Package: aghermann Version: 1.0.6-1~nd15.04+1+nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 520980 SHA256: 765131d4c208c334da87132d777ef0673d7c4cca62f96d87e60f1d3e05336642 SHA1: 5c4e5d222771b3d1119b848040c7dc37a2cc45e4 MD5sum: 04440351bcea08181f7ddfe69b8b2f7e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 680 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 244400 SHA256: 8df16469e4c7a140d6567b8276e3d13c5daf017b9ec30030bb6737b4e357cb21 SHA1: b08084786b7913f1d73259a14918da8754e61461 MD5sum: e9c8cf542cbce70a98c70a655c64a6c9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3460 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_amd64.deb Size: 495208 SHA256: e318bb52e69cd0dd411e98827ad3006927db02f517321f148e28b3cc541b7011 SHA1: c5d333fec963e854443b6ee71288ae12299f0060 MD5sum: e3c1ec53c579f7e560bbdfd87d008237 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5629 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_amd64.deb Size: 4574962 SHA256: fc303281204f6ed3d1689190dabd19fbea5945eb997abcca74a86b19a25a613f SHA1: 0a3b75ee8ad85bb77c019fc30364192f15169cfc MD5sum: 1ea984a7ae58d226e7ac5f44134dbfcc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1043 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_amd64.deb Size: 146984 SHA256: f9f12474523142192a4f42baaad449e6ec3e195071134fe3ce7008587136ba78 SHA1: 553861cf0ab343184494a9fde6cf595b0942f7fd MD5sum: b08b1faf665fec94df753e6254e9617d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27146 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), 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_amd64.deb Size: 3812240 SHA256: 9fcbcea77cf8fa4226597fe14c75c75cc084dca9dcb7ed67dd33e9f8602af0de SHA1: fe9f3307ce891239ffcd10f148496a4d53f2dae3 MD5sum: c6cfe803afc4e15f9a45e0bb3e5ef2c2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 17664 SHA256: 0772d8ae57a2b7e0c9df039d91aecb0f0ff3dd8a7bfc406f644cb4be625cff3e SHA1: b07c8c47e9005c9320d8ec31200dc3de32293c72 MD5sum: bc6dcdf7b119d2eb273379450f1811f0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 52648 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 25350348 SHA256: feb62782cb6d53918361662bcd820b3e9d48a2ebb44ae2a364598067ed81a89f SHA1: 5dc877e8d9e51d38d888356b97ff75f7242a606e MD5sum: 33033fa15034dca7f40880b2f8c9a457 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 126684 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_amd64.deb Size: 123934858 SHA256: 66c0881f24d350bfad16b4d09ec99918d24e349c0b16195c521d88e00bcd3e96 SHA1: 071adb77257ca80073b2d345f13b771eba5f1495 MD5sum: 5959a6695f3d86dd589abff60e2d8bd5 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: 20160921-1~nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 220 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_20160921-1~nd15.10+1_amd64.deb Size: 95706 SHA256: 2a383b7830859bd4b3954abde954aa0d28ce028dc121c1c2779c543e4c315d4b SHA1: 6c08fcaa83594a469659e868d9a5f0cf6d96d8aa MD5sum: 5f6f308197b552cadf9f91ec66b2207b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 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_amd64.deb Size: 38584 SHA256: a39a50a9fd9917205684db778dfccaf76bbec9a9ce591054078252ff1def5407 SHA1: b9332b060e1221f534f10b134dbd8fda82606a5b MD5sum: f44eb5e2fdf7eb604d82bd56cfc0e5f6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 44718 SHA256: 129f21a7c7c0247b2c190820b61c9fae2159a2fe6db3634fe002c088c34821cc SHA1: 13413f64ffae680161fbd4217c529335a97b8928 MD5sum: de8bbf50eafde5b3dd8a896bd412b7e2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 130 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 37506 SHA256: f90191fbcfc34f1f97d68638cb080f39195e6d139f8195d7e52c90ac57e745ba SHA1: bed50d974512a7bcf4b733ff657f2bbdfae8af18 MD5sum: 42cc5a260ccf70b5485984d69680e957 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 78720 SHA256: 85aebe0cb3f7225391dfbdf8f6b5688ec6ce61fb897d5f4613335b2851d3f449 SHA1: 4278b31fda4a5970911e911a8c5581137af45912 MD5sum: b93535fa14064d57d26c3b24f89cd786 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2870 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_amd64.deb Size: 598732 SHA256: 76e56382cb3aaa04e7d66e8054cde5463a80336b86ca0be2cf6fec93b41b9039 SHA1: 27e29d49ce60b629cde162cc30c68d9e4a98c030 MD5sum: 71c38fb89ad80892b315e189a6e4b054 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: amd64 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_amd64.deb Size: 8636 SHA256: c73151235babcb5b74a0b9f043f2b92bd1a42b83f21de0d12596d13753896148 SHA1: 020a287415e25e93e1e8c77d1ec13a5ee789c1bc MD5sum: 3b1ede1602a8d9f64618bd9fd5db52af 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6807 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_amd64.deb Size: 1343586 SHA256: a05cee1960bd0542142ed2ca72122f221a2e9ac56dff31303b9358ef1022160d SHA1: b169290a2ee3cbc1759dba5c9d0c396639f26a57 MD5sum: 6bbce3c6339f9c65c1d7627e95d3e51e 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: amd64 Maintainer: Richard Hartmann Installed-Size: 412920 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_amd64.deb Size: 29553280 SHA256: be17320ec981d8374bebe5934ace9d1ac14811da01e3860945f4835d1f3b495f SHA1: d69eb2cbe9631fcf6d0495d52153d8f98e675e2f MD5sum: 20ea295910c93a1b866d2450fc022ffa 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: amd64 Maintainer: Richard Hartmann Installed-Size: 45 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_amd64.deb Size: 9076 SHA256: df13c8d6accff21cae1128fda8e3626634b54097765c744bda4d814a294a4754 SHA1: bf65febb9152d0ab4b069d9ef9ca4b44fc3ea7fa MD5sum: dc4d8ce99c459c96dd4f4a6d010e02ca Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 75d11a3ee55319e6cebcf33286de8df9a39bcaea 75d11a3ee55319e6cebcf33286de8df9a39bcaea 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 12741 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_amd64.deb Size: 3626776 SHA256: 765d2d75d86c0c6338f3d22881175f3977c67d87b8ede914e2db8fe44342a720 SHA1: 6fb0f6893533440cf97f0aca8bda5d0bdac535a4 MD5sum: 56bb82e77f1824c583a713920a3d3055 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 36785 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_amd64.deb Size: 34737824 SHA256: d3479be43e499ed721bd6e00c83f660d86b161dea0c282ac55f49fdc86caf487 SHA1: 93c06e1a4dfc988049d97b360fb34c2f3a8f7292 MD5sum: 54c4176aa344cad93b92307b656e8cf2 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 1655 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_amd64.deb Size: 303200 SHA256: 3477c8345e575a16831cff0a950e924fa2286f031eeb918c9e785b4f58996648 SHA1: 96bf8271252c93eacdf06113f5c6c6fc49bdaddf MD5sum: 34c13f93bcc9fbe7962be4b8ede5e18d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 423 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1), libboost-program-options1.58.0, libc6 (>= 2.14), 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_amd64.deb Size: 122378 SHA256: 0f296e655d2529f43f92ae0fc6be8bac034ced74c9208080f19f3903b606573b SHA1: 932185a3af030744be0d5e8a3932415f5d637767 MD5sum: 8aa6b37d1a4162584743a10ebfb03fc2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1741 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_amd64.deb Size: 304894 SHA256: 7f509117c6b79e6dbe7c97d0e885251424a16429e8e5655d92ad22e47fc01321 SHA1: ae654d86568b835a854e72c41863ac9b54ce37c9 MD5sum: c8d412d06b55a32979a2b8bfcd959efc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 923 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 281544 SHA256: b331ef9f5f9d3b0e82cf8be9d825fc3eb7b855438ce35557263540e83b0e946b SHA1: ab39fe56782a6f2ca813406c60de261bd0ba28f7 MD5sum: 539e7cc42fe0462b54df00259b3f87af 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 395 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_amd64.deb Size: 71984 SHA256: a37a61296e0b36cb75246f4448ad7f5b06d667b4de5f9de1eb916645fea6b9a3 SHA1: afc47cd73fddebaa6e5d52e885fcb6a9bb6884b3 MD5sum: ca1c839801bf8f8f33a81b8c47369284 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 1423 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_amd64.deb Size: 238094 SHA256: 8f501e3174f8c7fb3363f2c9f254aef3d42110d746d62b76426427d388e2b86c SHA1: 497bea526340982ab23034527e665a0258564c98 MD5sum: 3de2e621fc8a706a390143f7a8d3ff84 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 189380 SHA256: 280bc4c730642c7683d630116ce6f1250613a285ceb9ee5c0c919caf1b991e7b SHA1: f0d9c3a2fea4ef60b4778efdc1830f372ebc1513 MD5sum: 319930ce56df4e1667ad757035d9627a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 280 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 77712 SHA256: 93c4e8cf9ead6e475db25896a91f0d3632bd1dbb2d881c87f0d9b65143a952b0 SHA1: 46f94dba10c9b45d73e068f211bd04d410b73471 MD5sum: d72c2226aa683b67fed10193207adbb2 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: amd64 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_amd64.deb Size: 21252 SHA256: a586fc2c7138b7ac2ffa99290c9b674e102a65440ef159b389bdbf037fa1ee4d SHA1: 7544cfe4e0bf990238f8b6ddb832a54a1fa42b7b MD5sum: 9fe43288ccdfaaf1cf8e374df2ed71a2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7746 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_amd64.deb Size: 915088 SHA256: 6d3f07725f0d7377037adbbb103a9493fef249ea59869a8109886736b80d2411 SHA1: 81b53327779bd4253fd8151abb1ff5d32bd3decb MD5sum: a181f254a80c7c12fdb03aa613d428e1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5054 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_amd64.deb Size: 818722 SHA256: d3ccc3fb25db51bd2f30b07956bfb3a469454d3c4195458c771936de54981a1b SHA1: b2878b3822e01afb1baffc1614fc7cc830aa5c36 MD5sum: ef32707d94a9f3859ef4c4e092f76ceb 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.14), 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_amd64.deb Size: 54902 SHA256: d42b2b2ea9dde425755c119c74a243405d36c699733d1bc257fc2ae0fb068bfc SHA1: e42b83a24c933e53f535481272e2f2f41c36d73a MD5sum: 0ec60e40cd7422e03c22fc6765591c77 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: amd64 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_amd64.deb Size: 8662 SHA256: 1c7e3c73e880663f31a5aa63d5bb25153c6a03e17253041b4a9b46bb107519e7 SHA1: a7e0079c4ace49d760304a8857750e74d8f45243 MD5sum: 246b7a348f6717856988f8d94359466e 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: amd64 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_amd64.deb Size: 19438 SHA256: 3db0c5d26ae21010349d67854323ddeb36e8189b6cfd755f806837b94f6b6550 SHA1: 17df03b3d3a704f586f34113f3fc698af4f6f2f0 MD5sum: cd04d6b95b239d97cbaf54b3c9b764db 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 133 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 42448 SHA256: 67eaa104ed0ab0484a8d756fa8fe1dac07be8a4b5eed39c7b36c3206cdf6b5f8 SHA1: 008f0fadb6a3f001fc8db22184e03b9f0cdcba25 MD5sum: 0263955da891fd014da2bc9e753621da 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 515 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_amd64.deb Size: 101408 SHA256: 18132c8728ac0b26463933ed438f32e0b0a678d9137880240ac1b2afeb78c97d SHA1: b623f0fb0c01bfe0fbe2e914c90f73f99c6ab779 MD5sum: cb60acda025249c32db452645edecd2d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 266 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_amd64.deb Size: 85388 SHA256: 79b8b760a3a2ed9a0c95838ce1330365ba936c6fc1417113d708491abeb39074 SHA1: 899c348c1ff75a9f6c133a51abb89dabfd9a2f1b MD5sum: 7def016111b6a1a71f02e5488c2c5cad 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 117 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_amd64.deb Size: 31336 SHA256: 43644426a1cb014a192d688660979941b829e08140dc65d03155cc1c3b2ea3f7 SHA1: eaf0ee119408a2f964c19e83af4615917551552a MD5sum: a8d1b8cfa054bb4172d570eb2574b4bf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 71 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_amd64.deb Size: 25452 SHA256: fa9a162a7fa77ff1b6d112f2201774f012615e8405cffe31d0abc8ac08854eee SHA1: f7262d2dcb13d09b4454270dd774e2716f1487f6 MD5sum: 03d75da45fb45097172a7f5c07e18a81 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 320 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_amd64.deb Size: 61352 SHA256: f9549e825c6534f5a605e8c76e2dd6d957f2af855270c5b2d5be9158b3136b71 SHA1: 2098c3673053ac44a22e71dd24b514e8925de072 MD5sum: a8ccdc5ac2532d6777143ad8ebbca6ac 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 43282 SHA256: f37a4759014205dc17ecc62ccddc767b85a74687252c93b98f7fd9e87791150b SHA1: d0e70f36121970770fc7064518f5728826f1f9a1 MD5sum: e6a8b48de32efebefc3d1adc802b8cef 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: amd64 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_amd64.deb Size: 13788 SHA256: 1e0802315327a838123f9a56c10b9325856f40b6e9302654fce2acaec241a8d3 SHA1: 2e7e9699aeabcf5ceeaa2b0db7490ac83f618b76 MD5sum: af70db860ac3751874d52f74ab629576 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 341 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 77814 SHA256: 80dffd7b4c80895929ee1ce943c0d2ec817a7b1a1107225e2f0aa68679bc9e04 SHA1: 02b02928e3cff07e5ac39db9ae2b8a9a8307fa6d MD5sum: b033287aafdbc2fa97bdbeaea268e28d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 277 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_amd64.deb Size: 74308 SHA256: 699f9626d49739684904c27913b17dcaf11a187359faed129351906680874a10 SHA1: d2e7bc3379146b0912627062c308627fd7d2aa2b MD5sum: efad2fe07c019fd08a786388dd3c0f62 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1787 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 445524 SHA256: 26aafaa7bc30ed4adab49223f2eb4ead2e891cfc43b82ae7dfb0c43e1331bfe5 SHA1: b5db8412249d025a104c3cd46438419aefd03ead MD5sum: 14633cbaa41df73ce076c784e30d9d19 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: amd64 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_amd64.deb Size: 80894 SHA256: b463293241dcc981bd741f38427e42a5d375f983f7ae433f685b727e2faab953 SHA1: 786c40c771f5782f07bef602e8e0357799fefc47 MD5sum: 6eee7fb021c2d2b68146746be6cf26be 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 120 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_amd64.deb Size: 37758 SHA256: 3d816cda59b140f328ed0e2a34fdd7a6597f98e29dbf38be06ff7447484d1ba0 SHA1: fd16596acf73e75a438d2a07cf4efe8ddd37deae MD5sum: 0d7e7021a481b5736152f028c4b99f63 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5560 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 829604 SHA256: 40d246cfc8d993bc7fe232b00af6f8a03686a86406f2e85be8d634c81d8b9f0a SHA1: 88c5d594ff045dd390e6da246ac9779b0fb38411 MD5sum: 1c296e0d8623ea72c7c6b033fba8baae 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 16779 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), 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_amd64.deb Size: 2312386 SHA256: e31d9422a4f2e6f77a43c86434b1b613399e060fd3735b471d2755cf67ee7a05 SHA1: de0954f9719d9ef5a32b35f6a81e58cbb29b4579 MD5sum: d123e8bf062ed7b37ddb38a856a1da9d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 87 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 37638 SHA256: 11dbaac6d31c1a39cc05d9171d05be01cfaaa77d01191031e18d70f8955bdb22 SHA1: ed7ffa325181c3fcaff669ca5c6048919d7e4716 MD5sum: 3afc4412fc99604a34c23f1bbdf3048c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_amd64.deb Size: 31110 SHA256: f7be3cc7aa2045129754099c254322ae1310a194d61f94ccd0b23cd3e346dbd4 SHA1: a9ead25abda0dfe22b9b51fae65222c07f8fc84a MD5sum: c66ee98da8a9ce48c8474bdabc2d04e8 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: 0.5.22+ds-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2945 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_0.5.22+ds-1~nd15.10+1_all.deb Size: 616566 SHA256: 8b792dea488b0ff5ee910b713ea3c4529b816a4c5b09a9801a6c1faf263db482 SHA1: 8f167dd64fdd61d9a8381397f4a7711f2bf25928 MD5sum: 4ac01c80f74709fea095b38437c9ec44 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), 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_amd64.deb Size: 19710 SHA256: 7d0c56ac2433430b9ab571db02531d979e89d824fe02a5707688fd8a4a5352d6 SHA1: 28810f033c7dbca0ab6dae15fa0e1ae0fae9de0a MD5sum: ad8c745e1c73a087286c20e07b6e421d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4586 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), liboctave3, libopenal1 (>= 1.14), libpciaccess0 (>= 0.8.0+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_amd64.deb Size: 907812 SHA256: 2dda29b13b4b65e6519b468c706dd763ff84d93bc8fb5138c54d14274aa16b8f SHA1: 38d717e44effdb06e01d5b4853f53c0c00205221 MD5sum: bfea32b90e63dbdb100c3087fdc8db44 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 853 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 339026 SHA256: 1ac214c20db8c2d27c489c35f1550856f2a7c1c57d6a718654a9d846bceef610 SHA1: b3fee11b02644444658898fa1279ff9de70516db MD5sum: 8d63c04b3289be274a61903675653a46 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4239 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd15.10+1), libc6 (>= 2.14), 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_amd64.deb Size: 1166584 SHA256: d16e426a00745933d8fe0f74aa4fb0bc599129106a5b240198b0a0bac7e5a2f5 SHA1: 25f6117c703e815d1893c6b866c1a8ce706e4a59 MD5sum: 2771cfeef7ed7c11f553505ac5aa8721 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3811 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_amd64.deb Size: 733230 SHA256: 7bbee64f1349f40a54a28c9fd723d95a8c76f9893e1928b4d310ab158205206f SHA1: c0d0b0ad4287cf968673c476ba5235696e7b68d8 MD5sum: c2e486039369bc37b2c92f9f36af182d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 190 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_amd64.deb Size: 73016 SHA256: 4cfb7c2f0da3cf474c1a4f600e38baac91601ef220fe37ddbc09c571d826c61c SHA1: de3a86e8787a8b2b9b631158677e6b7993770a4d MD5sum: b8608337d0da9dac59c02bae13ff9f26 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 231 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 (>= 2.14), 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_amd64.deb Size: 43404 SHA256: ac540e937d52e30d083d976f2464022ccf4128bd20a7d16c93b00e4d3474ba12 SHA1: cb1a55f4edd52b572a93cbc7c1d486696f0e9889 MD5sum: 979ddedc663b74cec8704d660d250901 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 158 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libc6 (>= 2.14), 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_amd64.deb Size: 40714 SHA256: 7e5b908ae45ccf4cc6d379fb748ce8da985172beda48f0b0156cb466920c7e60 SHA1: 6365b3ad359fe447cf4d994b901f373cdecd8c07 MD5sum: 912d31c71c6c547b7b2005fc1e19f002 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6784 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14), 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_amd64.deb Size: 1157858 SHA256: c27a05f596ecd316512d5555ce3e6ad0cd42759dedcf447d59bd71e1eb115067 SHA1: 888c7c8bc6117b3a359a91e450bf5156cbe84e73 MD5sum: 85dc4bcd1231b9071a99715b65d52322 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 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_amd64.deb Size: 45308 SHA256: b73b41ddfc083ba6b64d9143a307e24c110bb58369ac9781c758b481bb28d1b5 SHA1: f3c265a1d0ea1c2df0195c35a818b0f8b4994357 MD5sum: 1143cbcb697c048538eb515f46a82af0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 231 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) 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_amd64.deb Size: 54130 SHA256: eade3c6c85c40d8205536f43a4f45ea080e6b3aa31132e95bd6ed2d925ee9438 SHA1: e9b00d1ca2e106155f0699a0d4ec50dfa137f4a9 MD5sum: 0382e79b27593242773420343b4f6a68 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1320 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_amd64.deb Size: 237580 SHA256: a65707d17f93a01b2dfdf5f505353d5ea329b85c7341978d878a49d5235f6692 SHA1: 1b81773815ad71fdb36e681404daad5d4e5ef379 MD5sum: a3a756a535d4e96d3e69224db6882795 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1437 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_amd64.deb Size: 337648 SHA256: 089fdf256f8a7c6d177b45a5b82b20e2c78f67850557037ef5f510469884adb3 SHA1: ca9d2d677ca6e73146d1e81416297e36ba4619c8 MD5sum: ae7fa0625d4ad08e7b7abd84ed56006c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5577 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_amd64.deb Size: 1025968 SHA256: bcdd1b9cbdb4ad73070647277cd33c27bbe32977a45889052a0bffbfe8e83ba1 SHA1: d9605cd331277ec7b34b57d13d12c1a33b8c29f8 MD5sum: 69b1a392811d523cb1db092139b6cdd4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 50336 SHA256: 740f671451717dbbf14011bdc966ee156a828f0ed096574ef0f62fdb5eb58e28 SHA1: 5c6f3374e6d137dc3c4919b491f5745058a5f0ca MD5sum: 0c972f7ccd51f4779b87f1eb464ade0e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2613 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 619830 SHA256: 161481d77f8679d1c03793ee44d88f2a281b80cf69782b33be750ad106dffadc SHA1: 82c4d3c5e160b1d6090deed20cfe9e6533f9e803 MD5sum: 143682907e1529d2965c4d9bcffffa91 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3758 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 636040 SHA256: ff4711673e55a0abefdce9ccc05346f983fe49826b77a6949f97df983df8dcaf SHA1: e79ac29bba4e6bafa7968973db7b86e2e0ed0d13 MD5sum: a3ad4c190d3fdb0a46341cbc0fbf3415 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 401 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 (>= 2.14), 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_amd64.deb Size: 136156 SHA256: f5b87d36c04471feee4b4a7e094b1e4da101236399470e37efd386b75aefa243 SHA1: c613b83e6f774b781024f3ac3210541372e1757d MD5sum: b358fc9eee2f2690a4ce1b4d9b97d5fa 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 274 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.14), 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_amd64.deb Size: 106548 SHA256: 944efdf874423f66f0704ec8c3b3c7b63a60ac58ed1c2393c0abcc363878ef13 SHA1: 128f72de8720d4b6bb9fd4ecee62bf74a4d756be MD5sum: 8ace0108dde7dfbd74fdf9221d46a0e4 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: 0.18.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24240 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.18.1-1~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_0.18.1-1~nd15.10+1_all.deb Size: 2528058 SHA256: 2a75779cbe092573dfa41c77399957bb3ea9acb12238b9a0b7b0161d29642785 SHA1: 63d2f5a64a93e11dedea1e1984798eaf24db0b64 MD5sum: 74010cb893843c145e2ba8213dfcec45 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: 0.18.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58567 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_0.18.1-1~nd15.10+1_all.deb Size: 11062562 SHA256: c318679299f552d28991bcd4f0bccc4e124d9d07a4e61b31a748e2b7f9f9bdb7 SHA1: a664d124dec249be3751a9b06c93b81318505949 MD5sum: 6dfb088c7362eaa45384a551b6542983 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.18.1-1~nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6222 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.18.1-1~nd15.10+1_amd64.deb Size: 1574262 SHA256: 589401e1cb2081af45133895863015e1eeca9811dda4887713ee50a61342ab96 SHA1: 9a7c8e223c56328bc1f9b8865a7d63bb8d859de4 MD5sum: 6ba48309ed307fe3e3202d9dc4483819 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1434 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 (>= 2.14), 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_amd64.deb Size: 284186 SHA256: 178273665af4cc4d367595b8cc232dc6c089efb17d0ad3a234369277a8af8251 SHA1: 6269db9e94394423ba8aead3f942ef58380e8ba6 MD5sum: 17d8fa14e2a754a0f7d11e50f2207404 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd15.10+1_amd64.deb Size: 74374 SHA256: 88385a78f07f6cd8ab11195f70dc5733765b32669ca96cd76abc71492b9903d9 SHA1: a00e4b28a2df2fe4504e8bacd44acff112bcd98e MD5sum: 47e8cf91b97bb68d4df9977a3aa8be70 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 308 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd15.10+1), python-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd15.10+1_amd64.deb Size: 113222 SHA256: 3839a9efc56c1eb4e80bf71132a90f1b59e2d14d818c0a6e0eaa106e29d94c1e SHA1: 06cd4c4753d53669a56bcb7e9b4679464dc9cfbe MD5sum: d34e40caceb2f546975f0a27db3e7d9e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2805 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 591630 SHA256: 4e76fe2ad5eacd88bd6920fbe740c41d3bdca0fa0c6bbb6d1801512e0079d11f SHA1: 717a4b15a58fbbbc6752c06709d8dcf215a62a12 MD5sum: 5066a2886871aeebe8930cc760e23b12 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: 0.17.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65 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_0.17.1-1~nd15.10+1_all.deb Size: 55986 SHA256: dcaa0d8782e32703e3e68cb9e45f98d9b8de9d6959736faaba7be63b3454a785 SHA1: 04d45f2a216d92a152e3c535a1390aa854a45ba6 MD5sum: b02d58774b4f524fd61d87e80ead4674 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: 0.17.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5283 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.1-1~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_0.17.1-1~nd15.10+1_all.deb Size: 1223644 SHA256: e19d8c143e88651d29cb3213d402b0e8c76cc5f2b041ca9dd5f7704cd02f17a4 SHA1: 902f840bcfcbf2168c0c76b697e6944b530a4976 MD5sum: ad6a292d611ea5e69250736194123c32 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: 0.17.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24698 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_0.17.1-1~nd15.10+1_all.deb Size: 4063728 SHA256: b34d49d6f661d191daacb054ebaf839b8ce23cdcd2440a3f2339fb11435f3b6c SHA1: 1e0ddef8695e7ec350e3f6ee39a16b8891f2b770 MD5sum: effab945d57de3da4b8997c59878ef08 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: 0.17.1-1~nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5017 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.17.1-1~nd15.10+1_amd64.deb Size: 1111088 SHA256: 0f036262270ee16ef83d6a2c7e70d8166a235e0d0a474d98f2b382cc3c3cd950 SHA1: e044a89c87d991a5069c3ddc65bfe68fcc37fe4d MD5sum: fbb0be5bbb4a49cb83cb540f93447fae 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1740 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.8.0~rc1+git43-g1ac3f11-1~nd15.10+1_amd64.deb Size: 238420 SHA256: bcf0865f35ed2a167bac3cf5f9e937c81e04d06e59fdc8bbd2f882a1fd60b0b6 SHA1: 8aa2b9dca9360b1ab9b8a7e8974fd4f3ec0d86aa MD5sum: f4a1c223442ee86e280024468efc6f17 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1430 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 491598 SHA256: 9962127e8d3f77d7b620763b116adbe81e75bc977f3f06b79b23202aaec575c4 SHA1: d408d4ff6aed542c2cc13ab6365125934a0353b8 MD5sum: ae2705669daba6bf62d5441c78448ebd 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-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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 494 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_amd64.deb Size: 90778 SHA256: 0b561af538424d933738303cad4cc68bf90f2047a26769ad0322e5a9c6e42aba SHA1: 16c030b30ec3697298f6a2f3c6b98f3ee499b7eb MD5sum: 121d86860e7c68de809fd87ef49c0d7c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python-smmap, python3 (<< 3.6), python3 (>= 3.4~), python3-smmap, libc6 (>= 2.14) 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_amd64.deb Size: 54450 SHA256: cab192ca7cc52082bc10b3dd46341385c1d66ec3e0085716f2ccb62f9e2bc6f4 SHA1: 91ddfd1c2b6a08f07a9d96e26f863e44b1706df6 MD5sum: 42840c86b8489567f1d30d62f4441504 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1444 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), python3-numpy, python3-pbr, libc6 (>= 2.14) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_amd64.deb Size: 252858 SHA256: 9ba571288f3a8baac8b36fb5cb809f4be8087cadcfa5e31d10fc5c3b7327a94c SHA1: 746a1c2a6b3cccfb5e1842b78b40f0f6755d6eaa MD5sum: 5e699fcdd7a6a4b7b823bca07a9fc7fa 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2671 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_amd64.deb Size: 467518 SHA256: db1db7348b5a59db1c214744cce3c00856c446fee685d1a8c79d891414276f5e SHA1: 837cd37e1d95fe00e8e66b897f90219948c21dab MD5sum: dc076bb98883cda51a4874d1ca79c280 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12802 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_amd64.deb Size: 2133224 SHA256: 69c990b826d28b24d5c0c9cafd1ad3747d4b460a8e9684c6fe32a9a895b2e35b SHA1: 48bc3cf4fd2d260aff67be4535374a166bda8832 MD5sum: 9bb027d780caa88680ac95c1cded8105 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 637 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.14), 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_amd64.deb Size: 131116 SHA256: b3f6142a152f090716c576550e64c0ba06439ae6b456f11c591e17d1a872a594 SHA1: 1364087847e96c0501a79ebe262b32a0ea62afa4 MD5sum: 1f5b3b0fcba73592b3d0f049a6c53719 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.4~), libc6 (>= 2.14), 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_amd64.deb Size: 107166 SHA256: fbd5504b5dccb878a9882f646fbab98532928ffa3a9d56509aa9b7aa08919338 SHA1: 4d3f2142bf6529d7ebf32a4a27923e24803a522c MD5sum: 72c49d9bd6644c3e0f528d5e16156c97 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: 0.18.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24212 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.18.1-1~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_0.18.1-1~nd15.10+1_all.deb Size: 2524160 SHA256: 5752b49c628cee8fed89d9afa732ae631c22a2b17f45affccb38ad2da98f19c2 SHA1: 93852cc94016a4eff1fd135e6163c2f67998ed99 MD5sum: 36e56d2c5a856312371e63d09d659a62 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: 0.18.1-1~nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12113 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.18.1-1~nd15.10+1_amd64.deb Size: 2330640 SHA256: d5b3a8a1137b72f7a08e38e92623dc1bcd0069615f97ea51f0391ebe597ab05f SHA1: ab62c1c13a0b2d85583405215e4c1f5f88f9264e MD5sum: 30fbbd7eb951cde0d94551fa8aebd191 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 460 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd15.10+1_amd64.deb Size: 74434 SHA256: 03f4a69dfd92e1517d843494e5cc44aedfe90e64519853f5fc0ec8c654222769 SHA1: 71b03f021939a66b03dea23baacb7b5143b339cc MD5sum: 06e08809f0652baf5f9cb00d24413669 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 608 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd15.10+1), python3-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd15.10+1_amd64.deb Size: 169658 SHA256: 9ae18bb60bda0902cf633638b25bbd1819f21f38e981dda7f41b27fc907b82ba SHA1: e3044e452713abe8e47480d4d60c9721dc9de0d5 MD5sum: 1316f57720ef5103ddecb028d4306049 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: 0.17.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5282 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.1-1~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_0.17.1-1~nd15.10+1_all.deb Size: 1223188 SHA256: d9746fbf4538f239941a5b380316c6fed2ba7e56c9d6eccae057cc5277bf68da SHA1: 90dd24c089b0cc3ce132220fb6edfac4bca98e76 MD5sum: 12c494ced4be1d0e581792ab42e258f3 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: 0.17.1-1~nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9130 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.17.1-1~nd15.10+1_amd64.deb Size: 1478668 SHA256: 18e680898c9cf639a5c3ad077c9a13a3f68ce869718bb5f4d3b482926845bc8a SHA1: b876573088db36be5753af148ad828a6997a7cc5 MD5sum: bfa3380c09451379f0bc992d80d49c1c 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-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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 317 Depends: neurodebian-popularity-contest, guile-2.0-libs, libc6 (>= 2.17), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_4.1+dbg1.1+dfsg-1~nd15.10+1_amd64.deb Size: 151910 SHA256: f60b7d4168a176d040c041b038d0ac5b01bd5845844066f982101512e80a3f7d SHA1: 5e7539713fa1bb28e2a9d5ff65b37b81dfee3c38 MD5sum: caa0fc3bf6e24010deaa1f62bb55f89f 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: amd64 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_amd64.deb Size: 55236 SHA256: 0446359d2a3983f7bd4ee1570455b2237dd68719c278a5c921e608447231daf3 SHA1: 5246a19922904cf44cfc1b7a2e6690fb290ad878 MD5sum: bf4810d5f684942ba187279350384c59 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3279 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 930974 SHA256: ea8dc88f2465f32999a42e670b1b965add4d78aa67b4082536220b543371787d SHA1: 1faabfca6b4cb45f405ee7e80fc5b33a596fb41d MD5sum: a0599610bfe1569070b44a83447b3e6b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 30688 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_amd64.deb Size: 6616752 SHA256: 27ddc76d50babcb5c39836eda548204edd37ed0b3de610adce0af7f9ddfe49e2 SHA1: 10d45059aa9c6733dc1ece55651a7e084ca627c4 MD5sum: 2a65692da3f922833a3581c61e2c803f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 291 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 74230 SHA256: 545cb5a8e696f2500c952d19b13e42a17e5551dbdde9cf0a577f8393def02a61 SHA1: 4b148ae9417e8dfda0bb6ccc96910d460bc70f5e MD5sum: bd5616da3c446973381a985fb9508a92 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