Package: aghermann Version: 1.0.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1592 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp8, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.6), libunique-3.0-0 (>= 2.90.1), libvte-2.90-9 (>= 1:0.27.2) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.2-1~nd14.04+1_amd64.deb Size: 530316 SHA256: 2c4aa9b4cba266a54fc03d728d089af7a1409724d2719caa6508bd2f44b01de5 SHA1: 508a80078863c9220689c62855ad1f426835421a MD5sum: 64cf596ff7b4d46e356faab2b222ba5c 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 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_all.deb Size: 14380 SHA256: fddb023e52a6515b50557af46c086354d4096c16874c9cd9f375586299d472de SHA1: 618cbfadea7eb8069c32c0b3075a3033adb283be MD5sum: f13ced8df8376670cb14d9be8d8e7798 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: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 658 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_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 237980 SHA256: d3d8e428373c2af08b0e58cbe323438331a6cb5ec8f22117b933528d29eebcf9 SHA1: 3dd6c393a0fa8fcfe062f13e264fc1d2c5a5c4c5 MD5sum: 2284918a2cfb6f96f3fe22e9d3eec901 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: cde Version: 0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1022 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_amd64.deb Size: 144680 SHA256: f8a857091f8f96b6e353bc6ee61846d5a94a6591c4366545284c574e0e3ffe6b SHA1: ef8e513155605f8c04c1500f5e5d70f05e67836f MD5sum: 8fa54dc077b3b3e90548a1a58db6a0c3 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: 3.2.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24503 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libmxml1, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), 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_3.2.2-1~nd14.04+1_amd64.deb Size: 3631742 SHA256: a991f829e3a68725b5ffb4e30ffa0349089260be722f7821e6c73eebc1dc701b SHA1: aba14b25b9aa6921c8841188c1b64950842dfa23 MD5sum: 65a4a934d4230bbebb982cca380c7c9c 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: 2.0.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.4.0) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.1-1~nd14.04+1_amd64.deb Size: 17168 SHA256: ef66a662145b9ff89f5818e99cd68866729a71558742075cf5f5fb23c3ceb83e SHA1: f3e7dc3ad67aa0cddb76ab6d546b18b3c801adbc MD5sum: 9910d22a6ce4a6da1be9f006d051769f 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.2.3~dfsg.1-6~nd14.04+1_all.deb Size: 14540 SHA256: 4385586338f37032c756e9626ed215d1dede9d6d5d0adb4199ece4f265e5ab0a SHA1: 6ac10af615b0e674599e4d92462706c007cecec6 MD5sum: f343027dedf91268b442921d0919a3ed 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.2.3~dfsg.1-6~nd14.04+1_all.deb Size: 14552 SHA256: e23cef49e65a14f1b1b924b83e9388358d86f577a4e13f045a2a4ad226a117fc SHA1: bb05607bbfd0effe7ec8ca420e2f0271e093e994 MD5sum: ffb9d2c96fd5df36279abe253c00911e 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.2.3~dfsg.1-6~nd14.04+1_all.deb Size: 14556 SHA256: 3fe2b31d3e71a38b82d15e518dfe7d2a45655cfed575a89d969113f5ba76ea3b SHA1: 445fadd8e6fb5b172fb9d26f85912b7a9c8c6012 MD5sum: a468cbeeceb634f4a66b6a246add626a 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.2.3~dfsg.1-6~nd14.04+1_all.deb Size: 14552 SHA256: 0995360f316a8273e2a5a4356268be5b42ed5cbc0a01dbca8d6b64ab29c88e81 SHA1: bf4f08d22c902cd2d07c1623d43be42927c95488 MD5sum: 147439cd85c30ae21a2e4f37998933a9 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: 1.0-3~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 35717 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 (>= 4.4), libosmesa6 (>= 6.5.2-1) | libgl1-mesa-glide3, 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), libqtwebkit4, libstdc++6 (>= 4.6), 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_1.0-3~nd14.04+1_amd64.deb Size: 18651670 SHA256: 276ec2ffb3c3ce92e6508536509eb1afdb9f038f60413dc9a1d18f24e2bb98c4 SHA1: ecdce0563441380f4c4d71f0367b325e041372ec MD5sum: 112f942a73453be598c7792e4e5b20dd 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: 1.0-3~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106223 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.0-3~nd14.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.0-3~nd14.04+1_amd64.deb Size: 104539718 SHA256: 87732988254385966bf50fd3a11bef016221aef8a184d8eaacc8d7d944de44b6 SHA1: 6d5f1dce953e7bad2a729fa5fd841a564f07baba MD5sum: e7e5e42f1e654691b28993491b189eea 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: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) 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_amd64.deb Size: 37574 SHA256: 48dde4d86cc614b77aa5a2d1290f6a04dacdf59c1f77451f8c5d5b13532abfbb SHA1: 25a49d3bd47422f2a9c9bc46a5d17de84ce5525e MD5sum: 6a68f3fbd055bcb6c949ff86e93a9c03 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: dh-systemd Source: init-system-helpers Version: 1.18~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, perl, debhelper Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/dh-systemd_1.18~nd13.10+1+nd14.04+1_all.deb Size: 13814 SHA256: d174181f267afbaf3c6c7d6108b65eca78861aa6d3c71288a03db9b5cafd5a13 SHA1: 15700758d679f3bda80f55b5f435edad45d1b39e MD5sum: 4ed20ea08d8c497a1a3e9b7ce46fe4c8 Description: debhelper add-on to handle systemd unit files dh-systemd provides a debhelper sequence addon named 'systemd' and the dh_systemd_enable/dh_systemd_start commands. . The dh_systemd_enable command adds the appropriate code to the postinst, prerm and postrm maint scripts to properly enable/disable systemd service files. The dh_systemd_start command deals with start/stop/restart on upgrades for systemd-only service files. Package: dicomnifti Version: 2.32.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 514 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.6) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.32.1-1~nd14.04+1_amd64.deb Size: 95646 SHA256: a0faecbd1cd8ce2829c36033a89e482cb37b5951395174cc03dd980027f13d0e SHA1: 974e826d147fcf090f756122c99938b28c6f4965 MD5sum: 0be470f6d6d61b42ba8b5d2c43807762 Description: converts DICOM files into the NIfTI format The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer. . dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files. Package: dmtcp Version: 2.3.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2520 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_2.3.1-6~nd14.04+1_amd64.deb Size: 633372 SHA256: 3595f57c349b565907ff07de81fc6baebc049a7ae3000b18eea1f21c75617f59 SHA1: fe9fb79ad98515cbf16a3b353ea6a7db81043381 MD5sum: d36e7d4cf8d373e4a47d0dd462edfe57 Description: Checkpoint/Restart functionality for Linux processes DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains DMTCP binaries. Package: dmtcp-dbg Source: dmtcp Version: 2.3.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24027 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_2.3.1-6~nd14.04+1_amd64.deb Size: 4207898 SHA256: 4d3c64cb9a85b297b51a75f35030ecb871cfc774ef67cd89b8b3df7daeb4bbef SHA1: a94860fa591411023309edfe00b19989124b763b MD5sum: 5229bcb10442f308559de77e60f9d6d6 Description: Debug package for dmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 7062228 SHA256: aa1e0c88dbb25feff7d4a79637ce14e2bd7fccf5b2e73f675ba5b88baebdcb3b SHA1: e5d9d261fdfa5d96e1fe0b8e6ce4b67948bb54c4 MD5sum: 0bf506b1eed312f76a0e48cb663cb40a Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.8.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 563 Depends: neurodebian-popularity-contest, python:any (>= 2.7.1-0ubuntu2), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: python-gamin, mailx, system-log-daemon Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.13-1~nd13.10+1+nd14.04+1_all.deb Size: 165042 SHA256: e127f8ed110707b842f8965f0995ff6a4177040a785b17a4d0ccb39be90dad9a SHA1: c1603990e18d3f45b3dc14b2e66ef38fa8fc29ba MD5sum: dbbcec95193e5e863c3e18aa21f8af6e 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. Package: freeipmi Version: 1.4.5-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd14.04+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_1.4.5-2~nd14.04+1_all.deb Size: 1176 SHA256: 351ab497edf77e27057224f06e672245168ca0085478caf33e3a7f01364ac2f7 SHA1: cd509e11e871bc75c9395149003f56ef280ea88a MD5sum: 93127239881403163abd01b5aaa00625 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 126 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), freeipmi-common (= 1.4.5-2~nd14.04+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.5-2~nd14.04+1_amd64.deb Size: 44900 SHA256: 7ce099976d85f641032b8e540da6e34ef1898a40e80f287d913c148f8d2bfa7b SHA1: 87dd38ab8162d957ab9ecbfbe6f4d822ac83b977 MD5sum: e635e34f2c8b6fd038c41c868b75a36f 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: 1.4.5-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 304 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_1.4.5-2~nd14.04+1_all.deb Size: 187850 SHA256: d4dddb1d121a4517d005cf1be28bbc8e0f1ca21ecc51f74c3772f02ce3bf1343 SHA1: 7e102038afd8da8c55626ff7c8cbb9faa064ddf5 MD5sum: 18fb02f84cb18329f0e76eb58480c1c0 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.5-2~nd14.04+1_amd64.deb Size: 37462 SHA256: 9751006850a737ece127bf050ecd57c5c12a6f820589a0a99aabce0df9a8875d SHA1: 60f85e933f8ad794df8eae59fed2bbbfa254622a MD5sum: f6369f1fe83a226cf3989a2d86c78f60 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 192 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.5-2~nd14.04+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.5-2~nd14.04+1_amd64.deb Size: 78812 SHA256: 5dfdf87a556efad12e8c07e4c87873885b9e4c523fc8b4dd19f766dd581f68e8 SHA1: 5ece3993c1fb303b0579b2936939cce99af95193 MD5sum: e0aab05feecc1fed7e9f400322854153 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2794 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.5-2~nd14.04+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_1.4.5-2~nd14.04+1_amd64.deb Size: 588914 SHA256: e05f84d10485a8da2eb87406b3f07803e1342445c4129ffa1e0df76858989459 SHA1: 22e56b9d2740ef7cede4cc6a492c11f8fd77faef MD5sum: b1f00d9efd72b58f95581e2e7b75b715 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.1, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 6948 SHA256: 553d9653ebff53e3e2f0d9d43eea79cb1c26ca8a42ec7d22a475ff5c886723ed SHA1: 30330b93d7eef6a0aed90490e2e3ef4fbb8eaab1 MD5sum: 33b72a09547ea27f1ed3eab991cdf400 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: fslview Version: 4.0.1-2~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6540 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 (>= 4.6), libvtk5.8, libvtk5.8-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_4.0.1-2~nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 1313554 SHA256: ddf9f6835ed9f521b3f9acfb178a7df9d6b9317b84f148c48528c356401e094d SHA1: f4a1398af39ad1aece1266ab586a30f991f136f7 MD5sum: 2ed4f1bfb30262eb780d5ae318e63d59 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: 4.0.1-2~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2874 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-2~nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 2227008 SHA256: 9b2fd16b794a16978563ce66f865f124613b7bfd5e3dafa7fef33fe08fc00799 SHA1: 8dcabe069cb78ea29e21fc607cdaa60ff6b73bb0 MD5sum: be7ec9467211319b53022709eb7d3126 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1733 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_3.2-1~nd14.04+1_all.deb Size: 1667828 SHA256: 875b666f07d8700de4339beeab8a44f884d4df259e48ba95f9dd18bd6c007024 SHA1: 29482fb436e234a6cc826ab0b5c5bc3b92d028a8 MD5sum: 001bcf0d3061fcb4faac22a33186d0e2 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: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libx11-6 Replaces: libglew1.6 (<< 1.7) Homepage: http://glew.sourceforge.net Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 93038 SHA256: 65b460894e0cf44263960f17ea4e04cfa28127aeaf01b324b6af2b1ee66f1435 SHA1: a57c2afe4059f7a47a35f7a5f209582fbdaf24d7 MD5sum: 2ad2377bec59c31a820fe47a55e6cb08 Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the utilities which can be used to query the supported OpenGL extensions. Package: gmsl Version: 1.1.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd14.04+1_all.deb Size: 13800 SHA256: 4127230a0b3a6b132f2e98087b496cddbabf8efd64fb0573ac384d4ec292ddab SHA1: 16ab5cc30564be2024ea5ea282213fc38a320743 MD5sum: 75f0db3af8b2efad55c4794e50b84412 Description: extra functions to extend functionality of GNU Makefiles The GNU Make Standard Library (GMSL) is a collection of functions implemented using native GNU Make functionality that provide list and string manipulation, integer arithmetic, associative arrays, stacks, and debugging facilities. . Note that despite the name of this project, this library is NOT standard and is NOT written or distributed by the GNU project. Package: htcondor Source: condor Version: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 14734 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libclassad7, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 2), libglobus-common0 (>= 14), 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 (>= 9), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgsoap4, libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.8), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libx11-6, zlib1g (>= 1:1.1.4), python, perl, adduser, libdate-manip-perl Recommends: dmtcp Suggests: 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_8.2.3~dfsg.1-6~nd14.04+1_amd64.deb Size: 3859902 SHA256: be0f426d12774cf250f586b2c3aa1eef55236bcafbe3c39f918850c5f3bfa8b4 SHA1: 8a7e38fdcc03ad02bd77a3789af0df8d57b9326f MD5sum: 48c85fddc9b52dafb9d17d0cad6f91b7 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 40041 Depends: neurodebian-popularity-contest, htcondor (= 8.2.3~dfsg.1-6~nd14.04+1) Breaks: condor-dbg (<< 8.0.5~) Replaces: condor-dbg (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: debug Filename: pool/main/c/condor/htcondor-dbg_8.2.3~dfsg.1-6~nd14.04+1_amd64.deb Size: 37746812 SHA256: 910027a7d94bcb1a30b677b6979f7f6180400c671e4d5feb51e0ff40b7776c5a SHA1: 1ae577b82660e1dfc121507d0df853c71e9b1122 MD5sum: 2abad85044629b1a60397080164b0ad1 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1449 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: devel Filename: pool/main/c/condor/htcondor-dev_8.2.3~dfsg.1-6~nd14.04+1_amd64.deb Size: 264042 SHA256: 9dc038b884082f9e3090c731abc202c4adceadc3f2dcd29f1def12da526c0692 SHA1: 910fcd8cfa68adfa62fdb030f6068d26adaf2454 MD5sum: e697f617e195f306bd18b00d8a784f99 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5607 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_8.2.3~dfsg.1-6~nd14.04+1_all.deb Size: 1027266 SHA256: f76923613ccc0755dd5d979c17e721be2ee5408f3a272fa004143053d019d48e SHA1: 7c8995698be28af764c92b9a8798f23824fa50f9 MD5sum: b69bae82713d1c073ca663e61a8cfbbb 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: 0.10.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 331 Depends: neurodebian-popularity-contest, python-opengl, python-pygame, python-imaging, poppler-utils | xpdf-utils (>= 3.02-2) Recommends: pdftk, perl 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_0.10.5-1~nd14.04+1_all.deb Size: 151652 SHA256: 20cc65f855d2a8efe0c6b964f7a534902caed0d7bf4a14d25e53e26b7ce27ba0 SHA1: 975160d58edcc2b16da666817fbcf1508144bdbe MD5sum: 8a21546ca0990ed7753c52a9038ddd69 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 Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 9150 SHA256: 6221480f9dac530be0388cb543cb7222a71f2eeb5a05e3b7684189951be779a9 SHA1: d6e2bc39ee2ea2858d5aa50a8b825dcc1a9766ef MD5sum: 42c1f57576c0b1537c531816653e0f04 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: init-system-helpers Version: 1.18~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, perl Breaks: systemd (<< 44-12) Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/init-system-helpers_1.18~nd13.10+1+nd14.04+1_all.deb Size: 13450 SHA256: 9b738273e06fa645d7746ddcfc18257e82b1aa81991b60f4940c8336ca7c276b SHA1: a69ef0da8cacfe37a1898934c6feb74737e63597 MD5sum: c519d25c91c535528c645290c7201987 Description: helper tools for all init systems This package contains helper tools that are necessary for switching between the various init systems that Debian contains (e.g. sysvinit, upstart, systemd). An example is deb-systemd-helper, a script that enables systemd unit files without depending on a running systemd. . While this package is maintained by pkg-systemd-maintainers, it is NOT specific to systemd at all. Maintainers of other init systems are welcome to include their helpers in this package. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1703 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 297118 SHA256: 6d030c0553e1baa945c59f642fe677ad0be4430008a8015dd2fb81fa1f834f0e SHA1: 7632cbd31ec160d898889fdb5b75425078e38e95 MD5sum: 8afcac096635d33b106b8434e372e246 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: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 904 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_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 275414 SHA256: 754e31a708bc0cd4f1aff28a1e297e0cf08102493024b7a8c1543db16dca37be SHA1: c2f9723b2bcaaca0ac1c1fa728bf022cf8b1d5a3 MD5sum: 502efd9b79d91c47d20d34546bae3e13 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: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 373 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 75796 SHA256: 3b5e0aa194d197231fe427d593a951bf08ad24ec00ebcbc74676344b1f7be897 SHA1: c2f14a58813e26e34883aa060c99d421c4432446 MD5sum: e8608d7ab133b761c3e75c561a2396cb 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1380 Depends: neurodebian-popularity-contest, libclassad7 (= 8.2.3~dfsg.1-6~nd14.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_8.2.3~dfsg.1-6~nd14.04+1_amd64.deb Size: 237856 SHA256: 7c215f4586d68cf9729b354fea25c78567aff0e2b8539c64af3f9ce89343346f SHA1: c042387cc0bc093e469bc81ed34dbf38c4ceb340 MD5sum: da92a730e8c110c6b3e7600e0e5a557e 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: 8.2.3~dfsg.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libpcre3, libstdc++6 (>= 4.8) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.2.3~dfsg.1-6~nd14.04+1_amd64.deb Size: 189410 SHA256: 2458078ce05f6aff7da3fe2a02a230b11598d8e5dd5d234310da1770184f0067 SHA1: c3d2ee3d9d807f1ca7a5bddac74c3db93ff0eb6a MD5sum: c3b43f7862738baa5fa5d1ace9f9875a 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: 2.0.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 265 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.6), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.0.1-1~nd14.04+1_amd64.deb Size: 76728 SHA256: 733938362396abb3ad5808a5a407735bfa00767936a22afd0d2a2f5076e422fa SHA1: a4e6b342b1214af03c774efb2b01c791f37a37ad MD5sum: bb6875d1aab2d39f1a76f997c5a0167f 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: 2.0.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 110 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.1-1~nd14.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.1-1~nd14.04+1_amd64.deb Size: 20990 SHA256: 81538e4e2c286c3cb07b1a493f354420a23ed5d591e9a9475394efdaaca751a2 SHA1: 91c7d2b1f50c43731dbbad21c124dcfcb1e8cbde MD5sum: 291c3bf828a47a07befb0e4087969875 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7258 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd14.04+1), libfreeipmi16 (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.5-2~nd14.04+1_amd64.deb Size: 844842 SHA256: ebdf6fe3022507e57cb845e9ae3a1f533c254e2801f9952523a8dc1932c4c037 SHA1: a89b747b01ec7e8935cc2a4f34786249ed2cb69d MD5sum: 02a6e18bcfeb048cb606d659a75d2088 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4670 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt11 (>= 1.5.1), freeipmi-common (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.5-2~nd14.04+1_amd64.deb Size: 744052 SHA256: 23b8856cde180f9816aff06126e7e50e79c4420b06f382a14535faff7b9e083e SHA1: 6314acbf85b1339a1e05d69b9507669c76a92f8b MD5sum: 1a09f9dfdb06977b71a01d71458a2d19 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 87 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.1 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) 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_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 30362 SHA256: e8a8979b41d42f21b5b97130000fe360e9f66167623847d4f608ed614973339e SHA1: 30ae50a5ca361259407c276744468cb25ac0c514 MD5sum: e3bbfab7afe5a2b1737974519b07085b 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 6982 SHA256: 9af689757ee037f8d34358117b56a3b860ae8c658581fe6d8aa1f67d9d86e428 SHA1: 7f132f0f869dc116264088caeff64e5975a4378b MD5sum: e440d2135b0ae4be83af900f7fd32e2c 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libfreenect0.1 (= 1:0.1.2+dfsg-6~nd14.04+1) Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 15816 SHA256: c6a6c188ce07944fca57eac5322814bec9a01ed2844456fa0cab55c25647fff6 SHA1: cfccc02453f41e7da72fc64a7cfe259aaba1d2e2 MD5sum: 81b6239034f47a321444c388225dd083 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 592 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.1.2+dfsg-6~nd14.04+1_all.deb Size: 81624 SHA256: df19e1dd46b09ddc473c299b3683291b50a49cfffbcfffcd9eaad334a024985e SHA1: b8e22475326b83f36d4ca0dbcf1dea85c0109a03 MD5sum: aa0821d2cd61753792fbbb8f8f11d243 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: libfreenect0.1 Source: libfreenect Version: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libusb-1.0-0 (>= 2:1.0.8) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.1_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 30900 SHA256: 3014bd91b27661b8e78e85d88b79ad57843f9597a340d67f4df1cede160ad936 SHA1: 31dbd78d5e219b8472a869aea03706c971523dc6 MD5sum: f427bd0a8aebd1daca206c522752b725 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: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 632 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Suggests: glew-utils Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.9_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 132134 SHA256: c9d01e14e16796de8ba59168f5e2aca780f731df4569da1fe4c3427ce2ed47ef SHA1: f7d204cecb486680a636592eee7c5020f9af12bc MD5sum: 4c2d98b5e4c71f0d37adbcd029e55a88 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 33318 SHA256: 39cb64ee10450cb843cf341cfed96a6ae490a2fb91eaf50d2459ea9a5d156b97 SHA1: 60942982c2309725027facd8cd61e1d8b6a8ec8a MD5sum: 6e2d32defc57216e0a5885c9b392f8b0 Description: OpenGL Extension Wrangler (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglew1.9. Package: libglew1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1), libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.6-dev Provides: libglew1.5-dev, libglew1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.9-dev_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 109474 SHA256: 630cf44db5cd23c0b913225331431705c58e310f293b7b8cbc40f4d6f32f9bff SHA1: 2ac1f8b231e6bec9f937cc4a4ebf672fb17c24b2 MD5sum: 5023d2f6c7dc5fd7afd46ecdf1e2e7b8 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development documentation as well as the required header files. Package: libglewmx1.9 Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 555 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.9_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 119768 SHA256: 615f9882dbefc47d58b33c13b1fb40573606ae61d3d9e0527ef23ed201acb217 SHA1: 758dfddec881f59d3389baa2949679ef803c74b3 MD5sum: 599349c7537898948cc5c8ba52c53858 Description: OpenGL Extension Wrangler (Multiple Rendering Contexts) For more information about GLEW please refer to the description of the libglewmx-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 122 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd14.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 26922 SHA256: af29d359e95ef29914bf80431b89c58dbb22dacec1c02261e007a9a4c93309dc SHA1: 350a78d68ae9a41dd06343c4a5482d2e30285b6b MD5sum: 42bdd9efa582d1267576c2540be87444 Description: OpenGL Extension Wrangler MX (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglewmx1.9. Package: libglewmx1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd14.04+1) Conflicts: libglewmx-dev, libglewmx1.6-dev Provides: libglewmx1.5-dev, libglewmx1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.9-dev_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 8464 SHA256: 540da779ac116c49b30950b1188b32cdc087e8245e5b32de7fdd33cec0c2ef96 SHA1: f382c52feab3fd897d893b91c948d4481a6646f8 MD5sum: b301bc39123594c1dc7e7f1dd44b24e6 Description: OpenGL Extension Wrangler MX - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development libraries compiled with GLEW_MX. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 495 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd14.04+1), libipmiconsole2 (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.5-2~nd14.04+1_amd64.deb Size: 98338 SHA256: e400374f35e9356be74ae5d8b031e11844c28d9a2db22ccc7f9a9ca2f1490f26 SHA1: 62d666573d2bf1f1284715e23f00dfd913c2ffdb MD5sum: d73b2f41e4942809914b35a89e6175a1 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 246 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.5-2~nd14.04+1_amd64.deb Size: 82746 SHA256: 02083207ed804f9fc79e10b1e2fd0ff703bc4bd0c211fa53bb70e2460891ca26 SHA1: 29277034a387ef35275e1ab575c5b3f279a05faf MD5sum: 6184c6c8cf85327775eba3b30e65b1d1 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd14.04+1), libipmidetect0 (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.5-2~nd14.04+1_amd64.deb Size: 30972 SHA256: cc37a4d8c6a0ee31add806a16473676f2af28b1241dd0d7489013d3ea571d671 SHA1: b98b6429728f6d96209359d47371e8a94660f0f9 MD5sum: 93f011978a19fc059b4b4339f69d164c 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 60 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.5-2~nd14.04+1_amd64.deb Size: 25094 SHA256: a12ef1a6813f259d499faff026dbb8d0ca2a88f515eec9d5c38265d61b0655f3 SHA1: 461137d39de85d38c839c9d722391312337202c4 MD5sum: d882edba98dbc59d49fef4c7fd735cdf 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 301 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd14.04+1), libipmimonitoring5a (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.5-2~nd14.04+1_amd64.deb Size: 59924 SHA256: 00d8fcf3014b27034d57cfe401d9ac102c9b9bbefec80cd9cf20a727161c4611 SHA1: 471da4b7e9e2b13c30074518ced7d8baa8d341fc MD5sum: dc5b68b4674330ccfc0cfc5a4600160d 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: 1.4.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.5-2~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.5-2~nd14.04+1_amd64.deb Size: 41880 SHA256: 7bc2498a7d26999042c2b9fcb11c64910cdac7b43fec509d26d5505a3556668f SHA1: 464bd94982e2efb0355e4ca2bdbc2bedc62168d0 MD5sum: 344dc85993e63edf740e28df40931216 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: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24649 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-single3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp8, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 3734542 SHA256: 981545de2b73a039eb9073bf10bbb8c0e425343a5edb704b2fb141b6c0d69fe1 SHA1: fe67413e2998e17403c9163b81135e28259b0ad9 MD5sum: 54df8b6868cac79254b79ef059d59c31 Description: library for 2D and 3D gray scale image processing libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. Package: libmia-2.0-8-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67813 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 61603414 SHA256: 7ac528603e32723704cfebbc007b20b71745ee852b60e1d5685846e27159b703 SHA1: e12d914bea050a7b92fed6e197863fb29a918100 MD5sum: 195fe8e8322d6d67b62941f0379de88d Description: Debug information for the MIA library libmia comprises a set of libraries and plug.ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. libmia is library for general purpouse 2D and 3D gray scale image processing. This package provides the debug information of the library. Package: libmia-2.0-dev Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1087 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1), libxml++2.6-dev (>= 2.34.1), libitpp-dev (>= 4.2), libtbb-dev, libgsl0-dev, libboost-all-dev (>= 1.46.1), libfftw3-dev, libblas-dev Recommends: libmia-2.0-doc Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/m/mia/libmia-2.0-dev_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 170596 SHA256: 5320ef58eb4af06b42d24ab07eaf7c6ddc3f34e79c6dd662a9b108986498886e SHA1: c5b98a8c4b87ff8c0eb34fe7ec488ca1132bf91c MD5sum: 8c93b580ebdf71723b3856c55547be24 Description: library for 2D and 3D gray scale image processing, development files libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the development files for the library. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14003 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd13.10+1+nd14.04+1_all.deb Size: 828262 SHA256: b80877b4eb7ac26a8d128219be2df273b0d1115bdc039118aa39f0928a03a878 SHA1: 4f2d66594f12e0670fb739d4c7333bd5ffce4b44 MD5sum: 4880b2c099431c4b8afaa3e78dee6e67 Description: library for 2D and 3D gray scale image processing, documentation libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the Doxygen generated API reference. Package: libnifti-dev Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libnifti2 (= 2.0.0-2~nd14.04+1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-2~nd14.04+1_amd64.deb Size: 136386 SHA256: 5d3b9339c30c1b37e93d8d1e733884d17a28843c2c890594f99802028b172b6e SHA1: b091aa4daeb8854a3fc9ebfc2e5b4b370d3b5625 MD5sum: 447591c46fb42def7965b9647477f7a1 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1675 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-2~nd14.04+1_all.deb Size: 137676 SHA256: 3bab4349c0f35948663f799794b88328b12952dbb9eadb0e8a4085c0f270a5e6 SHA1: 8efa4c33a93f08cd665a505ac7aa01ce2a943db6 MD5sum: b29b153538f23cfdeddd32fc9dab6436 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 298 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-2~nd14.04+1_amd64.deb Size: 104646 SHA256: e93ecf3b7204191022fbc826cd7b9d6eef51696a51c941ea4e810d7a88d07068 SHA1: 4f8cc483b111bf5c27ffaf3bad6e20ae4cd0c954 MD5sum: 31adf0822b3af48f98e47e489f7fdcc0 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6371 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.54.0, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph99, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1226316 SHA256: 609321d47fa9bb92fe3c847c3de68ef910dfa3ca650317df024a661cc5c6ff60 SHA1: e341ef3c136c37f5bedd103d1eb3c3a100cd935e MD5sum: e8d30adf4f894a6cf74ea2d4530bb2bd Description: Framework for multi-modal medical and brain data visualization OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 3.0.0), libopenthreads-dev (>= 3.0.0), libboost-dev (>= 1.46.0), libboost-program-options-dev (>= 1.46.0), libboost-thread-dev (>= 1.46.0), libboost-filesystem-dev (>= 1.46.0), libboost-date-time-dev (>= 1.46.0), libboost-system-dev (>= 1.46.0), libboost-signals-dev (>= 1.46.0), libboost-regex-dev (>= 1.46.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 248388 SHA256: e1979f9ff461e4bd26b952e587c879464abc8805dde53b924226a1ba9957d869 SHA1: 8c707227d4e9a7783e77c11be320df628235fc84 MD5sum: 035d7cfb0b5854d0eff0e3f0039076a8 Description: Development files for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48075 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_all.deb Size: 2673508 SHA256: 6bfe8da2878784c3df24ef11993ad9d5b82019204eb362235bd094ac6865c0f8 SHA1: 714ad73ca23e5c34f65c7632c395534c4baf7898 MD5sum: 5f8cbf8fba45be0c2da0d39481c9c931 Description: Developer documentation for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 141086 SHA256: bb6124e7796fb2ec46a74995397dfbba18312339ec0fe849049b3b5bad060be3 SHA1: 116a59cad5a4eb2d9003e5e76551b38398a4e22b MD5sum: b2061aa60168de0aaef2c3828f277f14 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 141822 SHA256: f4b913b3478d86cb08b8d3a2869e1636a68e516d4f49df98c0c622b8ab3a9925 SHA1: 9bbe3595d3c1bbf9a3ca4db616135dc92ed9a942 MD5sum: b5eaf8376256f9d11aa3ddcd0ff7bc4d Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1311 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 325046 SHA256: d7007f17f588ef2f5e750af1c6cbff2e208445bdb6520bbfe25a92dc002edfd3 SHA1: bef37b08a1545e5a98c666e3d9fb32ba4c52657a MD5sum: 25d6934e9b0a01219311a6a8c86de7d3 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: lua-cnrun Source: cnrun Version: 2.0.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 105 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_2.0.1-1~nd14.04+1_amd64.deb Size: 38404 SHA256: 2fb891a9531c193709cb231792e0a42a104a9966baa452cdd7d6c05cafb7d207 SHA1: edf87b1abbe82048df893bd528e884777543b127 MD5sum: 02a22e592aa0aa43161a70c233444016 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: mia-tools Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8458 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1), libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1438058 SHA256: 4175b7c0f2fc73d3100e6f0f05e946c559120697c9f092ff25fb2d7c59c02245 SHA1: 4674acee003cf4f21651daa385d4f6fbc19f550d MD5sum: 70ea147c6b5bab34fad8f1b2e394e3c3 Description: Command line tools for gray scale image processing Command lines tools to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29921 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd13.10+1+nd14.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 27660152 SHA256: 2cb6d437d0283d982b4a69681b6fd85b49152794f3780d90bda5b70ed705c39c SHA1: b034979d96b59da1e938cc6099f0a6aceb4af28d MD5sum: 47578d4bd436714a8b039345556cde28 Description: Debugging information for the MIA command line tools Debug information for the MIA command lines tools. These tools provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1138 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd13.10+1+nd14.04+1_all.deb Size: 71894 SHA256: be1b730b60e4e46c09f731c458418f51468a54bd0bcb30c1b3ae62895cf5195c SHA1: 13b72c29850c963b4b7163d5728101f262982fad MD5sum: 68aa342ecdbdd76b549b62f3a8a0cefb Description: Cross-referenced documentation of the MIA command line tools Cross referenced documentation of the command line tools and plug-ins that are provided by the MIA gray scale image processing tool chain. These lines tools to provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes interactively from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statistics over images. Package: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 16024 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_amd64.deb Size: 2205714 SHA256: 471e4b106f893910fb05163a0ed70cf8550005bfdac8f15b689dc8d487401127 SHA1: 7db3a7a792d8498328ca7a7e4d02123f18fe6fe8 MD5sum: 262c81c3fa6e174ea44c25a69a5a7ae6 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1708 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_all.deb Size: 1658672 SHA256: 8c6fbf4d4201736009058951a8b0a0649b14eb2b31222086e4c40337b7b701fb SHA1: d390758dd46655f60156a87578c4e8bde2f62f7f MD5sum: 5c2f269adc054ae2960074a3cfec33ba 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1019 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_all.deb Size: 577154 SHA256: 99c69da1658d3ad0d38a2e617b99c1e97b6dd659de73b4d17de6abe2c836bee6 SHA1: 40d30c9da283129d64c2490423bc06de65605f3d MD5sum: 1e4972d196978a16b51c6ab0b5170a0b 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: mrtrix Version: 0.2.12-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 8802 Depends: neurodebian-popularity-contest, libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libsigc++-2.0-0c2a (>= 2.0.2), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.12-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1300186 SHA256: 551f98c5ed01a892ef30be69dd2632ca751be0a4c51bd2663478342ce4c981fb SHA1: e4faaf5483942391f9654b34ab335502b8112873 MD5sum: f543ec275d3ade8d4abf6e9d3f90a694 Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.12-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3490 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.12-1~nd13.10+1+nd14.04+1_all.deb Size: 3191882 SHA256: f32e1267d094094ab3cc0c0dea48e1ccf69fe473877e2e60136e4e6a27db354b SHA1: 31f466b044fd9b37817cda76e708ae9f65413a1e MD5sum: 391268dd332daa65f1524ad5d28fd893 Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: netselect Version: 0.3.ds1-25~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51 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_amd64.deb Size: 30902 SHA256: 85bcc0cb531b5e144101ecf8b3356e798ea1e256a212e6a395fe67f1191735d3 SHA1: d445f87a02a6be7f46662b4062087edb12adc3f9 MD5sum: 31e70fcb2d00e772f027e762c0d3f2fa 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 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_all.deb Size: 16732 SHA256: 6736e45053839e6ccff6ae6acee08c1b6946082a3551db89f5b75cf011f56942 SHA1: 5459e0e22973aeac24902aeb831afaca776152d2 MD5sum: 27d1f7525d5b1676fab50f43523897b3 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: 0.34~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 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_0.34~nd14.04+1_all.deb Size: 20130 SHA256: 26acd7fb0b1babef2f0926043a2828c864cda9c888a5c1c5b633c8fdd1a91c55 SHA1: d4b26ffa52859ca3129c943d66d95a4eba398d76 MD5sum: a79e9a3de0c34cdac9189badc4377c0e Description: turnkey platform for the neuroscience The NeuroDebian project integrates and maintain a variety of neuroscience-oriented (such as AFNI, FSL, PsychoPy, etc.) and many generic computational (such as condor, pandas, etc.) software projects within Debian. . This package enables NeuroDebian repository on top of the stock Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.34~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 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_0.34~nd14.04+1_all.deb Size: 9066 SHA256: 58d41866e436036d07debe2404c8cf3cac8571876c99c740297e89ec894ad485 SHA1: 927ec9b54334b655d3f47336b963ad2e97a17c83 MD5sum: 2a09c396a0fa22ed7acdab13350bebdc Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.34~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.34~nd14.04+1_all.deb Size: 114594 SHA256: 1903d3884c878f619467d29b60b9c8048b6dfa532cfd6b87f110b9b3b16b2150 SHA1: f027fc293da08ddedf4be6bc6e4ba2ee4c739ebc MD5sum: 540d72c3bca34b37301845ad0ac83d26 Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.34~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: devscripts, cowbuilder, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.34~nd14.04+1_all.deb Size: 30882 SHA256: 299a7cea710d5483461c6d53dd92a3e3df6f918e0587f1a428cf5e88bfe12328 SHA1: 3994580f5974e44ab3356a462f9fb1e8a91a5e3b MD5sum: d34af390ef9dcd01ec4c6b5724324486 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.32~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 108 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd13.10+1+nd14.04+1_all.deb Size: 14088 SHA256: 97679301db4c313bf776a5d18ff76e0b1af04b77da1156d1b500a56e308379b9 SHA1: 0b00e3321e0d1bc70c40437abc74430adcf4db07 MD5sum: f3f984c91e04f7b9ab57e22d1bb1af9b Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.32~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd13.10+1+nd14.04+1_all.deb Size: 7470 SHA256: 8da1af69542f153184f6d344861f1557e1a7a783b6c0b6d90b67e8dee8a855e6 SHA1: fc17ac754d0a08a79a0b1615c6ae10dcd89f36ea MD5sum: 341bf775ee30c2071e1c49a1acf6f88e Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.34~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.34~nd14.04+1_all.deb Size: 11150 SHA256: fa537d32580e550ef36f5bdf62390199d521faf97b070bc4908f721e284fc7c5 SHA1: 9e1f8d887d4dd299f4f818056471bef2e7771356 MD5sum: d51e943f2ac21c2fd3779370fee2ac91 Description: Helper for NeuroDebian popularity contest submissions 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 (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti-bin Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 176 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-2~nd14.04+1_amd64.deb Size: 55030 SHA256: cc5d92fdc77db140778d10fa11b5be665d4ae7faf54ff5f11b54702233bad5ac SHA1: 0d232196b8834b814ad82fe1a16fea494d5dcd76 MD5sum: c631cf7ffa6357a737832af18b7da9cd Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2231 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.8-1~nd14.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.8-1~nd14.04+1_amd64.deb Size: 333798 SHA256: 2e9d69cd17909b449a522ecc2f68f64bd477423aa664f70f765e3233556417c3 SHA1: 913f8a536decdd3ecddc47020b528ebc07356e85 MD5sum: 936334bcabdcd45977fe4d9dfb3cfa06 Description: convert 3D medical images to DICOM 2D series Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package includes the command line tools. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 606 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.8-1~nd14.04+1_all.deb Size: 615402 SHA256: 5c0c4de741d502aed671afa90ffd5f9d83bbb8d9b8fe3fb61e87a83207c51387 SHA1: 1e2cfa4676c02305b4cf2b7c081125917e51667b MD5sum: 35e250c61104ee3c777aa9d7ef48b08f Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nuitka Version: 0.5.7.1+ds-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2266 Depends: neurodebian-popularity-contest, 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 (>= 2.7.1-0ubuntu2) 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_0.5.7.1+ds-1~nd14.04+1_all.deb Size: 525558 SHA256: ef528cd005be6a0f9a11f47b5ee8b22d35e6b270350eae7e75bfc1ba9d142ab5 SHA1: ef01cf57e2e8db8ba0706808e86f40bc50bd5454 MD5sum: 08565abfe4c5ca5074021ed56b403c87 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: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.14), liboctave2 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 19312 SHA256: 844b209936f86b1584cb1fe781eaf56ecd17f2d234c6b5de10865297cbcb95dd SHA1: 7021c8a74d89c91d301dc2607323abe488761caa MD5sum: 163db5c5f556a12f4919cc618cfa4ea1 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: 3.0.11.20140816.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2835 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.2 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglew1.10 (>= 1.10.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), liboctave2, libopenal1 (>= 1:1.13), libpciaccess0 (>= 0.8.0+git20071002), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.11.20140816.dfsg1-1~nd14.04+1), psychtoolbox-3-lib (= 3.0.11.20140816.dfsg1-1~nd14.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.11.20140816.dfsg1-1~nd14.04+1_amd64.deb Size: 609028 SHA256: 16f6be95e48a29d3ba3ba06b8768ddd57b4d42b8ca976a07bba5f97bba053580 SHA1: d7f027953e4f9898a637334a0d1ab7875a7d8883 MD5sum: 43c96395ab698980774686f4922e15ce 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: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19512 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph99, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 3331020 SHA256: ac0352d0c0475b930bdad2f3733fb5b4c6aa9cc1c90e1c07e5eefa7db7bcc976 SHA1: 1205548c7e07fc9ce38ca584665b5c4ec9d5721a MD5sum: ff72e5fcf6b957018732a1eb23d980ae Description: Loaders, algorithms and visualization modules for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1955 Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-program-options1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libopenscenegraph99, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.6), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 733244 SHA256: ed0d1ebf8644abd66f1d5e249319194cd42d32b4e20861a438c1438bdc0cbf81 SHA1: 1bab7b90c4d01b7c7d7408dbcc7828d55c0b9183 MD5sum: 9edda61cd48fb5debdf4be31ed0ffd0e Description: Qt based user interface for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: psychopy Version: 1.81.03.dfsg-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14328 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.81.03.dfsg-1~nd14.04+1_all.deb Size: 6042634 SHA256: 2e6dd46ce0bdce7b4f6110dc63cf0f2965e1f57d3d2af45227337a36062e143d SHA1: c14895d347a969a7c479d7dc9420d35cf88446cf MD5sum: f582b3c7a65de6d6de9b54ead8926fe8 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: 3.0.11.20140816.dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58459 Depends: neurodebian-popularity-contest Recommends: subversion Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.11.20140816.dfsg1-1~nd14.04+1_all.deb Size: 19222842 SHA256: ec457f15991824c506ca305147b53ef1be6befb0b5f94d50e0e97a40f2133175 SHA1: 5fe1e0eef2380fefc0439050c945580e590694b9 MD5sum: e39a1a2bb16605ad54a9fdbd28f68a03 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: 3.0.11.20140816.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2275 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.11.20140816.dfsg1-1~nd14.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.11.20140816.dfsg1-1~nd14.04+1_amd64.deb Size: 476254 SHA256: 4ac939095b93a661b033c8f939c4960ce6e9c18a0c2868cf35cf629f4cd1f603 SHA1: 1f87b8235c49f6449c251a7c7dc155fa7b185fc4 MD5sum: 6fcd8918db845282141adca25e381f47 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: 3.0.11.20140816.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 153 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: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good, gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.11.20140816.dfsg1-1~nd14.04+1_amd64.deb Size: 54414 SHA256: 495b9ad9c809ded51fc5fbd383fd6ec8bb7217337aca6be3313407efc84c1536 SHA1: 30aa3be8d5cee014d6a4fe0bfe0c595705895255 MD5sum: 2f4c72d884dccdd20c461de32584080a 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-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 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_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 42858 SHA256: 36351c23f2c4b8ac837ecdb2287a85e8c4e7669dddd4ee1442e010d0a82de207 SHA1: 66798a5de9053e72f8778c8d0f09f16e4691f914 MD5sum: 74079f4cbc088e17028018446f4bcd9a 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-brian Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2336 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) 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_1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 399980 SHA256: 9b102fb44ba8ef99f962b24b26d8728f156056718f3eb9623913fc7b7caba662 SHA1: d86f3a0654ed4295d05de2f18f0eeb913556a87b MD5sum: 09ddbc80109b6a58ee6b674f29e7951a 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: 1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6821 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_1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 1974362 SHA256: d9c426b885976a7b29dde32cf747a24871a7a3635002c278e935eb11c57af91d SHA1: e20e051b8a911939382513cd791a53912f7cb300 MD5sum: 8fcfe3c4554b2af0690ca333000ca2ac 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: 1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 141 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.1-1~nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 40218 SHA256: d86bbcc1ab8c0d6e33e1e5df464252ea4e30013b55df6410246a13b0b3d54520 SHA1: a91e459d20cfadfd098624ebd0fc71f4bad96b50 MD5sum: 6ff13a3e0896da753bc146bfdc4299f5 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-dicom Source: pydicom Version: 0.9.8-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1784 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.8-1~nd13.10+1+nd14.04+1_all.deb Size: 357388 SHA256: 91219b2707d65b9c90115e228f0b7436b504a73b77240f30a1c9b83d28e8306f SHA1: 9a0c1416a19680e3f11e6a20f05a6fd4a8715ed6 MD5sum: 8c08ac8bc362936c87c2027a4b407bdd 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: 0.8.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4493 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-dipy-lib (>= 0.8.0-1~nd14.04+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_0.8.0-1~nd14.04+1_all.deb Size: 2318362 SHA256: 18527207eee27c67c9b579c87adf226c2e233bdb38dcc497126bba53265f4c88 SHA1: 8fa7e3b6749fef2254f9bca92b582c27fb97958f MD5sum: bbb3d39af1a9e7c36c20aaf88dcddc61 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: 0.8.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11670 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_0.8.0-1~nd14.04+1_all.deb Size: 9427738 SHA256: c64c21e0ca933c562ed9ec93db06d17e4d71f4ff580fefddeaee6940e51550ac SHA1: 648c16c93176db91e5dd0eca46f4eaa095c1b7a2 MD5sum: 4fc9ef9bbfa7ac496455bd3da15ae97e 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: 0.8.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4166 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14), libgomp1 (>= 4.4) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.8.0-1~nd14.04+1_amd64.deb Size: 781864 SHA256: 9a902626b31e8b93547e8cbaa385edb99e443681aa4ec7ed13d9e50e6ea97497 SHA1: 9ff7ee899b65374508bfb904cee12ac3e329dd52 MD5sum: f8abef11320c4c568528841ee3de27b9 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-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2388 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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_all.deb Size: 695948 SHA256: 37604b739e17ae561b68e1ffa8fd89495abab699acaa75ce4a4160ab0e9f1dc9 SHA1: ede08d0df1746f31ccb9eb6fbcdc49722e3b1b5b MD5sum: 95df9057ee0432389482bebb2bebc420 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: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.1 (= 1:0.1.2+dfsg-6~nd14.04+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_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 39056 SHA256: 76e9679fde400100dc84dd94c7975cc969864e8db3fa9cf6802d67ac92f52b0d SHA1: 03c16a03a1890dbd7395ec34bb400def7f114ea8 MD5sum: 0069be714ba5cdc9a98aa8179509979c 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-jdcal Source: jdcal Version: 1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python-jdcal_1.0-1~nd14.04+1_all.deb Size: 7670 SHA256: 1f7d63bfde1855c23e02ebfce05181789c84b273daab7ea32c66f78b1cca884e SHA1: 9d0226fb987ab11a64f01766cf92eacb9543bd28 MD5sum: 35bcdfe5fe51152dddaaaffafe9b8576 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python-joblib Source: joblib Version: 0.8.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 255 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.8.4-1~nd14.04+1_all.deb Size: 64348 SHA256: af190164dfa78380c0f09e17abb4143cd96312695de7c849d2468a46446fe26b SHA1: 5105df1b9af025fa0dcf48be4cd6d27a43501320 MD5sum: c1c44061113eb2e13c619380ea2c22cf 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-mne Version: 0.8.6+dfsg-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7181 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.8.6+dfsg-1~nd14.04+1_all.deb Size: 4021862 SHA256: 671246db49db07372b109782df562aaae4fcf1f64ed9d2c7d1ec631ccfb74b96 SHA1: 4706eb6d66ece935d20bbdf9cff1bf1c06636379 MD5sum: 54123e86d60e9e3b0355eae25a35ca58 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: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1292 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 308978 SHA256: 5d75b43e467de9a440b92c38aa21fd50b7200e1d9d9c4c765c8e00fa28e12d5b SHA1: 1e8f375529f499dc35686aa000a8f274d5f8b43c MD5sum: 9dbd82c96b890c7215da1337c8caa484 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: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5329 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 982798 SHA256: 5d5ed98cdb7c3afaccd197b2f8aeebc7d21d5a64f3359eba56898baa6d9b4112 SHA1: ac67a1309bc3f5f3c8c642416090d91de31e9a9d MD5sum: 3277c46895c12fb5b686fafe2ac09573 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: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 257 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_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_all.deb Size: 52650 SHA256: 89c6b2097aa4c46452fc4c94f25c9552c6bdbb11de0b74d3499a9fc731fcb138 SHA1: 180f3b068696bf9372da2ab0ebdeab29e18a44c1 MD5sum: ccd5f97d5b5360920b157174f29dcace 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-msgpack Source: msgpack-python Version: 0.4.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 171 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14) Breaks: msgpack-python (<< 0.3.0-1) Replaces: msgpack-python (<< 0.3.0-1) Provides: msgpack-python Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python-msgpack_0.4.2-1~nd14.04+1_amd64.deb Size: 53230 SHA256: a0a64aeaf7f04032415d296fede052fdd443cc87f4cc2f0562325b90b751c843 SHA1: f8523e8e12370630fdf373136a6c343d8dbb7cef MD5sum: db115976cf03862280db72ec82aaf506 Description: Python implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python extension module implementing the MessagePack format. Package: python-mvpa2 Source: pymvpa2 Version: 2.3.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6458 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.7.1-0ubuntu2), python-mvpa2-lib (>= 2.3.1-1~nd14.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, shogun-python-modular, liblapack-dev, python-pprocess 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_2.3.1-1~nd14.04+1_all.deb Size: 3684314 SHA256: 89058980b2241508a5c38ecca7b6ce5d83b4f69cfb305a8cdd250ab235f2f55c SHA1: d820614dee9226565deb95dee9243197798988a4 MD5sum: 0f99a985742a17cb761b88a2ed3587b6 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: 2.3.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27622 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_2.3.1-1~nd14.04+1_all.deb Size: 4511476 SHA256: 780a40e6d583db7a6199380b73e1cb6690c9c0b1955aa1b7cea3a52bd661fe4a SHA1: ee152b7296927d11ace4831a2e1abfd1ad75da17 MD5sum: eb9c3ff87c38f99d1c01fcf3bb949cd7 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: 2.3.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 114 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_2.3.1-1~nd14.04+1_amd64.deb Size: 44510 SHA256: c40b313b795d90ea2588ed7dc3c709bf76456ba7fb0c91fe206802ff11a7bdf9 SHA1: a085b91201a6c4aa0fd5ab6a39efd8c1d6811193 MD5sum: c6aa2517a84625348bdf3508e1cc517e Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 28812 SHA256: 15d6ad200903f48f7d0ac38e08d3aea9a417b73085929fcdacce541b5ecb0f05 SHA1: ab997820ecbef62ee9805767c8810a4a4663c6a4 MD5sum: 6ca9dceaed50e4921f7759c6fe0b948f Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Provides: python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 1719980 SHA256: ee744c5748b3d2cc5a8c7241d76198227c788d51f817108e01533f8ad9c91f72 SHA1: efbe4d81861db1ff40dd49ac92757b7c40944e30 MD5sum: 143b3deb6c33f6af87d90167c6039312 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 Python-Version: 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2452 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 361828 SHA256: 327f4c0f8751aebc623aac350b7298edccad690fb84848ce299e9f759e860673 SHA1: 4af73218d9a6aec7440962a8bd511f6ea0e7ca92 MD5sum: dc8908929e75c6f5a7d48f2868187e68 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-nipy Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2953 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-nibabel, python-nipy-lib (>= 0.3.0+git262-gbb838d7-1~nd14.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.3.0+git262-gbb838d7-1~nd14.04+1_all.deb Size: 723360 SHA256: 9e3c2ae899faf3920f66003f1311689b96e17352ac55a9684611d80dfd63e878 SHA1: ebaee3a20531d25fe59e8903b2999c9e889fabc6 MD5sum: f8ae83557d9bb61ee81fc7d1e20d6085 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: 0.3.0+git262-gbb838d7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7995 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_0.3.0+git262-gbb838d7-1~nd14.04+1_all.deb Size: 1142090 SHA256: 3437ed7d6491ff3082554ce73985c500339cde50cb407c51ba3fc774f5d2691e SHA1: 0e211e07439d4e3593742f8d3727ce2d2569b762 MD5sum: 9309cdf86776c79bee31e67e1ba1ad93 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: 0.3.0+git262-gbb838d7-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2402 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_0.3.0+git262-gbb838d7-1~nd14.04+1_amd64.deb Size: 560684 SHA256: f203e7c274e062095c07400c0f9d01d618e76d8f654ce3a7447cef22742cab1d SHA1: ac92026aff6fdbe51423611a4234f37ffc6837c2 MD5sum: 5681f5c6c715fa28a964fefec2bce903 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: 0.3.0+git262-gbb838d7-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3577 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 (= 0.3.0+git262-gbb838d7-1~nd14.04+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.3.0+git262-gbb838d7-1~nd14.04+1_amd64.deb Size: 605648 SHA256: 97da94538c4bb2c2ee9e8a7a7ee95ca1b3b6d2383c2e6de060bdc921d6cf6e29 SHA1: d77da249855c4c107f994645ee37eba34d377b11 MD5sum: ed1932720916d7d98d8a6a63ff391ec7 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: 0.10.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4573 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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 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_0.10.0-1~nd14.04+1_all.deb Size: 1158946 SHA256: 39836fcb648f64546c684c1831a50292c701b204b127ee8ea9a3ac3d162dce69 SHA1: fc0b5f3620bc163b435ce94c3537f601bd89ce0c MD5sum: f56846a6794f64b052f434dac5e5e4ca 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: 0.10.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20779 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_0.10.0-1~nd14.04+1_all.deb Size: 8759220 SHA256: 4b2c7602f68541b83fefb69f9e2b3277109f40fb53ce0ab93fffdd461303f5e7 SHA1: b5dd929f7a8df02f697c2ca7e98fc28cf8f1e95a MD5sum: 91069fca772934ae6d749a309252bb74 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: 0.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9348 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.5-1~nd14.04+1_all.deb Size: 2543180 SHA256: 4e7fb89d19eb0ea03cc9f7f5250620dff4f2d761927f03cfabb3cc68ad11a3c3 SHA1: e1fff7796a91f419a4a8333e365ccfa3bd6dcc14 MD5sum: 30f8838e072e488df104ebce556dbd3a 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: 0.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7695 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.5-1~nd14.04+1_all.deb Size: 5725954 SHA256: a99fe69605554c7fcecd941e29ad9906e9ce7e566a590d862ce4526048878c49 SHA1: 16bdfb5d90abff3b774016371686669a3df32fad MD5sum: de116c3ccfe8fb5cc2cb69458c80cc2a 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-pandas Source: pandas Version: 0.14.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8918 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-dateutil, python-tz, python-numpy (>= 1:1.6~), python-pandas-lib (>= 0.14.1-1~nd14.04+1), python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.14.1-1~nd14.04+1_all.deb Size: 1250804 SHA256: 2e7821948f7b793f7309b04041fb1dbb00eda43529acce534c2ac6c79315d0f6 SHA1: 10a08107031ac2dc0e2158a2c33ff584d8ee98a8 MD5sum: 367712ebb4fc8f082bf9193e48eaf2be 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-lib Source: pandas Version: 0.14.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4862 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_0.14.1-1~nd14.04+1_amd64.deb Size: 1296810 SHA256: 5923e61765dd1184f2b8a7adabbcb4f2cf8bf136f566bda2e704ee2985c06a40 SHA1: 567ac6f5b6ba0f5388d824de7dee205745a72ff4 MD5sum: ad11cc9646bc7575121190238edda568 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: 0.3.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 720 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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_0.3.0-3~nd14.04+1_all.deb Size: 162554 SHA256: 5dedc1fc454a1f938cbe4c075cda04dca81a02d99c6285d1522050af3f49827a SHA1: 82531c7115a139e1f0f76f1d33b8e9434eac7033 MD5sum: 38ee87afa0d292810409b31136bfb0bf 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: 0.3.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1244 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_0.3.0-3~nd14.04+1_all.deb Size: 352540 SHA256: a25375fcb24f4db0442e6e66e4692ef1f13c143b30ecfe4375c62ac0c679d7f4 SHA1: 7cf26c4e5b3b277a941384ac1a687e44bf75e26c MD5sum: 1547c7e45c8298fe81a121c9b97bb6e1 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 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_all.deb Size: 81638 SHA256: a3672edffea33c0135dc765fe3dbe3524115cf8cd1ae636f2bf7cbc09cfc47be SHA1: c317f00152e89dbf84b5a85ea883b44920eef65a MD5sum: 421e4d9f4c03a34b12fbffb0d0f92b25 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-psutil Version: 2.1.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 540 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python:any (>= 2.7.5-5~), python (<< 2.8), python (>= 2.7~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python-psutil_2.1.1-1~nd14.04+1_amd64.deb Size: 116160 SHA256: e18884e702b5b172fb98894fb96229a695f81a271fe3d3937f729fb6bb44c62e SHA1: 53c77e1021d97bd744b0f0f273319fbd060939e5 MD5sum: a9fa1922a49037a689110709ec38cf07 Description: module providing convenience functions for managing processes psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1366 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+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 (>= 4.4.0) 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_amd64.deb Size: 280316 SHA256: 18e1bf03b831fb92eb5c5842f0ac37626f4f4b72cd7166b5e096d7cda9bc733a SHA1: 9dc28ee207759930bfaa42697d7bd036f0506c12 MD5sum: 2f8617180be925aea587c05e501b028d 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 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_all.deb Size: 819336 SHA256: 4fd57971c92c6cd4cefaf9f32063e2c926a4cb901726c02263d9b4ea8cc24bb8 SHA1: 13d0d3aa4656070b80d4bed6e11ef0228e43b195 MD5sum: 335b1dfa97a9d8678444c11354131088 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-pymc Source: pymc Version: 2.3.4+ds-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1909 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), 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_amd64.deb Size: 432094 SHA256: d97f463e38aadff7fae263fba77e95d92398d51ddecc6bcc2f486bb13be6a451 SHA1: 021942ac580742fa889a8372a0ed5dc4083142a3 MD5sum: 7d7492482f884ea8a985db141e981bca 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1860 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_all.deb Size: 839822 SHA256: ca5b4a1c229d97f73a5efabb5bce300e4461516be6d6ca3fb09a71accd13d6dc SHA1: b7faad248279ffb84dc5464d0d050883c20afe1c MD5sum: c2f9774d355e63c5a38e9d90065b3aed 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 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_all.deb Size: 122882 SHA256: 62e294043371c55fc47adddcd8c00ee9b823bfc2885a7fe6a17545f5a9ba2cea SHA1: ac1a6014356d9f0d27fe921f17abf9a006bc6dfd MD5sum: d08fcaa0e9cdb30bfb91d7d5082d4941 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-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1595 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 331006 SHA256: 052d31fcb635f13e829a8eccfb5c81e56f6bb80ea9959feba88c783c7f3f536d SHA1: 50504f93bc680645c8cfc60dfce411486ed501df MD5sum: 05b04f538af2513542848e856c492d13 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-scikits-learn Source: scikit-learn Version: 0.15.2-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44 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_0.15.2-3~nd14.04+1_all.deb Size: 40880 SHA256: 967ee0b8ffcf0e1f0f5b741e680bab5cd631b770ba237ac1e5699139a272bdea SHA1: 5dfd7f4b844e9257766af9e7f7d384e73f0045a4 MD5sum: 085c1b7acc00de249f1805c75e08939a Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-seaborn Source: seaborn Version: 0.4.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 383 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), 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_0.4.0-1~nd14.04+1_all.deb Size: 74778 SHA256: e88ddb28118ea63bd4e588060420e0ff98ca8c526c60eb1cbc45f29ed14a5305 SHA1: 5dbca29c9f71778d63679a66bdfa690835c34a3d MD5sum: 640b8c07ec9ddef95d1f3369822c3820 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-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15134 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-six (>= 1.3.0), python-skimage-lib (>= 0.10.1-2~nd14.04+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-imaging, python-matplotlib (>= 1.0), python-nose, python-pil, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11927494 SHA256: 82c528be9e874b39de21a4bba62421c1d6bd7589c9596093dcf97becccbfa3ae SHA1: 172a2e19e17e3b5e2b165127f92fe4ef51f60003 MD5sum: 5c1c7e773ca81f8494f6b4b97e17b06d Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21865 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.10.1-2~nd14.04+1_all.deb Size: 17205200 SHA256: 60b9c823532f9aad362ddf844c783ae8afc19152e3a8633699c1b906979ba876 SHA1: ffda4a2dd76fb4d7df9deefa82715439553fa6fd MD5sum: 34188666367a224580d2a0306199c599 Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6595 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Recommends: python-skimage Provides: python2.7-skimage-lib Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.10.1-2~nd14.04+1_amd64.deb Size: 997084 SHA256: 9501af0012ef938b82e41c83c271da1ecfd4954320997db29b92cc5ec3986691 SHA1: e2d6410ecbaaf2feb9549fd33374da5c957584fe MD5sum: 688112921367a0f9422190d0dbf01fe4 Description: Optimized low-level algorithms for scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 2 libraries. Python-Version: 2.7 Package: python-sklearn Source: scikit-learn Version: 0.15.2-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3969 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn-lib (>= 0.15.2-3~nd14.04+1), python-joblib (>= 0.4.5) 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_0.15.2-3~nd14.04+1_all.deb Size: 1011128 SHA256: f28bed4332637dc4098ab64059fc10ae881dac510617c5e5112f27ead12716f8 SHA1: cb9a39bd815220aae314c3b6afddd9d0f996654e MD5sum: 70a17fb4fdfcd51bfe48f09d61865bc6 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: 0.15.2-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 66567 Depends: neurodebian-popularity-contest, libjs-jquery 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_0.15.2-3~nd14.04+1_all.deb Size: 42379350 SHA256: 3b5e5eaca5b63e9f368d67052e1c1da96b645bd374a97fcd39d3356a9de85538 SHA1: a85191aaa2d61314853c20f700cd0c1cb21c4c46 MD5sum: 56b585dc16dde146edf4a66b0f43049f 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: 0.15.2-3~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4195 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) 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_0.15.2-3~nd14.04+1_amd64.deb Size: 927032 SHA256: 4e8c9637076267b1a4a1cdfaa36bc5b823e20be17153466258ce9635639f156f SHA1: e71168b94e47a638ea47e3cbe2de00f127630289 MD5sum: 4d75fa79d9ccd660ba331fdbad450ff5 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-stfio Source: stimfit Version: 0.13.18-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 530 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python:any (>= 2.7.1-0ubuntu2), libbiosig1, libc6 (>= 2.14), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), libhdf5-7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libbiosig-dev, libsuitesparse-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_0.13.18-1~nd14.04+1_amd64.deb Size: 186820 SHA256: b9dc25af54c68ccc71d05f4cea151d4fd4854887527b24e40fbd5ed53b47c95e SHA1: 6cab38d38373384cfef3a4fa5e643e74f1a19792 MD5sum: fa4f8e0357ca41bb8c1c1de67d19a65f 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: 0.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 213 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, 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_0.5-1~nd14.04+1_all.deb Size: 38530 SHA256: e91ef2ae3278790c4c6249653e455c3b3d92162f3230d1f0d49c9a520a5486af SHA1: fd99fa261b9afb9d40da4bb54fee42a27bfb5875 MD5sum: 891bbab8bcfc7e859ad5ecfc953ef4e8 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-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 1683 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 271762 SHA256: b1feae077fecdb55e2a90d1548cc04f82558edc647f0fbf388e016b697b35ac8 SHA1: 7d7df5ea948bf2a17eecf2c7ddf9189287973b68 MD5sum: 88b09a65e000459011876c38e37de9af Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python3-jdcal Source: jdcal Version: 1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python3-jdcal_1.0-1~nd14.04+1_all.deb Size: 7468 SHA256: 94b7e4cf3470fc765314561c161e497952f1597f87ab641b702080c2dc2c4249 SHA1: 64f8dbeedd11a34c60e16344e5943e5977723c4a MD5sum: 3f05614962ed5a2ba097afe9a6646e99 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python3-joblib Source: joblib Version: 0.8.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 251 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_0.8.4-1~nd14.04+1_all.deb Size: 61454 SHA256: 77311999150d40a778fe815eca314a0ad2728fd1ae5c58b8d3e36f5b3c7b4758 SHA1: bcde7c656e13fb5bf11a25b5a83b26bc1a0a8640 MD5sum: f19c430ff021e29698784e42a66ff6c7 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-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1268 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python3 (<< 3.5), 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_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 306068 SHA256: 8bf3ac861eb683f771ac25919e67ba3ce2e516a6c959eb48d99f1c2e6965b781 SHA1: 62b98395c907e009ab81cd84e66554157ccf5fae MD5sum: caa4ff7d88aeba2bdd490c3b8d1414f6 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: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6031 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1100780 SHA256: 26e1864fc34cd5cc8abc70ad4441e529e242efd6f83829141aaf9e263e6e90e9 SHA1: e91fad9a55c55f2cbd57ca3dd549bc10e39619cb MD5sum: 57e3bc0846bae86506e429c5952c74f6 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-msgpack Source: msgpack-python Version: 0.4.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 177 Depends: neurodebian-popularity-contest, python3 (>= 3.4~), python3 (<< 3.5), libc6 (>= 2.14) Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python3-msgpack_0.4.2-1~nd14.04+1_amd64.deb Size: 50902 SHA256: 1688a260b9336841a1dabf5b562e9cee23588f578d2fd661dba17d66ab08b0ec SHA1: 51c60a4d77b2198bc422fa93684a202f2baeed7d MD5sum: c8b5fc99035954d2bb86cbec3625ff15 Description: Python 3 implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python 3 extension module implementing the MessagePack format. Package: python3-pandas Source: pandas Version: 0.14.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8903 Depends: neurodebian-popularity-contest, python3-dateutil, python3-tz, python3:any (>= 3.3.2-2~), python3-numpy (>= 1:1.6~), python3-pandas-lib (>= 0.14.1-1~nd14.04+1) Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-six Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.14.1-1~nd14.04+1_all.deb Size: 1247938 SHA256: d016a5929006b1adcc15ccf6066d2797e88a5ce4640c35959a6ac18e406b3897 SHA1: 0d590c6d22d66179223c33775ba1a0a851b947b3 MD5sum: 2250055c14cf83b0631aee5ec0f93e5a 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: 0.14.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4814 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (>= 3.4~), python3 (<< 3.5) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.14.1-1~nd14.04+1_amd64.deb Size: 1303218 SHA256: 8b3c629d52b24197cccbbfeece069a78ea3f9ba859dd1436ac853e56c1006595 SHA1: 69d8dfcdf4af78f64a1de9516ec7d3a431b934ac MD5sum: 263c1e8d5ba1f40539eecde827247250 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: 0.3.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 717 Depends: neurodebian-popularity-contest, python3-numpy, 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_0.3.0-3~nd14.04+1_all.deb Size: 162128 SHA256: 5301c49cfd30c0d88f549c2752d7dde4f890dc39633ea1cf0b87fbf61700e9cc SHA1: 948eb86c0ce9f3037e6a4d5cbbf97268e7dc78a4 MD5sum: f1d71d0c6f644bf1299fe7e64fc7af50 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-psutil Source: python-psutil Version: 2.1.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 248 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python3 (<< 3.5), python3 (>= 3.4~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python3-psutil_2.1.1-1~nd14.04+1_amd64.deb Size: 59804 SHA256: 221d8c34ef999deeaaa8d7e630c98af853de397738159dbbdd5db2a454cf9eb5 SHA1: 3bae4de769b768f0bdd99c0db85721ba7c0d9dd2 MD5sum: be4614304d66823dad1f0b88903ef2e2 Description: module providing convenience functions for managing processes (Python3) psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. . This package contains the Python 3 version of psutil. Package: python3-seaborn Source: seaborn Version: 0.4.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 383 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_0.4.0-1~nd14.04+1_all.deb Size: 74854 SHA256: 498877ef7135130a56695b8fac5a64f844ed79cd00735abd3dbb473d36846f4a SHA1: f48dbe10ede07da838e89a55d029c96f1870ce22 MD5sum: 895c6d97ad00ee3c2c59b62075ed160b 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-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15115 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-six (>= 1.3.0), python3-skimage-lib (>= 0.10.1-2~nd14.04+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-matplotlib (>= 1.0), python3-nose, python3-pil Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11919718 SHA256: 1d1b5c2fbf5fef5eb25d8d619bac87cfcb6362a1c97dbd10fae204f3acbeb3f4 SHA1: ca840ff46b54b7653bfbc18b965e09f2cfe9dd97 MD5sum: 42a0247cf46cf44a61b843f8c6c13542 Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-skimage-lib Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6280 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.14) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.10.1-2~nd14.04+1_amd64.deb Size: 954786 SHA256: 4efcd1de2c28b268a130903955c4e4937833e5451a3158f49fdde759420f710c SHA1: e810079e674b2545eac06aa9e097d7fafb4b7a04 MD5sum: bbe8c9bb26ee11359ce73bb44fb1780a Description: Optimized low-level algorithms for Python 3 scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 3 libraries. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2922 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk6, nifti2dicom (= 0.4.8-1~nd14.04+1), nifti2dicom-data (= 0.4.8-1~nd14.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.8-1~nd14.04+1_amd64.deb Size: 409470 SHA256: 24e5d509bb59afb6eb08f799df0c5f197390cc31478034361614350894680d27 SHA1: 027a13571b641be7f3771ee51d9bf3c1d4029a08 MD5sum: 5300b6da08958fabb787d21c322adee9 Description: convert 3D medical images to DICOM 2D series (gui) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the Qt4 GUI. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 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_all.deb Size: 9749152 SHA256: c83baf314478407e2f1b908e55554b5645b4a1d52f9ef5be18864a6ec74c454b SHA1: 993dd179e97b25766a9dd6b1d5884041448089a3 MD5sum: d92e890135a7c0c8eb5f4102b380b07c 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 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_all.deb Size: 45484386 SHA256: 182e2818ac165f6a04ef610a17226e4019e76b6403242ce5106dc8084088f456 SHA1: 4ede6932c3e3b32e11bd0e1360522b3cda6e69e2 MD5sum: dd2edf6746682da9d77ea73d1ee36418 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 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_all.deb Size: 8935290 SHA256: 5742ed7248b597e91212ca03e53541e520bbeccc2d59f865b278b7c94362661e SHA1: 32542240cefbb5d936731db01ffc3175348bc80e MD5sum: 511c71c1ed452c9f1c5dd547eaade5c8 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: 0.4.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1122 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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_0.4.2-1~nd14.04+1_all.deb Size: 537176 SHA256: d70fdb4a5c3c12495f55ccb2e61d774899e728ca550e2c024031f996aad3a5b3 SHA1: 45ba1480cf0f37f86f1bea60d94c6a6d197ce1fe MD5sum: 6b1e59da19077161f62e0fd0ec72d4d7 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: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 22678 SHA256: ea800adb74820759f1c8041031b4b396c15b127a50f03a44c9e7e374649c351e SHA1: 0b16001f8fc76a1fadef374d9f61187cc11edfcf MD5sum: 3ece230b8a5225d2691618b7b10e78ba Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: stimfit Version: 0.13.18-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2216 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1+dfsg), libwxgtk2.8-0 (>= 2.8.12.1+dfsg), python-numpy (>= 1:1.8.0), python-numpy-abi9, python2.7, python:any (>= 2.7.1-0ubuntu2), libbiosig-dev, libsuitesparse-dev, 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_0.13.18-1~nd14.04+1_amd64.deb Size: 615388 SHA256: 61507d941b4eb222370a215bdda01d3d978bc53257824171410fb19ff458c084 SHA1: 5c4c6d79db91ba76f368c3ea1bf40c5bb5a7b104 MD5sum: 3f679128977314d58a4ea0c1e6b5aa80 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: 0.13.18-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 25510 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_0.13.18-1~nd14.04+1_amd64.deb Size: 5296734 SHA256: 26924610a16597f07ac7dec508ba26d09821ff191ee806d35c140407c1ff579e SHA1: 27b593cae5f642ff868e05aaf1bf3c83e830c078 MD5sum: 258eccb5900a40bb25f7e7d386a2e4fe 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 358 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_all.deb Size: 85950 SHA256: 9a51b163a417b1a421415111ce4ddedea08a840e943a7a144f782b37944d8699 SHA1: 77a25da70008038d7ccaa99042ef1b0fe2a04229 MD5sum: f54d2b8e28fcffe650211599731dab19 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: utopia-documents Version: 2.4.4-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19367 Depends: neurodebian-popularity-contest, libboost-python1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.10 (>= 1.10.0), libglu1-mesa | libglu1, libpcre3, libpcrecpp0 (>= 7.7), libpython2.7 (>= 2.7), libqglviewer2, libqjson0 (>= 0.7.1), libqt4-network (>= 4:4.7.0~beta1), libqt4-opengl (>= 4:4.5.3), libqt4-script (>= 4:4.5.3), libqt4-svg (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libraptor1 (>= 1.4.21-3), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), python:any (>= 2.7.1-0ubuntu2), python2.7, python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_2.4.4-1~nd14.04+1_amd64.deb Size: 5158484 SHA256: b75e4838af05fc074984e33c3dc1a0a0968afb89b57b9944de7f646498662800 SHA1: afa027cf35010b12323d2267074ef9db6a38f7b0 MD5sum: 4dbebd3b035248d3e384ff709705a35d Description: PDF reader that displays interactive annotations on scientific articles. Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. It makes it easy to explore an article's content and claims, and investigate other recent articles that discuss the same or similar topics. . Get immediate access to an article's metadata and browse the relationship it has with the world at large. Generate a formatted citation for use in your own work, follow bibliographic links to cited articles, or get a document's related data at the click of a button. . Various extensions provide links to blogs, online data sources and to social media sites so you can see what other researchers have been saying about not only the article you're reading but its subject matter too. Package: utopia-documents-dbg Source: utopia-documents Version: 2.4.4-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47385 Depends: neurodebian-popularity-contest, utopia-documents (= 2.4.4-1~nd14.04+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_2.4.4-1~nd14.04+1_amd64.deb Size: 46251400 SHA256: 38be8f579de44ab6c20c96eca5103793a68efe0d786a8913abcdf6a3f86e5c66 SHA1: 917ba544ad67901bd00836b705af847a3c3c4e44 MD5sum: 04498e72ef22c1069067bbf7ea2a5c91 Description: debugging symbols for utopia-documents Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. . This package contains the debugging symbols for utopia-documents. Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 315 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 46628 SHA256: 99879ed027ea24549ba6c17fd51901a0282aea89609fad41fc4cf6e6919294e4 SHA1: e78f9e27a5b9cc7d1f18d571eb549caf7aed28c3 MD5sum: 220ed03353fa1bf02c2a1f9cdc18905a Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5258 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 1098504 SHA256: a567a702e1c24615265c3c07a530c2edc93b34118bd54deb639a086f992f3fda SHA1: b31602640c7180049f8c3138e7c5c347df0eebec MD5sum: 5676362401ef27d93a32ffc7451914fa Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables.