91040887a1b924744f4dd5cd76996 SHA1: 55200a00a5b19ee03d1ac7b7acb4a02aab73a66c MD5sum: 24145da68d681d87e9764d1123237b04 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-brian Source: brian Version: 1.4.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2456 Depends: neurodebian-popularity-contest, python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-brian-lib (>= 1.4.3-1~nd15.10+1) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.3-1~nd15.10+1_all.deb Size: 401954 SHA256: 2639f7f94a02b6a03b9d994514ec825013a3157e43e97548353ec48e50e4216e SHA1: cd7707a98f72246a465777c0beed0236e20d4458 MD5sum: c6ab48b5678813612556e161e4a69702 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7180 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.3-1~nd15.10+1_all.deb Size: 1984672 SHA256: cabd4cc24111bb1fdda894ba7dee2160d6cb1a6aad208523cd60392a19e58245 SHA1: 350f233ee92a864c5df8d70231180439fea315a8 MD5sum: a7dca5cb412c628e6b136e204ab96c5d Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.4.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.3-1~nd15.10+1_i386.deb Size: 41376 SHA256: b4b816d174e655fd0d97900d165e6759d5bad4c8f3bc7a752df9b74a39fb0e30 SHA1: c7323fc699017a2c3a230bbe11b8be8d7294e8d7 MD5sum: 857033609a3d2fb695916cfb6bed9aab Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 769 Depends: neurodebian-popularity-contest, python-lxml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python-citeproc_0.3.0-1~nd15.04+1+nd15.10+1_all.deb Size: 80446 SHA256: 53b97c0bcbd0e47ec9774a2a9c7948e7f7e6bdd0df9b4cfde61a69f0bee41293 SHA1: 2b9b89bfacadfab9db387c56b59d0a812495fa76 MD5sum: b04a87a0a44d909fbb49ed03106c9c22 Description: Citation Style Language (CSL) processor for Python Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python modules. Package: python-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python-contextlib2_0.4.0-3~nd15.10+1_all.deb Size: 8670 SHA256: c074f20a0bd51ed6eff89cbf6eecdd6517945fb4a709028e576a5e3a147db14a SHA1: 9124d93433c0907b1bd8082bc389f201a30bf631 MD5sum: b498d2525417efaa8d645bdaede4590d Description: Backport and enhancements for the contextlib module - Python 2.7 contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 2.7 module. Package: python-datalad Source: datalad Version: 0.3.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3000 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), patool, python-appdirs, python-git (>= 2.0.3~), python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0~), python-boto, python-jsmin, 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_0.3.1-1~nd15.10+1_all.deb Size: 584588 SHA256: 5ac028a5236fa565bee19e18041dfd064fe894f14b5e7ca949213ce1e509d5d1 SHA1: b995d17ab296a0197451ce694324ab4a140f5e7c MD5sum: b6f616bf0638f7b590bcb5ee7e5ce50b 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~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 502 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python, 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~nd15.04+1+nd15.10+1_all.deb Size: 78672 SHA256: 3dd0a721cb37499d77ea79aa6e90f76f25f033c06f52ce14e1e17202869af2b7 SHA1: b09765500ff57e38cd3624b02fe6cd9b7d25c441 MD5sum: 7cdebfec320f98b77e6d00bc110e9efd 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-dicom Source: pydicom Version: 0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1577 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://pydicom.org/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 359402 SHA256: a903e4b3b558d463a4807396a61dd2e71a4a9f204e9bfd56ebd21976ef56ae1d SHA1: f2eee4b06269a67d248f2bec75022de23ba9d608 MD5sum: 37c3a5938f94239a63f9d775ddac2247 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.10.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5796 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.10.1-1~nd15.10+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.10.1-1~nd15.10+1_all.deb Size: 2432344 SHA256: 2ce891614ec444d3dc6b1dc7efa3e60da6b4de7e77f8570deb85d5882ccf4a43 SHA1: e00f8d77a2901b521106fc09a227d744088d8b9e MD5sum: abe097e39581f6fc823e32fa2c2915f2 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.10.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14454 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.10.1-1~nd15.10+1_all.deb Size: 11466158 SHA256: 312104a24c4527f0b033bac1b035cc82a1788f70c57481050081c149790f1ec3 SHA1: 30bcb9425222d67b7bd2c54a97341e88189574e8 MD5sum: 260896a62e95ce91b89fc607e9ab1b73 Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.10.1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7103 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.10.1-1~nd15.10+1_i386.deb Size: 1107252 SHA256: bd0d0d21cc7cfe71a032582cd43db79fd7d10e23282f9d6921edbf8c8e307ce8 SHA1: 30829946c004f4567e5c2177b9153569cda13fac MD5sum: cbfa94aaa3987b305f80d2edf3ff8f0e Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-duecredit Source: duecredit Version: 0.5.0-1~nd15.10+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~nd15.10+1_all.deb Size: 49850 SHA256: 34ba5522914bc75422c137fa1e9a61e326547406b6ab0ac44ee525684030336f SHA1: eb907d4293cf283eda9759db6d7ac83122aa00e2 MD5sum: d24994599ed227b6321c595c0a7678fa 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-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2571 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 698814 SHA256: 6652ba241c1aa160d58862a8b30b7c463e89b24ecc86de70e2069606aae1292a SHA1: a0369e3800708c5369ec11a0cf8612d68c3a02cd MD5sum: 7fbb095c97ab3ed7df202c7ef2a552e2 Description: Python library for cognitive and neuroscientific experiments Expyriment is a light-weight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments. The major goal is to provide a well-structured Python library for a script-based experiment development with a high priority on the readability of the resulting programme code. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones. Package: python-freenect Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.3-1~nd15.10+1) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.3-1~nd15.10+1_i386.deb Size: 44760 SHA256: 5d9cdca3186e3bc7d252740f81557ec24dad0f108a65e1c489c115c3ccfdaeae SHA1: 62a975f98fefc70fbbdc54186510bc59e4d7b358 MD5sum: 15d8653484a8185ae8b978cb2c1827a7 Description: library for accessing Kinect device -- Python bindings libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-funcsigs Version: 0.4-2~nd15.10+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~nd15.10+1_all.deb Size: 12744 SHA256: f3025df6434a4c359cfe53955eb74a92a592a09be8b70f70f3755f01eb67512e SHA1: 1b11b6e019660c77416dd8999e329fb19c10f5f1 MD5sum: 14cfa948b446d3b931c69e793c0379a4 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 116 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~nd15.10+1_all.deb Size: 24172 SHA256: ba8d91360e86f607be004384d8c59a7dfc8beb61f2701b6e95438e7ee461bb32 SHA1: b83efe818bf8bfe3537ff1048fa0015693ab9008 MD5sum: 246a3ed96c519863ea9fe49e98e81741 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-future Version: 0.15.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1700 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python2.7, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python-future_0.15.2-1~nd15.10+1_all.deb Size: 336014 SHA256: 5edf2986bcca3aa79f5657633255e5a6f71e2a87229308cf93c051156ab33e3f SHA1: 94b77ca528d8f3b35516769f460301b4566e4bc7 MD5sum: 32f9807f7bfc49d24ff08ba68f9f547f Description: single-source support for Python 3 and 2 - Python 2.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 2.x module. Package: python-future-doc Source: python-future Version: 0.15.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1601 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://python-future.org Priority: optional Section: doc Filename: pool/main/p/python-future/python-future-doc_0.15.2-1~nd15.10+1_all.deb Size: 293358 SHA256: bdc098130dd79cb56dec2189b870777bdddb846b00adf3c49e76d25ef0cc5f79 SHA1: e404faf5d5b84f05238ce3eaac9e4a676fbeb272 MD5sum: 57ac1c16119e2986aac41add03c075ce Description: Clean single-source support for Python 3 and 2 - doc Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the documentation. Package: python-git Version: 2.0.8-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1586 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 0.6.4), 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_2.0.8-1~nd15.10+1_all.deb Size: 291678 SHA256: 5c55b4f0569abee9c663f3f30e1eb2a8b6252f67dece9c4fcf15dbfd8cd11e6b SHA1: 388a85d404e5d3d642a063ebb151ae710e1efcca MD5sum: 020751f525ebd6365a93e34639096f20 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: 2.0.8-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 935 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_2.0.8-1~nd15.10+1_all.deb Size: 123942 SHA256: 32b4fab252710e312924d6d963afb1ddd39c7a561bb43eea3efbadbb54ec4649 SHA1: 0618d69c6c21228dd39154686213ee9488036f6d MD5sum: 0c72032dbd15368eb2f973d9a01c1572 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: 0.6.4-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 230 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_0.6.4-3~nd15.10+1_i386.deb Size: 55176 SHA256: 3b74f397f60f549863a355c7fb1c99fd5cb400ca0494ade358b0a1eac8c7b1f3 SHA1: 3040be0b15092ac77d8b41500b81ba4d527dcb42 MD5sum: 6609387fc71ec149818a723a57db7ed2 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-humanize Version: 0.5.1-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 77 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python-humanize_0.5.1-2~nd15.10+1_all.deb Size: 12946 SHA256: 3d7c717bb267130a36d6808ac4bdbe8833f1f74d8bc53d3b0be052b166d46606 SHA1: 9ad504d41c2b45ba4fedaf3fd00b04bef659b55a MD5sum: 6dd73938eea0d270b0f932b91bf0d7e8 Description: Python Humanize library (Python 2) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 2 version of the package. Package: python-joblib Source: joblib Version: 0.10.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 498 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.10.2-1~nd15.10+1_all.deb Size: 115188 SHA256: 442637cc4d3dd60831b9d40b23f90f8961571df698635124ae560b287e46988d SHA1: f5d397e518dc2e1458470bd9fc264a705c00577d MD5sum: c7e2164087c8a210a3e5052db4f22338 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~nd15.10+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~nd15.10+1_all.deb Size: 21544 SHA256: fdbc10804925030af49b2b325093823221f54faca9f3a137b1f7eb8ceae5c460 SHA1: a5f8e57b7c9ddbc37ab0bdc31a6c7934df0179fe MD5sum: 20f51924eac529dada32197f3ffa4883 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~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1320 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 239152 SHA256: 4e6466766cea76e8f0d4a1b7eb00289fafca51b6e204b009769218b04a9b49ef SHA1: f1a2f8fb690558c74c7e6d47494dc71b519d63a5 MD5sum: f910f423b3d2a63049a037864e6f4656 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-mdp Source: mdp Version: 3.5-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1391 Depends: neurodebian-popularity-contest, python-future, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-pytest, python-scipy, python-libsvm, python-joblib, python-sklearn, python-pp Enhances: python-mvpa2 Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.5-1~nd15.10+1_all.deb Size: 277610 SHA256: 5103169b944bda1f3a2c145bb09e268475d9cdfdd3792945a7f8fb72df0a0b47 SHA1: bd6dda370c354c2115fe947d2a2a3a533ae6887d MD5sum: ddcaeeda108ad0b98dca1d3fd0ae5e23 Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-mne Version: 0.12+dfsg-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9419 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_0.12+dfsg-1~nd15.10+1_all.deb Size: 4431932 SHA256: 6e6c4c76e3e120b02dc782948ab476482c2b9a946fdc07cb3f618e1c5c5707f0 SHA1: 5083a7e7b63bbd1cddf4a8a872a16bc2e10e59a5 MD5sum: 531525ff5973eced4fe819b3102773f5 Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-mpi4py Source: mpi4py Version: 2.0.0-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1530 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python (>= 2.7), python (<< 2.8), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_2.0.0-1~nd15.10+1_i386.deb Size: 322092 SHA256: 2d9002b98ccf4032811aed3a841361da49bd48145f5e40bd21d9579da0d5e7bc SHA1: 5a072ec5ed059b8029fead725205e5db51cb9d31 MD5sum: 34d9d10c745b404067025932888a6e44 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3528 Depends: neurodebian-popularity-contest, python-mpi4py (= 2.0.0-1~nd15.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_2.0.0-1~nd15.10+1_i386.deb Size: 917026 SHA256: 6e30c3b62ca5f6ab8d9d94cb7141d880c39e223cc46330a8f4fad4462fba731d SHA1: 44fce1b0815fc9ac6bca0b72fffaabe300eaed02 MD5sum: 6734c0923c7309dedb33aa1206ddae1b Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 2.0.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 309 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_2.0.0-1~nd15.10+1_all.deb Size: 56284 SHA256: 575cd02b35483b3b30bb0d8cd6416219698cc66c2a991a519939bd97580afd2f SHA1: 016ee2eea289862d8b3078fdfe42d7039ea68947 MD5sum: 82661b3ff32fca538bfb30d6ec7b3b2c Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-mvpa2 Source: pymvpa2 Version: 2.6.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8533 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.6.0-1~nd15.10+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~nd15.10+1_all.deb Size: 5095996 SHA256: 670768f014847f546c1784cfa99a02173a315d2dd55933cafb83de7178b933c4 SHA1: d327cb2a92e869f11ee10b07d5e4f29c1c9fc6b6 MD5sum: 290f6658aa4bfd26aa60d8697975c48a 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 33854 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~nd15.10+1_all.deb Size: 4708928 SHA256: 673b17f1a5598a4566308221c019fdc5ab75f1e41825673fef027db2a1bd2520 SHA1: d28fdbdcee5e64c4416ea2905e41b0b905fea566 MD5sum: f22029d270c8476160b5fbab306008b3 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 133 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), 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~nd15.10+1_i386.deb Size: 50780 SHA256: b975041285b785967697fb889e767e6b3eca9681c5a3c6525410988b71ea4493 SHA1: 772d0e3588bddafb93200034611c64084f27fac8 MD5sum: 12408ff67d1f5364c8092422df9c3fd7 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-nibabel Source: nibabel Version: 2.1.0-1~nd15.10+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~nd15.10+1_all.deb Size: 2161930 SHA256: 332efe21937507a9b850f9030b8eca2b7dd60c8317650af1dee3b9386c662a74 SHA1: 55c3d750a809ce3368f9e3dd3bffa9438b4bec04 MD5sum: cfb4ea33b99310e06bf949d065e38083 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22194 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~nd15.10+1_all.deb Size: 2619944 SHA256: 9399e47a42087c9005bec8c092289c326e024fc6869c9f6c4b9a5ccf62a8c734 SHA1: dd3909412504a5a45602012edf30c621f18b882d MD5sum: b77efe67e091ee438b1afc15d9048d70 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2423 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~nd15.10+1_all.deb Size: 731182 SHA256: 41dadbd520bf0d1dbac82d0f62dae0f5d9076be26e1576826c3113aa63309110 SHA1: 8e7a2126d5b925da9cadce38f984be3aaa06af80 MD5sum: 45975e12a1a20a50f73f7f5a683e807a 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~nd15.10+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~nd15.10+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~nd15.10+1_all.deb Size: 738048 SHA256: aeae126b9df240c81a20bb7b66b0d1419906177ff5db56be0d2ed71e8dbcd95b SHA1: 7b9ccf157d3735af5758d314210882154faff02c MD5sum: a917f76e6d1976f1f7f0142ad00abf9d 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10935 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~nd15.10+1_all.deb Size: 3091004 SHA256: e2eb66fca8b3a35ad70d36e8880d68c8613460dc08f4394f3b4fcc3f3b9867cf SHA1: f05c8adb5761ff419187613c96fb9193f88e3b9f MD5sum: 37ed364e519f7087dbc4e166764eaed3 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2725 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), 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~nd15.10+1_i386.deb Size: 571888 SHA256: 277f03a403103161818de11d9f9554cf5bc0566c767f93c99b507d8494b8c77d SHA1: f36a19e51b146bcb6287e85e8fc7834ee47c8d50 MD5sum: 0d1955239da6f084faeddd558ed47137 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3165 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.0+git26-gf8d3149-2~nd15.10+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~nd15.10+1_i386.deb Size: 450798 SHA256: 369051adf116af2934bbb25a0064fcc6d364d8d257df222862c0a18edb0acb8c SHA1: af4c19f2649dad670e773eff6f15d9236dfd0268 MD5sum: f88a018d4e76baf210889ac32795c15b 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: 0.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8454 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 Recommends: ipython, python-nose, graphviz, python-xvfbwrapper, mayavi2 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_0.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 1420158 SHA256: 0fd545b3427945dc7839ec01306a5ae9e3b70c82eb6cc4f37a75000c4aea46f1 SHA1: 782bcf359a296737d6f9be924ae3175012530d13 MD5sum: c0507e321514629faf892f85d10c03f8 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: 0.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23460 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_0.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 8916428 SHA256: 3489524c3e0479ec4f912e3ce85e85d781a858454c95a5f4d8c33ecef1893741 SHA1: a5c883b21262b7657c78ca5478787e48304505a6 MD5sum: a10f5e7314b95618b0a4c85382a614de 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: 0.6+git15-g4951606-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9379 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_0.6+git15-g4951606-1~nd15.10+1_all.deb Size: 2561372 SHA256: 4814136697d52bf61b947d96e3fed2a01e3ae4f0a426e23bf78fbf3fe2589592 SHA1: c0f327f8b064dfa2bba0811b68bb88f4dc51e5c8 MD5sum: b34010f28df79815355d1275496ffd63 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: 0.6+git15-g4951606-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7795 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_0.6+git15-g4951606-1~nd15.10+1_all.deb Size: 5752562 SHA256: dadf27f4bd3df92a037e46b29831fbc9119252bdb8db226a530f1c357228f95e SHA1: 9eb10d3f3d87ef8cce7fe419c7f7b3bfd62a37b7 MD5sum: 85b0007fc84cfdd8895ab32de577ed94 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-nosexcover Source: nosexcover Version: 1.0.10-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 30 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python-nosexcover_1.0.10-2~nd15.10+1_all.deb Size: 5230 SHA256: 2dadf08af4cee9bb738c3d6636c942ef43be5ebd00f6f4e0fad4d9ecc51be41a SHA1: 4614ae0dd8c36cc30029b93d17292b087663dcca MD5sum: abfd387267deac0874d82e13f31dcf49 Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 455 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 124018 SHA256: f3fcdc4dcba561bddd95cefc05975084cb0cfc3d8a5785eb859b0530fb97c529 SHA1: 5a8996de257a438c3db07d675d0a5c9ff31b2a57 MD5sum: 3d484be97b6e7944ba3eaf2091820e9f 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: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numexpr (= 2.4.3-1~nd15.04+1+nd15.10+1), python-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 94232 SHA256: d1f838f2350cb5a0f64889c0d682fb680cbe23de1144d1c40b035d817bdc4b76 SHA1: 7bd10c62997795205b70de88ea485a64ff70bb8d MD5sum: e928442db4ff92dc380e95c20ad2559e 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1328 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~nd15.10+1_all.deb Size: 199904 SHA256: 022566c9685732d3a67cca3cbd7fbb63108d380aab9be04547e7cd6234524b58 SHA1: f55c941767c3b35f16f44eae74ea5f6224c0bc2c MD5sum: 8b6b566df08a8783a1c727dde3616b3c 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-packaging Version: 16.2-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, python-pyparsing, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://pypi.python.org/pypi/packaging Priority: optional Section: python Filename: pool/main/p/python-packaging/python-packaging_16.2-2~nd15.10+1_all.deb Size: 17092 SHA256: 019ac454d760ca392d3afcb561a34cc41b8a041edd89102c2e48413ebe4af226 SHA1: b7af65bb7ec5a820548d9b1d26d94a06730abc59 MD5sum: 0640ebc0e8bafffbd5aec9a1d07445d5 Description: core utilities for python packages These core utilities currently consist of: - Version Handling (PEP 440) - Dependency Specification (PEP 440) Package: python-pandas Source: pandas Version: 0.19.0+git14-ga40e185-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25158 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.19.0+git14-ga40e185-1~nd15.10+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_0.19.0+git14-ga40e185-1~nd15.10+1_all.deb Size: 2588340 SHA256: c0b5feff2d9eff5fc560fe2b44a351faf51a9e953f0db546630ca6ae29a1d80f SHA1: 078ffaf967fe2d0aa1446a41ed0da6b85c50574c MD5sum: 1ca6fb704fd1e7e1b846a1b56d726f6f 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: 0.19.0+git14-ga40e185-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 60220 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_0.19.0+git14-ga40e185-1~nd15.10+1_all.deb Size: 10271464 SHA256: 588f032e2183d5debe9bad9c25f653e2ccd04b49a1362b87425c15057350305f SHA1: 2ea7d7272d1d582c94c32a2d1f81af3210e01213 MD5sum: 2d9a0d915af1f2154f36143e70050373 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.19.0+git14-ga40e185-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7878 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), 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_0.19.0+git14-ga40e185-1~nd15.10+1_i386.deb Size: 1753718 SHA256: 1169fe8cdf7058f74d4b772d894fb693fd9f97db983760c47bb4f379995342db SHA1: a870217a176202775e50a6746b89eee90841afe8 MD5sum: c2e4e6dd7b580362a0fae927b11e4f05 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 783 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_0.4.1-1~nd15.10+1_all.deb Size: 171530 SHA256: a138d37607bd61b94c05562c2d744774ffa999352c95691b8ce62b2cf634b8a2 SHA1: 73f22404099531ad93c877a47f2aa300e084408c MD5sum: 5b604eb576a5aa546771d5c12481cd8b 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1374 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_0.4.1-1~nd15.10+1_all.deb Size: 358758 SHA256: f36a39459d9124d8b720d8cfef0d823df23253669f24e419b44a04764be872b5 SHA1: 4c359188f6cbd2bde22fa7500ffd05627559f6ec MD5sum: b2913de0d784a00801ac9f4a8695f524 Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 758 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 82530 SHA256: d92ec2025469219732229d52024021a91ed1be44b4d3a0c968ee39adb4506714 SHA1: cf2cf43bae1aa11ba91b4558b50a3e046aafe00c MD5sum: 7339ae7d62fb0b93e77bfd92362e30a3 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-py Version: 1.4.30-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 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_1.4.30-1~nd15.04+1+nd15.10+1_all.deb Size: 66700 SHA256: 8ca1f393f248519edd0f52de3694de8e511238d2032c6dc0fe1242261908ebf9 SHA1: 7cb7aea10bd5fb3db2aec1ac0d89804294b53809 MD5sum: cfdcd004d5ef98a38394886c5236de3b 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 105 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~nd15.10+1_all.deb Size: 20244 SHA256: 939711ca56797e16ad95b1127c2ef33121e3ac15b4bc6600d85ac73760053e63 SHA1: 149c28a94f0fe404ffb1ee62446245f89377cea8 MD5sum: 3455aa07d52f4a663345381f7dad7d41 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1855 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-1~nd15.10+1_all.deb Size: 1072174 SHA256: 7ca014a30a8f6aa7460208c27040908ac250fa62cfef263f57a3f76ea4cecd6b SHA1: ce6b08e11a031147000332d45b32e161787f7e63 MD5sum: ba4d848cc1b06a4ed1518e8a2b26f196 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1416 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode1, 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 277152 SHA256: 05119be8089703a2a7280cdc5063a511bb5a15f22af7835bba9168e9b378f48d SHA1: bb4c84b972591f4f8fcadfecc09dc533b5c846d3 MD5sum: a7710e8a405ff3138656d1ed8545da9b 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 819464 SHA256: 8c17d1434c8e1da5e583f98d1a6cd3f9861767295c63a8f97dd1c7cb9ef33efa SHA1: 19d1be20a9ac8c71cb8ff3383a695e9f56f75db4 MD5sum: 45bc27c8ee6f2a8e368cce8ed3fb6f8b 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 390 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd15.10+1_i386.deb Size: 74928 SHA256: ff1e821f3714c28938dee229e2bc8dbc55a83d5b0f1ec8343ef8a17d379f73ca SHA1: ecaa233d624420b9f295654f509dbae6e759e93b MD5sum: 6204dd1a79e03d5078d9ac34e4e96fd9 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 245 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd15.10+1), python-dbg, libc6 (>= 2.4), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd15.10+1_i386.deb Size: 103484 SHA256: b5160721974850d89951c9c570a2d216408f33fc4109712603a5f2b6c8e76e4a SHA1: 60ea4e313496f535f2ec35560616608c785dbe4b MD5sum: f10823bf219baff558331d8ae64b25ae 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. Package: python-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 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~nd15.10+1_all.deb Size: 67896 SHA256: 2acd013576144f006341615eef2415d1ca7f53e9b47fbf3450146fe3e39cc153 SHA1: 5dad8f6f09414f6ae44d41d5c17f76a652053031 MD5sum: a225af8142daf2bc8644094b2de0a3ca 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-pymc Source: pymc Version: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2668 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.11), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, python-scipy, python-matplotlib, python-nose Recommends: python-tables Suggests: python-pydot, ipython Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: python Filename: pool/main/p/pymc/python-pymc_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 527858 SHA256: eb622e1174beb55874203fce2ef81473fa31256edf7d7f80b698c1c30915f8c1 SHA1: 3c0afd5be786eefda36c121e7c1d5c2d43927303 MD5sum: e23a044de37f188e79aa28cf68d90fc6 Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. Package: python-pymc-doc Source: pymc Version: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1894 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: doc Filename: pool/main/p/pymc/python-pymc-doc_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 839798 SHA256: d3aaaba642f681a3628813694c80f363c2d5227e847276d89b5b73aa6523ce59 SHA1: ce8e7a60b397a3afb6fa64bd4a348944415c646e MD5sum: 36d84dc5b94e1bce656a0a626657afa2 Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. . This package provides the documentation in HTML format. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 818 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 122702 SHA256: 907de30bc8e14386b8c39219e5b930c49fc5085c48ba1de63defc033de919dd0 SHA1: 2349a0f46e32d4b1fa4700085e6ed4860d1dd2ad MD5sum: b84b793301926a44fe0ad806f70a95e8 Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pytest Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 464 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python, 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_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 102354 SHA256: 2cbc118fdf6a5b9ab7322c2b80519598fff9f8fcb0db2e36193067fa0c133ac2 SHA1: 2cc0c7470f6d1bc7274e365c8630ee7fe46fe644 MD5sum: 56aa0c33033979d21e014df680763597 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. Package: python-pytest-doc Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2973 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_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 403654 SHA256: 6dfdf797382968cc3e3b30e7b20d0ec16e207433a315afb8038cd6772bdd333a SHA1: 9acaa57e48d5edc8d703fdec146d409ebb3cbd75 MD5sum: b5e67852cc706f273cbd4f3446a24658 Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 61 Depends: neurodebian-popularity-contest, python-pytest, python-werkzeug (>= 0.10), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python-pytest-localserver_0.3.4-2~nd15.04+1+nd15.10+1_all.deb Size: 19272 SHA256: 6fb68ebb08da4df6b381bb489a6a9cfd8014d46ae4026b34f4e84df9c819d4ca SHA1: 812f04249c0e18ed99efe15908d30b12f3774220 MD5sum: ab59e0d9c1c17c190d6046db0b63fe4c Description: py.test plugin to test server connections locally (Python 2) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 2. Package: python-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python-pytest, python-tornado, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python-pytest-tornado_0.4.4-1~nd15.04+1+nd15.10+1_all.deb Size: 5776 SHA256: dccd6e64154c95e64e7d74b12739a27460adbac7bc69a586c1936d002fb0f1d6 SHA1: 7fb37482492de05163754654ea174c32badc6900 MD5sum: 1e34a857279804ffc8ea8e9377cd5104 Description: py.test plugin to test Tornado applications pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 2 code. Package: python-scikits-learn Source: scikit-learn Version: 0.18-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 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_0.18-3~nd15.10+1_all.deb Size: 69590 SHA256: dc8839da624d72f914dd26fcc3d62e27e5caf826fbeba5b3ad396c10ce78eea9 SHA1: b4e811e1cfd6ebb8ef39735e933d3e497a534cc2 MD5sum: ff5caa8004fa9c9a88cc608c3f28a318 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-scrapy Version: 1.0.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 987 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-lxml, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python, python-openssl, python-service-identity, python-six, python-twisted, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: ipython, python-django, python-guppy, python-imaging, python-mysqldb, python-pygments, python-simplejson | python (>= 2.6) Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.3-1~nd15.10+1_all.deb Size: 175920 SHA256: 6027c4f2a56dcb383c813a0ed3c15290bc519842e2af25e6fd3bc50d910f3c40 SHA1: 6aa8c65767453c69384cc1a24c93a63fc685a929 MD5sum: da7767fe5790c07f9d1edf49ae0e49cd Description: Python web scraping and crawling framework Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy script and modules. Package: python-scrapy-doc Source: python-scrapy Version: 1.0.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7118 Depends: neurodebian-popularity-contest Recommends: libjs-jquery, libjs-underscore Homepage: http://scrapy.org/ Priority: optional Section: doc Filename: pool/main/p/python-scrapy/python-scrapy-doc_1.0.3-1~nd15.10+1_all.deb Size: 1543576 SHA256: 047e3f3e4c8555716b17dbbda247b6d0a994b8e25b22f4b5eef74a950ddfb21b SHA1: 5cc3162fba6761c8cda45eb9b11b54cebcdf993b MD5sum: 9bc9a5b6e535e640c31fd340a8f04a53 Description: Python web scraping and crawling framework documentation Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy documentation in HTML format. Package: python-seaborn Source: seaborn Version: 0.7.1-2~nd15.10+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~nd15.10+1_all.deb Size: 128280 SHA256: a3ade7c10a3dc5e3fb05691052ede3140878ca7279aa2af91bf7f71a35c42534 SHA1: 474ba55efc485ad72dbefa4b9cb49a1eebeb0b71 MD5sum: 2b5f4b14469fc9e87e8aeab04dacde47 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-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python-setuptools-scm_1.8.0-1~bpo8+1~nd15.10+1_all.deb Size: 10146 SHA256: ec91e0a08e4d0b861b1b7fc19a4497c1b12bbb3d574790c695786669781c8618 SHA1: d09974942a1c94a2e046bed77aeeecd971ddf406 MD5sum: d16786e7b7290a632e009e0f2be4bf91 Description: blessed package to manage your versions by scm tags for Python 2 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 2. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1+nd15.10+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~nd15.04+1+nd15.10+1_all.deb Size: 11100 SHA256: ed8ef878a5acf90ddaca8ef5a9a823e37c018b6cdbaa188d317525382d85a317 SHA1: 7e1d6d6c8f09db6bb829bc8c1626a4cca0f927e6 MD5sum: 234ce848817dcb32bea848057a866628 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~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 45 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~nd15.04+1+nd15.10+1_all.deb Size: 11348 SHA256: 1710f5fa454425b0aa703d0ade438483d0bf57eeb1afe7d8997a70efe8cc5508 SHA1: b8f2871cb9c636494a38de1ef65cdeddb8531a47 MD5sum: 93f40a89beabde7e2ae3bda5db966f4c 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: 0.18-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6545 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.18-3~nd15.10+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_0.18-3~nd15.10+1_all.deb Size: 1382798 SHA256: d372024a871eebbbd367d5c1db118114f48c428a761b3fe26a198afa822f9bc9 SHA1: 768044f265d7f52a84abb3303e9f618947a56b52 MD5sum: f7dd2ea51314e76fb8675ed682e246ba 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: 0.18-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28216 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_0.18-3~nd15.10+1_all.deb Size: 4764596 SHA256: 668c796b98cb9f76f87c54c44b6d84ae3f3c035ac3b785031890ff4aae3665bb SHA1: 0da5c2be5a97d0d2be4e2662faa1c49d927de711 MD5sum: 515f741432c1ea6ccf916803b290cf9a 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: 0.18-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6239 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), python-numpy (>= 1:1.8.0), 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_0.18-3~nd15.10+1_i386.deb Size: 1278304 SHA256: 6d5eac6a47b7ebd01c9c93a949bda3140586f0d8e97f42362c54fd3c40fc069e SHA1: 99604c63d20e38a70b952e5b4f4fc98804160f1c MD5sum: 55650b22ffc246351a03171531fe4b63 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: 0.9.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 91 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_0.9.0-3~nd15.10+1_all.deb Size: 20272 SHA256: b87c4e2f168bd32fdd0dab535152c36c43e665c6f2e918d707822bb3afaca3c9 SHA1: 0c6c1a540f6609d7668bd1a72f134cd7a4e2db36 MD5sum: 6776fc1b2bb10b669afcab4401345ea5 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-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 360 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python-sphinx-rtd-theme_0.1.8-1~nd15.04+1+nd15.10+1_all.deb Size: 117260 SHA256: b070fc77ec214ebeaa7f4fd98275a75bf81ae7d52efd8ea18df62e9aee4df17f SHA1: 613816e175a7cf7868edf04b76f55b92684316d9 MD5sum: c83aed789938169848a09c179ddfdd54 Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-spykeutils Source: spykeutils Version: 0.4.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2076 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-scipy, python-quantities, python-neo (>= 0.2.1), python-nose, python-sphinx Recommends: python-guidata, python-guiqwt, python-tables, libjs-jquery, libjs-underscore, python-sklearn (>= 0.11), python-joblib (>= 0.4.5) Provides: python2.7-spykeutils Homepage: https://github.com/rproepp/spykeutils Priority: extra Section: python Filename: pool/main/s/spykeutils/python-spykeutils_0.4.3-1~nd15.10+1_all.deb Size: 309612 SHA256: a50e224599a6bc0426400f243ba36adfde729f0033b769b4f9781c93de7f63b8 SHA1: cf80b9ebe001580f48fd5407c927dc9b325bfd74 MD5sum: 070cdee197ca8f3b29300efa8906ee00 Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16001 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-statsmodels-lib (>= 0.8.0~rc1+git43-g1ac3f11-1~nd15.10+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~nd15.10+1_all.deb Size: 3344448 SHA256: d86fd1a39100ac6e98899e1698f943669f5b4b1ea110ee96361c416b38586697 SHA1: e70b3c16fc85b5971ce4dad24e99bbbe6f0cc7a9 MD5sum: 46520baf10dd86c1b23641010328e94a 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 51142 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~nd15.10+1_all.deb Size: 8398790 SHA256: ae57c5a0cb37986a831a28dc94c481501abee0a70e8b01d350084267bbcd0312 SHA1: f39a3575ceaed56456dfeba2b5d96b0615bc2f1a MD5sum: d1c57f6ee4ffe683b96e100c6dd2816b 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1501 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.8.0~rc1+git43-g1ac3f11-1~nd15.10+1_i386.deb Size: 209416 SHA256: 37eb30fe6440b98a3538af6a2533881aaa33050ff53c511b8a94fa342a6f7ad6 SHA1: 7355f77425f6d0c2beed47e5046c47776d7cb98e MD5sum: 58b1229c53010a8cf4c851bd60541eae Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.15.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1426 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.7), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), 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_0.15.3-1~nd15.10+1_i386.deb Size: 506420 SHA256: 0eab7d885c549f0becba4d94c68c5c7426bcb2b48397dbdbde171e46f1dee12e SHA1: c411c5851bdb5a0411ae10a80f9a1ecccfe73529 MD5sum: c78c6ff539818d9fb9221a172b403e79 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: 0.6-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 192 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_0.6-1~nd15.10+1_all.deb Size: 41648 SHA256: d9e0e9f82b01d42aaec80b8ce6fa375488d157dfc09ad2708664e15b70bd6b44 SHA1: 140d45cd9ae676ca9a844dec817c69634a3d5de9 MD5sum: 2773633610a43552825d0e747ad9c8cd 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: 4.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 138 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_4.4.1-1~nd15.10+1_all.deb Size: 35330 SHA256: 327752e886d4df6215701987438f41de522e26caf2df0f277626326b74b21289 SHA1: 6384c635ab38341d2b4ec3a3ebb2dde64bdfdd3a MD5sum: 0876411eb702a39c68f5d724cc03c312 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~nd15.10+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~nd15.10+1_all.deb Size: 65322 SHA256: d60431eb0b2861cae214aa19f4edc4d73e346e1cfd9ae18dcd63420515a91e7e SHA1: 26e78d376a837c3bc60acf08f4620f6fc5c8083c MD5sum: bb2502b173d1e59bcd236ec4e5210eb0 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 251 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~nd15.10+1_all.deb Size: 65750 SHA256: f6daaca92634f908c6bf1775f769f9d53e65cbecd64e39c52ebf1dbfdb6bdbec SHA1: 9e0bf19f2a3dcc5f80a8c831b36d84e7d545bb6f MD5sum: 2e59daa990ac2c90f88c48262b05d7a8 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 158 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six, 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~nd15.10+1_all.deb Size: 43610 SHA256: b3bcfda50732b3bee3e76f6acf78fdd1c6605c3ddd6aba27d743156a4aa26505 SHA1: 2f2c645dc199a7e81db6cf315406741b2d3408e6 MD5sum: af63ff74f9cdbe7359d7047dbd7b1ddf 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~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 489 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.04+1+nd15.10+1_i386.deb Size: 86994 SHA256: 28d983057e0d3fa7ec7ae2a04816286ef3b960546dc015278207dd7bb3834cdb SHA1: f5b529940ee9d89b12c21a68ebe0afb0bcf16382 MD5sum: bd4c30a948c7f6d733252f0384a56aae Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python-w3lib Version: 1.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, python-six (>= 1.6.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python-w3lib_1.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 14178 SHA256: b56e06fe8a1e6fee6777e4018bc7d636d11c63da12365bffd36a17748229316a SHA1: fa42311dce6460190b0f53e9732332f27c700ce3 MD5sum: e1e6355c15ee506303fbb9f8bf538e8a Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-jquery Recommends: python-simplejson | python (>= 2.6), python-openssl, python-pyinotify Suggests: ipython, python-genshi, python-pkg-resources, python-lxml, python-greenlet, python-redis, python-pylibmc | python-memcache, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python-werkzeug_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 163506 SHA256: 36413e807ef6c8a35a35370ee02139b6481335228d5ee8309984b97dc5c2eeb5 SHA1: 2de31195fc04e0452fa9d41b72d9d1a21778dd6f MD5sum: 6d06077dd2e41bdaaf0e3472b80df99c Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python-werkzeug-doc Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2697 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Conflicts: python-werkzeug (<< 0.9.3+dfsg-2) Replaces: python-werkzeug (<< 0.9.3+dfsg-2) Homepage: http://werkzeug.pocoo.org/ Priority: extra Section: doc Filename: pool/main/p/python-werkzeug/python-werkzeug-doc_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 880818 SHA256: 057a3dc0b856ac6387131a0f8d8693f4143a32e93ad22189f9729f10fda2d9f2 SHA1: 751bb017a92beebba4ce4863fbb52f88311dc916 MD5sum: 8a23035e9376f2d33827b4e4c8da721e Description: documentation for the werkzeug Python library Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd15.10+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~nd15.10+1_all.deb Size: 20982 SHA256: 6dc4d4d04dc613bfdd5328e03371b6ba55b5706fbc955288467046d04c02decd SHA1: d8ea2582684e2565160d5cbc828b94728f977ef0 MD5sum: c3617eb5f75008261ea0730237b35388 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~nd15.10+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~nd15.10+1_all.deb Size: 58120 SHA256: 9b2751cec2482b90e99094662b435c40970fe7ae97799e91f2adedca837ea3b9 SHA1: 1c51461e77d454e131207be305c803b300935348 MD5sum: 2c7e6aa73e31c38dce86103189ff66f5 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-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 777 Depends: neurodebian-popularity-contest, python3, python3-lxml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd15.04+1+nd15.10+1_all.deb Size: 81936 SHA256: 0044b925f2a4b2936b99fa8d876ef80b47a556182f1a12f302983846a4b1f90f SHA1: ae77286eb819a6f599f442b8ec79fecaceaf4678 MD5sum: de0adeb3c0b211c74f5274dd3ae94e69 Description: Citation Style Language (CSL) processor for Python3 Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python 3 modules and the CLI tool csl_unsorted. Package: python3-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python3-contextlib2_0.4.0-3~nd15.10+1_all.deb Size: 8736 SHA256: e113a4bcb9b97cc6847f1b6e3ede3a211f1c15b2fbf0300f79211de43f32f0cf SHA1: 709296fa01004b17282e9539f49bfd307a81e9d1 MD5sum: 8f47d6b47f71a7dc0979953dd42e7478 Description: Backport and enhancements for the contextlib module - Python 3.x contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 3.x module. Package: python3-duecredit Source: duecredit Version: 0.5.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 236 Depends: neurodebian-popularity-contest, python3-citeproc, python3-requests, python3-six, python3.5, 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~nd15.10+1_all.deb Size: 50082 SHA256: f85ec1757b4d405e1c47fb0ff1c6b14899b29d425b037bbd19276429fda2db0f SHA1: 06adedfafbb583dea16ce79cb2251c1a6dd7557a MD5sum: d93021a31abb6fb0d2cc57baaf3f4316 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~nd15.10+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~nd15.10+1_all.deb Size: 12834 SHA256: 256e4ce90b1b4077b813b17522685117f04bdb3c2eb1eb38fa5a577f2945912f SHA1: 701559eb59dd1cdf6193dacc8b1d51283640de9b MD5sum: 486add510b38e4817f35471ec101125c 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-future Source: python-future Version: 0.15.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1650 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python3.5, python3:any (>= 3.3.2-2~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python3-future_0.15.2-1~nd15.10+1_all.deb Size: 333842 SHA256: ba406507a688c80cfdc878e818080979a74c7e20f8c3acb9ff7e91121f95534d SHA1: 6a7bef47ed008b663f078ca887361a40b4168856 MD5sum: 61e3c39728abee8dc61eea69866e893d Description: Clean single-source support for Python 3 and 2 - Python 3.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 3.x module. Package: python3-git Source: python-git Version: 2.0.8-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1584 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 0.6.4), 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_2.0.8-1~nd15.10+1_all.deb Size: 291642 SHA256: 3524c04c2d9507e9b57c5ddf38e347dc0b7ec4e479360da0211f60768a60f7b6 SHA1: 814c5e368bc1f0b6cb2fbbee1b8edbd04f6d375b MD5sum: 0f31ceb3c82cfff2fe6946690db05ee7 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: 0.6.4-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 252 Depends: neurodebian-popularity-contest, python-smmap, python3 (<< 3.6), python3 (>= 3.4~), python3-smmap, libc6 (>= 2.4) Provides: python3.4-gitdb, python3.5-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python3-gitdb_0.6.4-3~nd15.10+1_i386.deb Size: 55552 SHA256: 9ec1368e3b2ed0f32ac79156780652c1a3aeb24fb75dad9ecd9bdecce8be5e8d SHA1: 146e8150a1f14451a7950e57eaa74e5eb9cae631 MD5sum: 131040911fb35f8049677f27e0ec92d4 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-humanize Source: python-humanize Version: 0.5.1-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python3-humanize_0.5.1-2~nd15.10+1_all.deb Size: 12680 SHA256: e9e699f17f354de3e4d7baced43b41a7d582fccd6cc1ad892c9e137486c6773f SHA1: 3f1ce33104fe52071cb463e036474e8e1e671c66 MD5sum: ae611130a59c7598a5c3beb5abb33e62 Description: Python Humanize library (Python 3) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 3 version of the package. Package: python3-joblib Source: joblib Version: 0.10.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 487 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.10.2-1~nd15.10+1_all.deb Size: 111810 SHA256: ea831f108eb5b54c36026e50edd5f29adf4f7c5e974489d9d203e64fded97e92 SHA1: 5eba1244c681cb36ab32717362fca5768d070955 MD5sum: 9272246109f618e9049bacc7d04fb377 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~nd15.10+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~nd15.10+1_all.deb Size: 21616 SHA256: bb9e5a3d1de141af7d46fe2e5b9e6f4ed91d9f6e422fa1e7140cbd53962051d0 SHA1: c8dc3689d5e304b17748f00f8a5330a583b8969f MD5sum: 2c657b90b96c683c75a6eb51165df168 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~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1448 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), python3-numpy, python3-pbr, libc6 (>= 2.4) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 250312 SHA256: 6338c7a368c8d23d9ba86c75f9b30c0426a1888ee13c1c3ced448021752a5468 SHA1: 622a41b0ed72b283b7623af6eeda65652c4aade4 MD5sum: fee8f1bcb10d6b5e1969b7491d507b44 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-mdp Source: mdp Version: 3.5-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1387 Depends: neurodebian-popularity-contest, python3-future, python3-numpy, python3:any (>= 3.3.2-2~), python-numpy, python-future Recommends: python3-pytest, python3-scipy, python3-joblib, python3-sklearn Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.5-1~nd15.10+1_all.deb Size: 275328 SHA256: e30052c0042964fd3c2a8cac115de352dd0c4b1247bd77b78bda1fb4bffcbdbc SHA1: 6d22803965940f5d6c6bc8e27402044aa6f9e61e MD5sum: 845cbf422a68390e7055f0407b916bd1 Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 3. Package: python3-mpi4py Source: mpi4py Version: 2.0.0-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2813 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python3 (<< 3.6), python3 (>= 3.4~) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_2.0.0-1~nd15.10+1_i386.deb Size: 414976 SHA256: a2bd23abd82b027be4cc7530272e229e443fc60f67f2c329bdedfdb9e9c6997c SHA1: 72955811a3c65b037366767f9ef73655eb082973 MD5sum: d8368b52de293eff4c6ec5a453f15c6f Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8121 Depends: neurodebian-popularity-contest, python3-mpi4py (= 2.0.0-1~nd15.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_2.0.0-1~nd15.10+1_i386.deb Size: 1885212 SHA256: 47a1b9a82712d4bf6c8d1536df9a04862f57ab8bb91de61733f3a197f36fb02b SHA1: bd76be6d1a1a8b950cc0f992344b88559ff50485 MD5sum: 1abfbe3d1ef2055f925143e1a91b8dec Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python3-nibabel Source: nibabel Version: 2.1.0-1~nd15.10+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~nd15.10+1_all.deb Size: 2154552 SHA256: 5ee027ff2750f8f22979292b060066981fdcb2acc36949cca68c043e79b9d034 SHA1: 0f123c894723b36850197aa3bf9f1e54e39f31bc MD5sum: 69383d55d2a9b8730b2d75c8304311fa 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2208 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~nd15.10+1_all.deb Size: 687022 SHA256: 3cff6fb1d268f5a7cde4f3c51693d8b8188087513964a20407f438f07c44c1b6 SHA1: 02d4b0ad23cdca89806e659e92553d0fbc914b07 MD5sum: 722de17432140570c5dfd040a4c6390e 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-nosexcover Source: nosexcover Version: 1.0.10-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, python3-coverage, python3-nose, python3:any (>= 3.3.2-2~), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python3-nosexcover_1.0.10-2~nd15.10+1_all.deb Size: 5194 SHA256: f879fea14e9713873a34f9b08de841eabe3c73d4e83be37c696da27ac3041362 SHA1: 525ec098eb6e51dba33a4c65fbc01b589a0450d9 MD5sum: b8ce14dd093dc5eb879a44a9a859c608 Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python3-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 745 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 118474 SHA256: 89479d014453d12d60b8d49858032fc1d95ebfca9276419f648c021d481221ca SHA1: 1171a5ecfb14a53cc349267b73a8444535f325b2 MD5sum: 83058748730eb8c974be44756a2f04e0 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: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 631 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.4.3-1~nd15.04+1+nd15.10+1), python3-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 94602 SHA256: 63153a71c8d70e8e7ce9dd07132bde42472e81ff60e7024591d2d0fc77d8028a SHA1: 0915e9ad837c7c3fd342f5de2d6d369ee0a7c460 MD5sum: 8bf8e16436f0bd47f55188986a797ce5 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1320 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~nd15.10+1_all.deb Size: 198452 SHA256: c7d28defe9e7065752835ede5cefa87e0005bfb1446cfb5ae4228deabbae8903 SHA1: 0693ab6fa3c2c4f25ddec6b2cd5ed816392f1560 MD5sum: ebebeb99d67227172b1122db3bf0885a 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-packaging Source: python-packaging Version: 16.2-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, python3-pyparsing, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://pypi.python.org/pypi/packaging Priority: optional Section: python Filename: pool/main/p/python-packaging/python3-packaging_16.2-2~nd15.10+1_all.deb Size: 17174 SHA256: 4938cdb28a158add3a7375c47cacf1813912991bc17447ae6691c58f5e164cb7 SHA1: 2a0a4c0067da6feee57a89301547a24b7ffd1913 MD5sum: 6e48a9f6850fdb30f3e8cd3b0da1f4e5 Description: core utilities for python packages These core utilities currently consist of: - Version Handling (PEP 440) - Dependency Specification (PEP 440) Package: python3-pandas Source: pandas Version: 0.19.0+git14-ga40e185-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25126 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.19.0+git14-ga40e185-1~nd15.10+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_0.19.0+git14-ga40e185-1~nd15.10+1_all.deb Size: 2584738 SHA256: 1d1b66bba739e4488f105d8720f5b01767c12166a791c1ac619d9b4e236894ca SHA1: 3d9a93a709143f7d98ecf8dbeca2d561e6344e33 MD5sum: 565c9b454418406176eee6c4912fc282 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: 0.19.0+git14-ga40e185-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 15527 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.19.0+git14-ga40e185-1~nd15.10+1_i386.deb Size: 2671738 SHA256: 612aaefda44a0670bd1892ff5fbd286f1f625b5003004a4a1239f841d4a23a15 SHA1: d4d0754070bed1b8960e927984363bfb402b4569 MD5sum: dabeff73fad80a8dc96a3538a7c558ef 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 780 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_0.4.1-1~nd15.10+1_all.deb Size: 171132 SHA256: 374bd7eb78069fdf1b1ef6175fb3886bbde3a55699f80d7c4861065f4f137660 SHA1: 0e6fba8b23f0b29d7f38b11bc2f2665e9ca05874 MD5sum: b42c7c14930ed791f1a1cc02c5e43f0b 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-py Source: python-py Version: 1.4.30-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 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_1.4.30-1~nd15.04+1+nd15.10+1_all.deb Size: 66784 SHA256: 44c24c7e7d14ae7ebbc777d138a0255b99c2033e47da0535c186df618af32d68 SHA1: 152c58c9c5f05613b29b29d17ac6479e3c5c8c6e MD5sum: 07f66b4226d0cc61a272c82e8bdbddd1 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 105 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~nd15.10+1_all.deb Size: 20320 SHA256: ea5e29c81e0ff7ed9c7b709cbf612b666c35e127ea2b55d45712c3ef86397848 SHA1: 9697be33e4d25641f59212265a8d24fe076144c2 MD5sum: a3e9f828f9be1f9509022b682ccb5a20 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 446 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.4), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd15.10+1_i386.deb Size: 74978 SHA256: eedb101c61268dfcb94f8775a1db1718a00b1ecabdfbe99bd448d056d09302a0 SHA1: ecc4a5fd93f6eb9f6d35a887c001b71cc9cd1e19 MD5sum: 5441c14c1fe8301cd21214e0dd932b9b 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~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 479 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd15.10+1), python3-dbg, libc6 (>= 2.4), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd15.10+1_i386.deb Size: 153524 SHA256: f37c59652dab963bdaace2ad2725c986f0b84c283652df5f3e57bf92760ce6ab SHA1: f22d8ee88a81a273bd0e593b3f87290fd0d61c6c MD5sum: e3b4671324e11a8d32e58f97fbda160f 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. Package: python3-pytest Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 465 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3, python3:any (>= 3.3.2-2~) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 102460 SHA256: 424de9f1c79e3e22df9e310ed6b7e4b526f15964fa9e281c9f32eee34788de84 SHA1: 91180a99a3dce1a700c7ee432de886252e59404c MD5sum: 08dda5d2bc3625ffa1d13b9a5dbfc23f 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 py3.test script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 61 Depends: neurodebian-popularity-contest, python3-pytest, python3-werkzeug (>= 0.10), python3:any (>= 3.3.2-2~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python3-pytest-localserver_0.3.4-2~nd15.04+1+nd15.10+1_all.deb Size: 19344 SHA256: 8fd2067e092f0556686cd15f9ce8feee1eec3fd1ea4751ae32af05ee3c18843b SHA1: 1f420dc2c6c5b2d515c152a36a51820d6cf3c49b MD5sum: 6b6ba11341c3a7feae080e053f21600b Description: py.test plugin to test server connections locally (Python 3) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 3. Package: python3-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python3-pytest, python3-tornado, python3:any (>= 3.3.2-2~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python3-pytest-tornado_0.4.4-1~nd15.04+1+nd15.10+1_all.deb Size: 5856 SHA256: c1a5806687563e8096815a04fcbcd1c7679d9b656371bb71687d52948d63a7ae SHA1: 0cae286527ca4e4545f1dd84ea72ed3009e126df MD5sum: 79cf2d318bb1d9be926c8594e6fec5d7 Description: py.test plugin to test Tornado applications (Python 3) pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 3 code. Package: python3-seaborn Source: seaborn Version: 0.7.1-2~nd15.10+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~nd15.10+1_all.deb Size: 128314 SHA256: d41947264f46b2e3822864bcd9b703735d6951295659668c9858eab0e857b695 SHA1: dfe56512121f35b871deb0098e6c398759b1efc3 MD5sum: 0d06cf0b1cc3c012f603bbac3710935a 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-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: neurodebian-popularity-contest Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python3-setuptools-scm_1.8.0-1~bpo8+1~nd15.10+1_all.deb Size: 10196 SHA256: aec343c6c126505a2ca8d49aba715d7bf71b8926da9b976bb8c318493fe74b96 SHA1: 5ada37411a552c3daefff1f7e639d3e1500790a1 MD5sum: 641bb6eeb92966e7365f59a6fa4135b5 Description: blessed package to manage your versions by scm tags for Python 3 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 3. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1+nd15.10+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~nd15.04+1+nd15.10+1_all.deb Size: 11166 SHA256: 1a35d61217a447155375d01b44b37352135bf032b57e8339a8bd18698ad7bee5 SHA1: f1da621e5d147710e807cf664696af5e55f7b08a MD5sum: e5b2847694d0a8355dee4125351645b3 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: 0.18-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6544 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.18-3~nd15.10+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_0.18-3~nd15.10+1_all.deb Size: 1382608 SHA256: a3e513716cf21b9d7aae4dce9cd7b638f7628e57303fed66e90c015f50aa4236 SHA1: 00e67e3fb8cef4c37a3e14b4f8d67d970944c707 MD5sum: 994b866ae4690f05a1333222b2143d04 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: 0.18-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 11435 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.18-3~nd15.10+1_i386.deb Size: 1682070 SHA256: caa7a22ed447250ddc0b0f0f10bb216b2dcd1881344e60da80128c27397fcd39 SHA1: 31f57264ef5e780a5ed17c7424fe49bea332dad4 MD5sum: aaa38023f0695ea960c1990926b2e718 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: 0.9.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 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_0.9.0-3~nd15.10+1_all.deb Size: 20210 SHA256: a7b3e986cfebbee76d94d96ee250b6bf30daa9e05523aeabe532c647949da347 SHA1: 958c3fcea49144bef5ea4ec0fd7e765bced58cc5 MD5sum: a6c56b7c4d8d325899ae8f4bd7598488 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-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 360 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3:any (>= 3.3.2-2~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd15.04+1+nd15.10+1_all.deb Size: 117324 SHA256: 2087eafa13d5d935b75bf36177ccfb79fcd4a4d725a019a9405e6c0fd01a7946 SHA1: abbee96514412f64d6290c13eb64b0e76301b72d MD5sum: 1be1eb10f30f9c390b16d84730cd7621 Description: sphinx theme from readthedocs.org (Python 3) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 3 version of the package. Package: python3-tqdm Source: tqdm Version: 4.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, python3, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.4.1-1~nd15.10+1_all.deb Size: 35610 SHA256: 3d672446eaa58cf21b117034dfa3e650101e86227553fd033c858898e586d118 SHA1: 5cc7f32c2ee638f5b7b648edcce3f1d240810ffa MD5sum: e80a7a7b2224b14a6ce66c6bf442ede7 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~nd15.10+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~nd15.10+1_all.deb Size: 65462 SHA256: 3f4de8c8c45ed9cb612484f7f4f0ef22c45bc83dd0c28973789b150e57c52e8f SHA1: 4c82bb1717718e5ff8e8372069e2b1c869e2acf8 MD5sum: 7d2fe27828b03d0edae51bbc9d54aa8d 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~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 158 Depends: neurodebian-popularity-contest, python3-six, 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~nd15.10+1_all.deb Size: 43660 SHA256: 87467b0cf42e3b7197dd751cc11bfe3ae3dc97c079b2c3bd74926c292e65bca2 SHA1: 0a06a088059a07035959e89234c0c16fb44b7e43 MD5sum: a9ca94836e77ce920c5cf1363006f43c Description: record and replay HTML interactions (Python3 library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 3. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, python3-six (>= 1.6.1), python3:any (>= 3.3.2-2~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python3-w3lib_1.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 14272 SHA256: 533da9885ad69c4c60651a590db9fe179c98ca1299ebdad29088b6a9442ec0e2 SHA1: 2a0727511a0a354a099d604f19678016d837da35 MD5sum: b430b30d2b88af7a47b2cd4f7858d04e Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: python3-werkzeug Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libjs-jquery Recommends: python3-simplejson | python3, python3-openssl, python3-pyinotify Suggests: ipython3, python3-pkg-resources, python3-lxml, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python3-werkzeug_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 163474 SHA256: 8a96e417144a08c9a879cc1f5a75631c281bb44e3365214ac99d47d7de3f3158 SHA1: 20740ca85a429f29943d1d914db42fcdbb144741 MD5sum: 89cbd15be9a80bb4de07236524ee85f1 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: remake Version: 4.1+dbg1.1+dfsg-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 326 Depends: neurodebian-popularity-contest, guile-2.0-libs, libc6 (>= 2.17), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_4.1+dbg1.1+dfsg-1~nd15.10+1_i386.deb Size: 155398 SHA256: fef5c8233a3598c9e2ba4d84b2caed9b95ee6fe053c329b2f61568529b78dd78 SHA1: ee463dc54bf89369f3f4bb8e07d73da9eab38e48 MD5sum: 7918d097887b2573663d08131aefdb1d 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: 2.1.2-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 310 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.1.2-1~nd15.10+1_i386.deb Size: 54122 SHA256: c0c4f8a73b9f894f7c55c2d1a7aa6df77fcaabb61718f4be2fc5c65dc843279d SHA1: 62dcf8f31c0f1616207d294ae4ae79eaabca0e2d MD5sum: 937522def5c7bc2b9ee92e1d6dd30037 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19187 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~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 9766876 SHA256: 7d9bdb3a82e3a43a02259ce2031e99063bca119ddff1e3d6bf7ce6a143b9bd37 SHA1: f83778e94a46401b881ced3fbc687dc547f5f6a7 MD5sum: 1c82284fd53d2f35105ec08dc391695f 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~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73020 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 45519214 SHA256: c60d1744dbf2040909c0f26a32cbe986fe1036f3e5e54c09e8725b841202e253 SHA1: 0f1de9650eb97178e6519f5f010cc73a97144a63 MD5sum: 124be2462bf6d731e2fe1cec360c6551 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~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9252 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 8934882 SHA256: 6480ec9d767bca325e0a22048cae1ffa576957b7571173989de5b2aa34e6274d SHA1: 37ab9dddd62047263547e3f9c9d870145ca75495 MD5sum: 6341a23c432a49ecc5ee9c3acf4f1f67 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: spykeviewer Version: 0.4.4-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1952 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.4-1~nd15.10+1_all.deb Size: 1291826 SHA256: 7552cbbe1e00ffd605c5fd1b66f50683a027c4cd5762b171f628e560b141d167 SHA1: c589a8f176e175e39224ba231b55a54311aa76d8 MD5sum: 989236bfcf364596da1d5fc9175f742a Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stimfit Version: 0.15.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3068 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.7), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), 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 (>= 1:1.8.0), 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_0.15.3-1~nd15.10+1_i386.deb Size: 944086 SHA256: 4730f590519e3bb4ead8aa6dea82453340d1a2261ad7f0180ed45caedeae2ef3 SHA1: 45e323f6898231f472231ad74df0f5c015c82ecf MD5sum: f3318644ccae312fc910f1bb1cc42b4c 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: 0.15.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 23612 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_0.15.3-1~nd15.10+1_i386.deb Size: 6185690 SHA256: 78af01402527721718765c2b191fa62ece4c389d4b9298db9e841a099c4f5074 SHA1: 843c48ad8344d6ee693134c38a30f0d0a83aabcb MD5sum: 81b3191360ee5bcf774e3ae1e1746ddb 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: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 85928 SHA256: 936b9b3bf81d8968c2480748adff4cb602f064eeb3fd484923b10f2f376063ef SHA1: 027a77a63a9a04e4f169e0c0f041a9620e4b31b5 MD5sum: fc628c660d2d143f5dd33145ae1cc28c Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~nd15.04+1+nd15.10+1_i386.deb Size: 74284 SHA256: 778cc167ae10be4d14a9993f4b1e7a209a164212a9ab6b593f71c193f74e2d34 SHA1: d3ba2f4426ee04179a9f8ab82b251eb381e8bcc0 MD5sum: 80413e7c7d77a201365fb25c1c29037d 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