Package: afni-atlases Source: afni-data Version: 0.20180120-1.1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 109419 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni-data/afni-atlases_0.20180120-1.1_all.deb Size: 98215048 SHA256: b7b30ce4345671d92cb08f939b76de42f81a6839abe3d47dba1db0620fe64e0c SHA1: 792d6506cc866acfa54fc71475f823e686f169f7 MD5sum: deaddf5e6992face9b5edeb62644187c Description: standard space brain atlases for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provide AFNI's standard space brain templates in HEAD/BRIK format. Package: aghermann Version: 1.0.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1529 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.8), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-3, libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp7, liblua5.2-0, libpango1.0-0 (>= 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), libx11-6 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.4-1~nd70+1_i386.deb Size: 697410 SHA256: e8ccd575ec662206068d31c95312a55b0efd2dc5737932697af292724b8c27e4 SHA1: 03e39de878c607bb14c9bac0bd3b93a11d2f5a01 MD5sum: 6dec465b63a121e297e18176b789c672 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: ants Version: 1.9.2+svn680.dfsg-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 40052 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.20, libstdc++6 (>= 4.6) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-3~nd70+1_i386.deb Size: 12761250 SHA256: 9b085461c30d311102cee8e3baedf449e5c8f874825e7bfbb04f88dd1d46c8aa SHA1: 834cdf56592c9f8a1d51f3bb6b27c783ef31fb4d MD5sum: 5e10a43282eb3d99b80904cd14c1c841 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). Package: bats Version: 0.4.0-1~nd70+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~nd70+1_all.deb Size: 15366 SHA256: 2a32b894f1a426e1effcecdac7afb898992c41a99a32c5b7885626f12b349d10 SHA1: 7696e4469ab1f974dccfe7c782384965e2e80d2c MD5sum: ed9c98c88ecce9dac667d78b77559f25 Description: bash automated testing system Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. Bats is most useful when testing software written in Bash, but you can use it to test any UNIX program. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 667 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_1.4.1-2~nd70+1_i386.deb Size: 284478 SHA256: 5fa7b43cf6b229591128d19a55e423feb63588bfa699fc1b2b25af33d7b405e3 SHA1: 79212e759e89f86ff3a29cbb5ac0f587f00631cf MD5sum: a2f3567c024bb82be5b36d39fb46b4b5 Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: btrbk Version: 0.25.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 313 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv Homepage: http://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.25.0-1~nd70+1_all.deb Size: 85344 SHA256: 5617d1de86f6bae03fbf7ba56f2c34ad51f67a987bf0935ebb8f4f7cd946a5d1 SHA1: cb861cb8393d65c7720dd1c40a8b400199e000f0 MD5sum: 50987700c969c9b27066dbb2d822e46a Description: backup tool for btrfs subvolumes Backup tool for btrfs subvolumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations, with ssh and flexible retention policy support (hourly, daily, weekly, monthly). Package: btrfs-tools Version: 4.1.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3518 Depends: neurodebian-popularity-contest, e2fslibs (>= 1.42), libblkid1 (>= 2.17.2), libc6 (>= 2.8), libcomerr2 (>= 1.01), liblzo2-2, libuuid1 (>= 2.16), zlib1g (>= 1:1.2.0) Homepage: http://btrfs.wiki.kernel.org/ Priority: optional Section: admin Filename: pool/main/b/btrfs-tools/btrfs-tools_4.1.2-1~nd70+1_i386.deb Size: 1835416 SHA256: 66cd70a9606f151ef2bbad309c624ee6e50e9c9a1c33480433666ab7e89e1c7c SHA1: 66e3ac980b2f77df697f0364468475215cb6b14b MD5sum: bbab5867066a88c94a2f77572465437a Description: Checksumming Copy on Write Filesystem utilities Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains utilities (mkfs, fsck) used to work with btrfs and an utility (btrfs-convert) to make a btrfs filesystem from an ext3. Package: btrfs-tools-dbg Source: btrfs-tools Version: 4.1.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4890 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd70+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd70+1_i386.deb Size: 4704596 SHA256: 7a81d909fd264a4df1b01e194739b7556e02bd05c288b3a6bff5f1b1c06a8f8d SHA1: 6e79d7ec389cd0a5515fc74d9cf93f7d24b9aa3c MD5sum: 830adc2fdf7fbcee0f6a79a7e3a95ac2 Description: Checksumming Copy on Write Filesystem utilities (debug) Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains the debugging symbols. Package: caret Version: 5.6.4~dfsg.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18495 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, zlib1g (>= 1:1.2.3.3) Recommends: qt-assistant-compat Suggests: caret-data (>= 5.6.2~dfsg.1~) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.4~dfsg.1-2~nd70+1_i386.deb Size: 7452648 SHA256: 3e01694737885e1a3ae5b06aed7320ab8edabdbc78510d8f2c3fbdd0325fb049 SHA1: d362d0c5de0f3751e56e495c412cfef616baaaf9 MD5sum: 600cf70c5e9193af0318fde18c123987 Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes: . - Map volumes to surface via PALS atlas - Multi-resolution morphing - Projection of foci via PALS atlas - Surface-based registration - Surface flattening . Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more information. Package: cde Version: 0.1+git9-g551e54d-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 797 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd70+1_i386.deb Size: 331532 SHA256: 9b2480b357ab8f9c2de591e0aff1cdafd123525f968288d95cb6815c3f156b61 SHA1: 8b9b957ffbb4b051baac5f36271f6a9afafef757 MD5sum: 3cc87189455a21fe95a9ed99771bc964 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: cgroup-bin Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcgroup1 Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/cgroup-bin_0.37.1-1~nd70+1_i386.deb Size: 63608 SHA256: 9f5087592cb74bde00439f5d54b4388750a102289ce4ac9574231547d1657aea SHA1: 43342c8ebefccf39d1cfc066b8a1c4a451bdb67a MD5sum: 0354bc4d541b8a7b0d60df0c2e9f38de Description: Tools to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . These tools help manipulate, control, administrate and monitor control groups and the associated controllers. Package: cmtk Version: 3.3.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 23217 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk2 (>= 3.6.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.4), 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_3.3.1-1~nd70+1_i386.deb Size: 6963306 SHA256: 22c399e803c55069b29f4dac839cc101ce0daed7ec56f3f782355c26890f40fe SHA1: dd38804b0e6ebacf7f1cf911e04eab3e36630062 MD5sum: f7db9d52bfaadccf0438df2d36c5a813 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 Version: 1.1.14-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 300 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libreadline6 (>= 6.0), libstdc++6 (>= 4.6), libxml2 (>= 2.6.27) Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun_1.1.14-1~nd70+1_i386.deb Size: 130148 SHA256: 843e04bb21ea34e7e404f0b7a2426cce89b6ecc23e260f64fc5c06df0af8ef85 SHA1: a09ab6b6e9e508992f9d7c4165ca7848626db593 MD5sum: bb98387ba7a49389c1c89bd50ad8fb2c Description: NeuroML-capable neuronal network simulator CNrun is a neuronal network model simulator, similar in purpose to NEURON except that individual neurons are not compartmentalised. It can read NeuroML files (e.g., as generated by neuroConstruct); provides a Hodgkin-Huxley neuron (plus some varieties), a Rall and Alpha-Beta synapses, Poisson, Van der Pol, Colpitts oscillators and regular pulse generator; external inputs and logging state variables. Uses a 6-5 Runge-Kutta integration method. Basic scripting and (if run interactively) context-aware autocompletion. Package: cnrun-tools Source: cnrun Version: 2.1.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.4.0), libxml2 (>= 2.6.27) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.1.0-1~nd70+1_i386.deb Size: 24154 SHA256: 79731dedd4dd9646d1c0e576a17a4cacd4e8f5a374ab8c5d29a769cfa5b24c84 SHA1: 3dc6221c2b16dea3d1cf5ec0b35fbdc84e0f7594 MD5sum: 52b8935db00e8a385f01bef03eef84ee Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.9~dfsg.1-2~nd70+1_all.deb Size: 17002 SHA256: abbf77f50a6104a530e324c12b06e245c4206d141009ba88b39b0dd336fce4ad SHA1: 39cabc45542eeccedced03199b771768d8dd0647 MD5sum: 28edf9d91e129ee394ccb01ed4e83646 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.9~dfsg.1-2~nd70+1_all.deb Size: 17012 SHA256: 20f2876aeb2e1ad33e526e1f387952ebfd188105e989e03699ac1443ae8ebda1 SHA1: 4bb469fda74ab86ac3bb07ad447cb8dccfb442ec MD5sum: 3275a41522e8de4146c01376e213cb06 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.9~dfsg.1-2~nd70+1_all.deb Size: 17012 SHA256: 7eae55862c441c0fca7debbb7b470f70dc8ee6f5114979d58413e22c4767cdf7 SHA1: eb2782a003f44430efac293a614d3d03f4f05272 MD5sum: dfad9779c0de1648878452780c955c2a Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.9~dfsg.1-2~nd70+1_all.deb Size: 17010 SHA256: 62584dcf06cdd38bda6617d41b5cfbca4560807587bebbae78f4b07f87a06e4d SHA1: c6e1042033803db856f315ab9dae8b85c96506ba MD5sum: f1e42e8cbbc41d8ab741e043fc0e3b4a Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: connectome-workbench Version: 1.2.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54891 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.4), libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.7.0~beta1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.3) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.2.3-1~nd70+1_i386.deb Size: 33780786 SHA256: 042f3cc1ffb4754bad7ae8f155f17081c04efb4b56cdde1fe633e408b3f71fb6 SHA1: 1100996ddefe3df56b39ce750e7d8ecd326442d8 MD5sum: b2475149fdd3e0362fd1c9c78f44b9ea Description: brain visualization, analysis and discovery tool Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. Package: connectome-workbench-dbg Source: connectome-workbench Version: 1.2.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 121909 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.2.3-1~nd70+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.2.3-1~nd70+1_i386.deb Size: 120548976 SHA256: de1b173f3a089d73dd3e5ef51626cd82d8f69a5e6bfc7ab9f314a55fc2a9a553 SHA1: c2dbaabd98eda5f091669b4662ee5f5717536edd MD5sum: 4d16089821b0f24b0477f351d400ff5c 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: connectomeviewer Version: 2.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1578 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-cfflib (>= 2.0.5), python-networkx (>= 1.4), python-nibabel, python-numpy (>= 1.3.0), python-scipy, python-chaco, mayavi2 (>= 4.0.0), ipython Recommends: python-nipype, python-dipy, python-matplotlib, python-qscintilla2 Suggests: nipy-suite Homepage: http://www.connectomeviewer.org Priority: extra Section: python Filename: pool/main/c/connectomeviewer/connectomeviewer_2.1.0-1~nd70+1_all.deb Size: 1356156 SHA256: 84e3a8e4487cd67005eaf2c292b248e7e812057408ca7b7e012d71c3684298c2 SHA1: a20067603c1694d3c598d7e261e2bb64a98253df MD5sum: 4325ba9177d6224461c4520b1b7a41a0 Description: Interactive Analysis and Visualization for MR Connectomics The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics. . Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit. Package: coop-computing-tools Source: cctools Version: 3.4.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4050 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfuse2 (>= 2.8.1), libglobus-common0 (>= 14), libglobus-gss-assist3 (>= 8), libglobus-gssapi-gsi4 (>= 10), libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), libncurses5 (>= 5.5-5~), libopenmpi1.3, libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), libtinfo5, python Suggests: coop-computing-tools-doc, condor, gridengine-client Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.4.2-1~nd70+1_i386.deb Size: 1398844 SHA256: 5551401b09a456076bd199fdf340bd2f0c09e0f079ec7658dbd10f05815eab79 SHA1: fc3721c9070e2815b1f48c9dfbd6cd9cd8530d62 MD5sum: fd3310d6fd930d51f45df09621526543 Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.4.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 830 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.4.2-1~nd70+1_i386.deb Size: 222958 SHA256: c3bf9352beb6d6732566925c9f471078067880f33820445d42e6245f82b91024 SHA1: c97d96fea24d7be085de423fe7036ab213a99437 MD5sum: e2b1d5630029b2aa43f47254581acf85 Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.4.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2319 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.4.2-1~nd70+1_all.deb Size: 310890 SHA256: ca1fc4a117105875244c5c1a16994aa4e1c7496de9d177e96bbd351def1da0b5 SHA1: 154b372d4c5b7a25d5885e2ae8d79e64808671b2 MD5sum: c5f2ca94795a12217de0438befa22e8d Description: documentation for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides the documentation (manual and API reference) in HTML format. Package: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 224 Depends: neurodebian-popularity-contest, python3-datalad (= 0.17.5-1~nd+1), python3-argcomplete (>= 1.12.3), python3:any Suggests: datalad-container, datalad-crawler, datalad-neuroimaging Homepage: https://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.17.5-1~nd+1_all.deb Size: 187092 SHA256: dcfab5ab31ab85c685b4439648c3095efb236b34c92eb2f870fc1376dd0dbab1 SHA1: e8a088bc96e73f10444588eede93689410943c07 MD5sum: a4020bc221d05979fe1738d432660717 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) Package: dcm2niix Version: 20160921+git16-g0339407-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 243 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_20160921+git16-g0339407-1~nd70+1_i386.deb Size: 108868 SHA256: 9631f51a1b093e887343fc18181e381356713e30cf9b211906e6fdd7232f3160 SHA1: 3156482aeff01f84d5560ea0595f57e5b24a5458 MD5sum: 3b03689e548f6ec85f460419df0749d7 Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debian-handbook Version: 6.0+20120509~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23215 Depends: neurodebian-popularity-contest Homepage: http://debian-handbook.info Priority: optional Section: doc Filename: pool/main/d/debian-handbook/debian-handbook_6.0+20120509~nd+1_all.deb Size: 21998670 SHA256: b33f038d8363175473cc056a5f98fc7af52386a466b45d4b2e42d2f25233a3ed SHA1: 7a0b369b4548a3f4fb61aa1ef9efa2ddf2b319e2 MD5sum: 3e3d2cf990fcc5ed1ed6bdbfb5c1c3dd Description: reference book for Debian users and system administrators Accessible to all, the Debian Administrator's Handbook teaches the essentials to anyone who wants to become an effective and independent Debian GNU/Linux administrator. . It covers all the topics that a competent Linux administrator should master, from the installation and the update of the system, up to the creation of packages and the compilation of the kernel, but also monitoring, backup and migration, without forgetting advanced topics like SELinux setup to secure services, automated installations, or virtualization with Xen, KVM or LXC. . The Debian Administrator's Handbook has been written by two Debian developers — Raphaël Hertzog and Roland Mas. . This package contains the English book covering Debian 6.0 “Squeeze”. Package: debruijn Version: 1.6-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfftw3-3, 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~nd70+1_i386.deb Size: 45346 SHA256: 5359da2f63e045cb27969830711cb61285c4b34c7a7687a18db48a2e08ef4342 SHA1: fef5f10221fbfbb9edaaaa3875bc6ed506a5cbea MD5sum: df1baca3fc49684579ec2dad10cc9d82 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-python Version: 1.20131021-1~bpo70+1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 227 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Priority: optional Section: python Filename: pool/main/d/dh-python/dh-python_1.20131021-1~bpo70+1~nd70+1_all.deb Size: 63466 SHA256: 877c1a30fbb0c52443e860255912ffcfb9ae9a31da796b6309fe6b1f08e15cb1 SHA1: 28786b4c55b41be8544285f6f0c7f8e8c265d89c MD5sum: 5bb11f7e1e42aac34e67c025f353039f Description: Debian helper tools for packaging Python libraries and applications This package contains: * pybuild - invokes various build systems for requested Python versions in order to build modules and extensions * dh_python2 - calculates Python 2.X dependencies for Debian packages, adds maintainer scripts to byte compile files, etc. * dh_python3 - calculates Python 3.X dependencies for Debian packages, adds maintainer scripts to byte compile files, etc. * dh_pypy - calculates PyPy dependencies for Debian packages, adds maintainer scripts to byte compile files, etc. Package: dh-systemd Source: init-system-helpers Version: 1.18~nd70+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~nd70+1_all.deb Size: 14630 SHA256: bedf7f47ba2292bae5f532bcb9125cab3e1a3e4ac1d1e4bdeeb4ebfe10efc1c3 SHA1: 1b9cc0b9731616b968aa0ab95b59fa96f3ff9d13 MD5sum: 8be99fbb0699e021da9a760777f36c2f 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 482 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd70+1_i386.deb Size: 155860 SHA256: 11fd9ea6abd6e17335ed7e8242672be857048b1d06919c116733a1bd4417d584 SHA1: c940e6b06bb113616cea512d30a788c0e053518a MD5sum: 4aecff0c65e6ce5b2ffbf3177e4bcb2e 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2650 Depends: neurodebian-popularity-contest, libc6 (>= 2.9), 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~nd70+1_i386.deb Size: 1099256 SHA256: 9c142c889351abcfe07de366ba3f91bc85f0d96bd376258be388e60971d60ec4 SHA1: ede75ba1c240ca022ca454c7c4f0305cdf601713 MD5sum: e4bc4219846488a46887006967580187 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17494 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~nd70+1_i386.deb Size: 6284378 SHA256: 4510381174e0373a4691554f3d7a62f6ab29b2c9120e438d3233f31626a9907b SHA1: 297b87191d1ef741231099ed9c60554df7a0f5bd MD5sum: 943a6bf4f6e8670d1c6d1f77c7cdad05 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: edac-utils Version: 0.18-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libedac1, lsb-base (>= 3.0-6) Recommends: dmidecode Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: admin Filename: pool/main/e/edac-utils/edac-utils_0.18-1~nd70+1_i386.deb Size: 28796 SHA256: 7ec585f0e8766ff37c6107b440e14c2b54ed0ea8dd190061d6cd8d96ef6815dc SHA1: dbc2e8126d805d7bf0d06faa37c7ab5637ec5a0b MD5sum: b30f0907ff74af952b6b05139416d379 Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package provides command lines tools Package: eegdev-plugins-free Source: eegdev Version: 0.2-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 77 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd70+1), libc6 (>= 2.3.6-6~), libexpat1 (>= 2.0.1), libusb-1.0-0 (>= 2:1.0.8), libxdffileio0 (>= 0.0) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/eegdev-plugins-free_0.2-3~nd70+1_i386.deb Size: 27524 SHA256: f1d6dec8b5cbc9e0ca00529f8b104166286cebc5fa1345866655843c50e742d2 SHA1: 0f2f02a659bc265f79ed1882ae345413865dcded MD5sum: b02fad1a1080734c5b44c9b2ec26cf5d Description: Biosignal acquisition device library (free plugins) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the devices plugins that depends only on free components. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd70+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~nd70+1_all.deb Size: 7224720 SHA256: a25c47daa7e5cabbab1e2864994d7ca0d5b207e5609c31fe0f62c32fae733590 SHA1: 6a5b78425b50d335c0f1e49bc20cd68aae0ab3fc MD5sum: fdcfc99b0c53436258c20f5eee125e50 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: eegview Version: 0.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libeegdev0, libmcpanel0 (>= 0.0), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegview.html Priority: extra Section: science Filename: pool/main/e/eegview/eegview_0.0-1~nd70+1_i386.deb Size: 12716 SHA256: e04aed3b747363fe070da08a090a8fba64967aef974bff2389cc2e26cb7a3d52 SHA1: 51a6b4f282e219e5178f68c329aedd44c4d1d4bc MD5sum: 6cbfb8c0720e5aaf4232d664c7410c3e Description: Software to display EEG data in realtime This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment. Package: environment-modules Source: modules Version: 3.2.10-8~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, debhelper (>= 9), tcl8.6 | tcl, libc6 (>= 2.4), tcl8.5 (>= 8.5.0) Homepage: http://modules.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/m/modules/environment-modules_3.2.10-8~nd70+1_i386.deb Size: 102718 SHA256: 8ad591869dadb2156568cbbc5112833df1eca70480593b07824fb5510e3ed252 SHA1: 20dbb05ec3c4ff71a10044de0489003a2bc9c0e3 MD5sum: 598721575434f630cc7e5f0f7527a984 Description: Modular system for handling environment variables The Modules package provides for the dynamic modification of a user's environment via modulefiles. Each modulefile contains the information needed to configure the shell for an application. Once the Modules package is initialized, the environment can be modified dynamically on a per-module basis using the module command which interprets modulefiles. Typically modulefiles instruct the module command to alter or set shell environment variables such as PATH, MANPATH, etc. modulefiles may be shared by many users on a system and users may have their own collection to supplement or replace the shared modulefiles. The modules environment is common on SGI/Crays and many workstation farms. Package: fail2ban Version: 0.9.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1503 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: mailx, system-log-daemon, monit, python-systemd Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.7-1~nd70+1_all.deb Size: 359084 SHA256: 9764488d306582212be33d9e8d36ce948751ce5b344e3d2a93835c29778ced49 SHA1: 869c8755b0201ef47d3ea226deb36ae3ee1b10f6 MD5sum: f840ae9fba08b74ea1607c16e34f0f32 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: fis-gtm Version: 6.0-003-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, fis-gtm-6.0-003 Provides: mumps Homepage: http://sourceforge.net/projects/fis-gtm Priority: optional Section: database Filename: pool/main/f/fis-gtm/fis-gtm_6.0-003-2~nd70+1_all.deb Size: 15108 SHA256: 8a48d53f74d1f1705844ba5ddad14a6f75f3588c56c92e5de6cd0dbda3952598 SHA1: 615f1962b57b77ab49d8ab6702fc989cb40b409a MD5sum: c3fb09773b5eb09dd6cadbbdc024e5b8 Description: metapackage for the latest version of FIS-GT.M database GT.M is a database engine with scalability proven in large real-time transaction processing systems that have thousands of concurrent users, individual database file sizes to the Terabyte range (with virtually unlimited aggregate database sizes). Yet the light footprint of GT.M allows it to also scale down for use in small applications and software appliances (virtual machines). . The GT.M data model is hierarchical associative memory (i.e., multi-dimensional array) that imposes no restrictions on the data types of the indexes or content - the application logic can impose any schema, dictionary or data organization suited to its problem domain. (Database engines that do not impose schemas, but which allow layered application software to impose and use whatever schema that is appropriate to the application are popularly referred to as "document oriented", "schemaless" or "schema-free" databases.) . GT.M's compiler for the standard M (also known as MUMPS) scripting language implements full support for ACID (Atomic, Consistent, Isolated, Durable) transactions, using optimistic concurrency control and software transactional memory (STM) that resolves the common mismatch between databases and programming languages. Its unique ability to create and deploy logical multi-site configurations of applications provides unrivaled continuity of business in the face of not just unplanned events, but also planned events, including planned events that include changes to application logic and schema. . This metapackage always depends from the default fis-gtm version. Package: freeipmi Version: 1.4.9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd70+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd70+1_all.deb Size: 1122 SHA256: 760ec4be7b50fdbf5310c97bbfd29986f7d0c6f5ecb1781f12e18ec461d54831 SHA1: 1b87081846b6d5d371cb1774c14c8f37d6d9c90e MD5sum: 5880c9684719ff72e16a96b133e4f7cb Description: GNU implementation of the IPMI protocol FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This metapackage depends on all separate modules of freeipmi. Package: freeipmi-bmc-watchdog Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 123 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.4.9-1~nd70+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.9-1~nd70+1_i386.deb Size: 53504 SHA256: e8153502414dc96c8c44dac78b512ea45f46fca027118cc9ebdbc0275751b9ab SHA1: ae606e9dac0aeb2ddebb184f767b585f8e4bacca MD5sum: 96837fa8a0c5548e46645ab8d0ac2e1f Description: GNU implementation of the IPMI protocol - BMC watchdog FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a watchdog daemon for hardware BMC watchdogs. Package: freeipmi-common Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 451 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest Suggests: freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-common_1.4.9-1~nd70+1_all.deb Size: 346136 SHA256: 7c83c6c36fb5ee831c625242ee5afc0e4362d1623307815558e8b708fa22c122 SHA1: d756a6943a9b6d91838075927fbe2b70b0431261 MD5sum: c8737ba0a120c1f3d45839b573327f2c Description: GNU implementation of the IPMI protocol - common files FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package provides configuration used by the rest of FreeIPMI framework and generic documentation to orient the user. Package: freeipmi-ipmidetect Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 100 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), libgcrypt11 (>= 1.4.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd70+1_i386.deb Size: 53170 SHA256: 23358fac8ea07805cbd34852fdbca6755fdc0107bb60c1767de15623aa2f4943 SHA1: a4b400ae9b0082d0fe1fe824444f21296ae6fff1 MD5sum: 95bbf7dc016d5e48ced09d4a5c314906 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a tool and a daemon for detecting IPMI nodes. Package: freeipmi-ipmiseld Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 189 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.4.9-1~nd70+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.9-1~nd70+1_i386.deb Size: 92498 SHA256: ea0fcb1daf56a46696475c8ff7587d1f410ab643eaaf434b7410c746dba9f444 SHA1: a24b5b405704e0eeb3348ecd98dc2bfc54755c90 MD5sum: d83b42263204a461ded7fde815bd8079 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains ipmiseld which takes the system event log from the BMC and imports it to syslog Package: freeipmi-tools Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2816 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.9-1~nd70+1), libgcrypt11 (>= 1.4.5), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd70+1) Suggests: freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-tools_1.4.9-1~nd70+1_i386.deb Size: 1243472 SHA256: c8e6facb0fa735e671f4a4ba5cd5eea876dac11f8e3eb81dfbb66f3b0ac429a6 SHA1: 03a493f0f05b5a5e57f6902593fbb01e3fb8b0ee MD5sum: 111c6f96b64963e0a2465b5bcbc2e996 Description: GNU implementation of the IPMI protocol - tools FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains assorted IPMI-related tools: * bmc-config - configure BMC values * bmc-info - display BMC information * ipmi-chassis - IPMI chassis management utility * ipmi-fru - display FRU information * ipmi-locate - IPMI probing utility * ipmi-oem - IPMI OEM utility * ipmi-pet - decode Platform Event Traps * ipmi-raw - IPMI raw communication utility * ipmi-sel - display SEL entries * ipmi-sensors - display IPMI sensor information * ipmi-sensors-config - configure sensors * ipmiconsole - IPMI console utility * ipmiping - send IPMI Get Authentication Capabilitiy request * ipmipower - IPMI power control utility * pef-config - configure PEF values * rmcpping - send RMCP Ping to network hosts Package: freenect Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.5, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.5.3-1~nd70+1_i386.deb Size: 9160 SHA256: 26639cdebca7c4f95d15c658d4d9c8a5cc178f8db85f060a768f768942455c83 SHA1: 66ec2d4749c8e532aeefb0390a6d06e603e71f00 MD5sum: b8e8415dbc40d4f12ba9599d9636b4e7 Description: library for accessing Kinect device -- metapackage libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the metapackage to install all components of the project. Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 146 Depends: neurodebian-popularity-contest, python-scipy, python-matplotlib, python (>= 2.6.6-3), python-nibabel, python-numpy, python-pkg-resources, python (<< 2.8), python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd70+1_all.deb Size: 15820 SHA256: c9edf062db46754e401360cc2108bd3bbb0f27d1d1af4dce0e0ce5ceb46563ce SHA1: 90f2182a486de64f8faa89c2b352383b71d81922 MD5sum: 3b5533d566430cb10f0c189371ec87b6 Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.6, 2.7 Package: fslview Version: 4.0.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6052 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), 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~nd70+1_i386.deb Size: 2332456 SHA256: 0f24850acbe73948d852bf0201f0ae93373c5b5894d68da67db35bcb5e5beae4 SHA1: 3378e0ffb13823206835b56a408e2eb38005926a MD5sum: 7ff33d5635a2b5bfaeb174a6b23391a4 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~nd70+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~nd70+1_all.deb Size: 2346532 SHA256: 485b06c824c12100413729f1a795e7963897b84bf9b92e2b8b91b5f207f1e709 SHA1: fe14f20c5faf550a29cb9b24121fc2cfddedacd1 MD5sum: 641476378b45b8e334faefe1ccdff8cb Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gdf-tools Source: libgdf Version: 0.1.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 168 Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-program-options1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.2-2~nd70+1_i386.deb Size: 56122 SHA256: 6aa6489b99b1828d1c7957db5469c0ea99afb39c7b1172d9da6cfb3f5a4c53e4 SHA1: a47ee82829ac6fe83a477afd0b9435d626c11f91 MD5sum: a23a1a4453cc6ae9f0517748c081e2b1 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: gifti-bin Source: gifticlib Version: 1.0.9-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, libc6 (>= 2.1), libexpat1 (>= 2.0.1), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-2~nd70+1_i386.deb Size: 28366 SHA256: c21a251994de80dd38e13204765e5821c1f54173970f6180a9edba05d5799928 SHA1: 8ea08f45c36f94c67dd7dbf36e2ff2eb683cdb25 MD5sum: d7d0a511b1e34242ad7dccc171b92065 Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: git-annex-metadata-gui Version: 0.0.0~pre1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 86 Depends: neurodebian-popularity-contest, python3-git-annex-adapter, python3-pyqt5, python3 (>= 3.2.3-3~) Homepage: https://github.com/alpernebbi/git-annex-metadata-gui Priority: optional Section: python Filename: pool/main/g/git-annex-metadata-gui/git-annex-metadata-gui_0.0.0~pre1-1~nd70+1_all.deb Size: 10846 SHA256: 4cefeefafc8659f14e475056622e72271890b0597c5ee3d6969d858ba055169f SHA1: 623ca070dcb2ee57645f6a4efa9d24e9c728e8e7 MD5sum: ce78c7ebbc9282afa6b73d6bc907b761 Description: graphical interface to the metadata functionality of git-annex Flexible graphical user interface to view and manipulate metadata of git-annex repositories. Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: git-annex-standalone Source: git-annex Version: 10.20241031-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 236968 Depends: git, netbase, openssh-client Recommends: lsof, gnupg, bind9-host, yt-dlp, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, adb, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Breaks: datalad (<= 0.12.3~) Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_10.20241031-1~ndall+1_i386.deb Size: 68790604 SHA256: 54a538b686e2e3c42f6cf7260adc0ffe9710f3c6acc07a3b0832df703dba5a6b SHA1: be36d7de781610ad2928fe4ce19fa9ff92631f78 MD5sum: 97eb9b52c155f9c314da9711f48b2ed7 Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing large files with git, without storing the file contents in git. It can sync, backup, and archive your data, offline and online. Checksums and encryption keep your data safe and secure. Bring the power and distributed nature of git to bear on your large files with git-annex. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with dozens of cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: git-hub Version: 0.10.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, python, git (>= 1:1.7.7) Homepage: https://github.com/sociomantic/git-hub Priority: optional Section: vcs Filename: pool/main/g/git-hub/git-hub_0.10.3-1~nd70+1_all.deb Size: 37408 SHA256: d2e1eb2092713fba7a9d553290200a7fb95fbe9e54e3383dce1e50adbf3d7938 SHA1: 0e13f70392db89b4528e2cabdc9e97e7c0979f59 MD5sum: c1d795919ea3c5f324101dedaf630f2e Description: Git command line interface to GitHub git hub is a simple command line interface to GitHub, enabling most useful GitHub tasks (like creating and listing pull request or issues) to be accessed directly through the Git command line. . Although probably the most outstanding feature (and the one that motivated the creation of this tool) is the pull rebase command, which is the rebasing version of the GitHub Merge (TM) button. This enables an easy workflow that doesn't involve thousands of merges which makes the repository history unreadable. . Another unique feature is the ability to transform an issue into a pull request by attaching commits to it (this is something offered by the GitHub API but not by the web interface). Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 360 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd70+1), libc6 (>= 2.1), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 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~nd70+1_i386.deb Size: 135728 SHA256: 9106f3d915f0509db8e4f30785cde816bc64a9ffde088922920a9b031c703d2e SHA1: 37ff0f57ba3c9280f983ea81172af8c36614f25b MD5sum: 7c2028c2984d8337dea75686e0bf63a2 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~nd70+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~nd70+1_all.deb Size: 16578 SHA256: 67088e7164c36ef9252ad4cbfe6c844c8d743d262951ff4e4c326ec757aa78b5 SHA1: f448553684f801378d706b67eb873bfb7579ac15 MD5sum: 2a15157f72f9ee1d82110c7c1375a1f4 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: golang-github-ncw-rclone-dev Source: rclone Version: 1.41-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 2492 Depends: golang-bazil-fuse-dev, golang-github-aws-aws-sdk-go-dev, golang-github-mreiferson-go-httpclient-dev, golang-github-ncw-go-acd-dev, golang-github-ncw-swift-dev, golang-github-pkg-errors-dev, golang-github-pkg-sftp-dev, golang-github-rfjakob-eme-dev, golang-github-skratchdot-open-golang-dev, golang-github-spf13-cobra-dev, golang-github-spf13-pflag-dev, golang-github-stacktic-dropbox-dev, golang-github-stretchr-testify-dev, golang-github-tsenart-tb-dev, golang-github-unknwon-goconfig-dev, golang-github-vividcortex-ewma-dev, golang-golang-x-crypto-dev, golang-golang-x-net-dev, golang-golang-x-oauth2-google-dev, golang-golang-x-sys-dev, golang-golang-x-text-dev, golang-google-api-dev Homepage: https://github.com/ncw/rclone Priority: optional Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.41-1~ndall0_all.deb Size: 399416 SHA256: 528b53f3312375d31d5cebb95472a57272cf242e14a92cfdf99c45be2ff5511d SHA1: 75f8871fd668e815023267a857b37ad60b9d1c2f MD5sum: a87865eafe10185420838e2e4ffd7b55 Description: go source code of rclone Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers. . This package contains rclone's source code. Package: guacamole Source: guacamole-client Version: 0.8.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 475 Depends: neurodebian-popularity-contest, guacd Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole_0.8.3-1~nd70+1_all.deb Size: 428518 SHA256: 0d8d7e00f9bea518612ae40596246823279ff8d7c1126ec10beef8848c00a385 SHA1: bdd2e798af468ea8cbf87d32a8b113c7a0b72c57 MD5sum: 153ddcf74c34d7c6195d669dc5992716 Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole-client Version: 0.8.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole-tomcat_0.8.3-1~nd70+1_all.deb Size: 6944 SHA256: a0f7f85710d74708386d4be22e68c0ceeafe410755930f075c49648962c5684a SHA1: 663164e7be20b679af98ec91fb8ebe16f5b8917b MD5sum: 915d0c1d4bb6540aab4ec1066e39e486 Description: Tomcat-based Guacamole install with VNC support Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. . This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.10), libguac5, libssl1.0.0 (>= 1.0.0) Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-server/guacd_0.8.3-1~nd70+1_i386.deb Size: 15682 SHA256: d5d03c041897fa6d733402acb8d2d6b0a5a1a41fc6c7b6dc27bbe49c2eaf8768 SHA1: ff25c173676125ff8acdbcb9bb399af92dfdf9d9 MD5sum: d8f0c2ed951b65ed2a2081534dd6cbc0 Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: heudiconv Version: 0.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 79 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd70+1_all.deb Size: 10874 SHA256: a0bc382c1c1ca41edef3b954c91cee8530b851feeed9addaac5f4d174edaf81b SHA1: 7b8845aa5cfc5531c9a6b0fe1b1a5996b77e7310 MD5sum: d2474cc6c51da55868e16181d36fb33a Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: htcondor Source: condor Version: 8.2.3~dfsg.1-5~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 14575 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.11), libcgroup1 (>= 0.37.1), libclassad7, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libkrb5support0 (>= 1.7dfsg~beta2), libpcre3 (>= 8.10), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), 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.1-5~nd70+1_i386.deb Size: 6169250 SHA256: e0677a621999347f3b66892c66811b90ae11a34df057dccc8a260221d9c5c8bf SHA1: e7447632a84214c925cb79b7dcdb281d288b1717 MD5sum: 5c83dbb4d411655865400720e57e798f 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.1-5~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 35159 Depends: neurodebian-popularity-contest, htcondor (= 8.2.3~dfsg.1-5~nd70+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.1-5~nd70+1_i386.deb Size: 33664022 SHA256: 217ba82e69cba5c34f05f69a0bd3f341838324482818889d315ab0a8b5c6cf7b SHA1: ae3331fe937b1601ad664eb66d6c92246a3c94e9 MD5sum: 55cb1fe3500036b43bf6122681482bbc 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.1-5~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1218 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.1-5~nd70+1_i386.deb Size: 379970 SHA256: 201b2c60c8efd298f9322a0a6b691f632e48e96e9e9bf9da9b07ec64d99fdccc SHA1: 1b7fa8c544850fa56a84c8d5048d628bc4550c2d MD5sum: 40297323a582f98f2f8fe7bd24fc407e Description: distributed workload management system - development files Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of HTCondor add-ons. Package: htcondor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5972 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.9~dfsg.1-2~nd70+1_all.deb Size: 1451216 SHA256: e304adca93b7c870ef404a4e640890f5f6ad18c6484f47aa38f4cfb6a97e729b SHA1: 1bd47f9d7f31241e6f386f5e0de6240793dd153d MD5sum: 9c197b74551f6e9b9ea72aad29ddb273 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.11.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 470 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil | python-imaging, poppler-utils | mupdf-tools | xpdf-utils (>= 3.02-2) Recommends: mplayer, pdftk, perl, xdg-utils Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.11.1-1~nd70+1_all.deb Size: 191406 SHA256: 3af6beef9ba3350e3f723b74247dff56b10879e099536a2597f9e6c214cabe43 SHA1: 974748224418a4c8aaf81414b8f7ae93f0af691b MD5sum: 28639d1eb13fe7b535e85490dc11c30e Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd70+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~nd70+1_all.deb Size: 9652 SHA256: fac3ad8fc2cf1126a2b7fd3a9497594c3372cf7ae5a006d552d0b18e97334a11 SHA1: 803b8e967a16602928187f76ba0a8813d6a68866 MD5sum: c70545ff21713e721dbd16f9a195cbde 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~nd70+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~nd70+1_all.deb Size: 14306 SHA256: a70fc6126cb55857e2dbcb3b3068a3003fab56f54640fe85140a477943bdbf17 SHA1: b9aaea635981bc1d0d3d14fc1bc2c0911024e369 MD5sum: 5c7feaf7e6d24d453d49aa549a530d40 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: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.5.0-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest Suggests: libinsighttoolkit4-dev Conflicts: insighttoolkit-examples Replaces: insighttoolkit-examples Homepage: http://www.itk.org/ Priority: optional Section: devel Filename: pool/main/i/insighttoolkit4/insighttoolkit4-examples_4.5.0-3~nd70+1_all.deb Size: 2405102 SHA256: 3ff83e44b9415f06d817801b64e38e19080a9c56025ddebe8dd2401c2f9952f1 SHA1: 8da3d0e8d88b240932b9f08138e5aafd068a08d6 MD5sum: 634b74017a90396baf729df0e0bdc393 Description: Image processing toolkit for registration and segmentation - examples ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the source for example programs. Package: ipython01x Version: 0.13.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4808 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython01x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.13.2-1~nd70+1_all.deb Size: 1306320 SHA256: d259e419c42ab2f29c62a358f1b70ac483246c60043a213cf2a0e2ebb27940b9 SHA1: f1da0836b718381b16709910018994a049da53cd MD5sum: 445c27ebd25688a209351c5432f11a9b Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.13.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16664 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.13.2-1~nd70+1_all.deb Size: 7243134 SHA256: a34015da70830de42c97645c790f2fdc179da0b1b48848617dd8926b23b017e2 SHA1: 50455b67f63f0e2b7b95c4cda4c6f61feb14fa09 MD5sum: 4c412f1cfd211f9b4a81a0f7986b445f Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-notebook Source: ipython01x Version: 0.13.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-notebook_0.13.2-1~nd70+1_all.deb Size: 896 SHA256: e6bf753904ea6c85c72689ffbe60b4f7b77243e38733c4c8a486c9b6fdeb69cd SHA1: 9226720c79cf6b2fecae5206e4a5af313318d950 MD5sum: 587920ae0a922c5a9ea5d60f75c52367 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython01x-parallel Source: ipython01x Version: 0.13.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython01x/ipython01x-parallel_0.13.2-1~nd70+1_all.deb Size: 824 SHA256: 0097d83205fc332bebc5e9e178063ab3c6d740909a6c8ce7da2930d300556864 SHA1: ced489b459fa0edfd0a0414d2a0b4cac6cd7e9a8 MD5sum: 172195f46a65a28d182025cd62cd2503 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython01x-qtconsole Source: ipython01x Version: 0.13.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.13.2-1~nd70+1_all.deb Size: 910 SHA256: 009e2f9b28f70112713dfd1fa64bff7958a250fc2d5f622ef925c49d15afa5a1 SHA1: fb211e7d7981402a4329181ed727148ee38195d4 MD5sum: 9bb764488392203162c98cee5d3f794d Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12043 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython1x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython1x/ipython1x_1.1.0+git7-gf5891e9-1~nd70+1_all.deb Size: 4536746 SHA256: 852baf9b42738d3cb3610260a2172fb95197f347f5403d68470980ac1d58c022 SHA1: 0d89510fc1dedaa618407fa67d579ed6fa16bec9 MD5sum: 50bda66cac5a0b55216797762e2de43a Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-doc Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10388 Depends: neurodebian-popularity-contest, libjs-jquery, ipython1x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython1x/ipython1x-doc_1.1.0+git7-gf5891e9-1~nd70+1_all.deb Size: 4186970 SHA256: ffbd105da9db893459abf3d319ff7ebd58f492a3fad45738335c90488f65b3ca SHA1: fb31071ec088898eaac6fcc6e1c3e56f71236eca MD5sum: 9792dc5f34ffdb37466d60ac1bfe508e Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-notebook Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-notebook_1.1.0+git7-gf5891e9-1~nd70+1_all.deb Size: 910 SHA256: a2dc21ce94ea07009c263c637733d436d784f065f23cb86f9ca1a9a478104346 SHA1: 3fa9be414b9acd8cee68e5a773ca27f109bbf048 MD5sum: c62ead473d9515cdf7314225fdbc1303 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x-parallel Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython1x/ipython1x-parallel_1.1.0+git7-gf5891e9-1~nd70+1_all.deb Size: 836 SHA256: 6509f33db3634701939c662a8a3d66ff7695136545d7ae9555993e28542e3e8c SHA1: c85c4b2438715328245e44b2ad087cfb584c9159 MD5sum: 8a5cc2d4d0c568873da2f65fe69b4087 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython1x-qtconsole Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-qtconsole_1.1.0+git7-gf5891e9-1~nd70+1_all.deb Size: 922 SHA256: 35eaab30109f0f388a6911664a74f73bdac66419cec5f0193274eef59eef7308 SHA1: 1a5f95fdc76899d101c6f67ec8d0a4475e05f281 MD5sum: 6f5fcf44c21bd72bfa12f0dcb8d07f85 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: isis-utils Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 885 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libmuparser0debian1, liboil0.3 (>= 0.3.1), libstdc++6 (>= 4.6) Homepage: https://github.com/isis-group Priority: extra Section: science Filename: pool/main/i/isis/isis-utils_0.4.7-1~nd70+1_i386.deb Size: 275184 SHA256: 5427b06b38ffc47c02f41c6b9d42c8523cb504abb6ad139f9861c212215d44e0 SHA1: 20aa8e36c9cfa2227afad2f9ef72faecf8e83441 MD5sum: 4a892a1378c0d7f1322eb53062562e7e Description: utilities for the ISIS neuroimaging data I/O framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides a number of utilities to process neuroimaging data. This includes a multi-format converter and tools to inspect image meta data. Package: klustakwik Version: 2.0.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd70+1_i386.deb Size: 22258 SHA256: 5321fec361cb2ff2ae813693f8becd384c9b8faf595d7fe8707f520b1acf85df SHA1: 4ac78b37a834698a88bc89041c2d61276a727caa MD5sum: a1a16d24ce0cf8b981f2f379191839d2 Description: automatic sorting of the samples (spikes) into clusters KlustaKwik is a program for automatic clustering of continuous data into a mixture of Gaussians. The program was originally developed for sorting of neuronal action potentials, but can be applied to any sort of data. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1321 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd70+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd70+1_i386.deb Size: 415450 SHA256: 7f671eb88711bb1a0f00fb032a5d647f1505e798236480491494bc9b9467232d SHA1: 4d0d9173c0b652c6e7777128ffed08b5c89f6447 MD5sum: 27e72249e01465cc9aef4684fa20d4a3 Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig1 Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 807 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-2~nd70+1_i386.deb Size: 329902 SHA256: 8ce42a38300267f203e912f07fcdf1a3ec264f2957e2e75c4eea0d5d586a96bd SHA1: 967a67691bb3c14845a4455eec0ccaa41dbfe99c MD5sum: 63e3ee7628a0401ab9a1402abeedbe77 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig1-dbg Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd70+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd70+1_i386.deb Size: 116762 SHA256: 79fc3c09658858a51c392e39c3a6fe2bae046817afb4d8e77f24e040b709bd4b SHA1: 466a72b56b0bc0e09410a499063f5beebe8eb4b3 MD5sum: c7c9adf5c21cfe4b41c3106c91e25915 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: libcgroup-dev Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd70+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd70+1_i386.deb Size: 17400 SHA256: a510e8e72379490b0e5987512003957f636cda90d0c6b657ad1f17f85b146c0c SHA1: ff36c43e4f97fe7cf5f0a1963a6bd31b4916f0cb MD5sum: 7eaa7fa2534375bc6aaed8312972adc4 Description: Development libraries to develop applications that utilize control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . It provides API to create/delete and modify cgroup nodes. It will also in the future allow creation of persistent configuration for control groups and provide scripts to manage that configuration. Package: libcgroup1 Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 75 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd70+1_i386.deb Size: 37268 SHA256: 0bae64fba1ea1def702205889dfed7b5eafd61e86962493e952ef50cc2133277 SHA1: 5b6dd81e2ef694a149e3d1745862f819ffc137ea MD5sum: 9174141fd966b2d81a3137c6ee928ed2 Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libclassad-dev Source: condor Version: 8.2.3~dfsg.1-5~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1177 Depends: neurodebian-popularity-contest, libclassad7 (= 8.2.3~dfsg.1-5~nd70+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.1-5~nd70+1_i386.deb Size: 357446 SHA256: c202395841037fdc795561dd700b960798fd24e32805406d7251c17a1764590a SHA1: a470893a07c6b27353b8d6ad15d69b0d0f893f10 MD5sum: 81eaf7bafa335f76f626eb231e7326c1 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: libclassad3 Source: condor Version: 7.8.8~dfsg.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 843 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/libclassad3_7.8.8~dfsg.1-2~nd70+1_i386.deb Size: 282020 SHA256: 466970b407b6fda7be38b29e57261cc02ff9f1e81423da3cc83efd069d3a90b8 SHA1: 695ba5aa59ed7e2a65c7a0b4ff85f7e7a5d84ed0 MD5sum: f1a738c33a0bd8f40be71a045f38f92c Description: Condor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libclassad7 Source: condor Version: 8.2.3~dfsg.1-5~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 614 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.2.3~dfsg.1-5~nd70+1_i386.deb Size: 247654 SHA256: f4ebfc4febe602acefbed2bab1810875079ea91b80c4ba2b01ed3bf77db8cf0f SHA1: 662288481156aab8d9dd25b8f5df68bd96a4e0de MD5sum: ffc40a0e540e5b14d3e2c1e7337699d7 Description: HTCondor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libcnrun2 Source: cnrun Version: 2.1.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 294 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), 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_2.1.0-1~nd70+1_i386.deb Size: 103408 SHA256: 76623e245ca1472829621967b49722adb09c03406a72928a61c0d7291cd40396 SHA1: 798618ac6bb91bbda4cc51ebdd1b5e4bce55a1a9 MD5sum: 2afebb2be425e9c2b012fda8491d6fdb Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.1.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.1.0-1~nd70+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.1.0-1~nd70+1_i386.deb Size: 28422 SHA256: 34b232db8e97c940e397812964758409cddd62cdd7783371e105c2d5ebf59035 SHA1: 9536afd07540c316535791f0046214e12808a6b3 MD5sum: 1a5c63c7eb69d9b672e44f017c0c0554 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: libdmtcpaware-dev Source: dmtcp Version: 1.2.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.5-1~nd70+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.5-1~nd70+1_i386.deb Size: 7296 SHA256: 7fb4852effe002dfb2a1570c6d6fca891bcf3d9c6f625a4a400eb9dbbbb9ca68 SHA1: 9ea31fa84e67acb904130d9b1f3a7a7e3fba226c MD5sum: aae725245bcbf2410b4b65d6ca04285a Description: DMTCP programming interface -- developer package 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 OpenMPI, 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 provides libraries for developing applications that need to interact with dmtcp. Package: libdmtcpaware1 Source: dmtcp Version: 1.2.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 15 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.1.3) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.5-1~nd70+1_i386.deb Size: 7214 SHA256: 49b14f45f6148cdac462ebe533316370cb496e63643128018b1c8b477005ac9b SHA1: a7436f2da646739f43d36ecf912922dc9a64006f MD5sum: 14298b1b5be0b2cdc1699072be473a52 Description: DMTCP programming interface 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 OpenMPI, 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 provides a programming interface to allow checkpointed applications to interact with dmtcp. Package: libdouble-conversion-dbg Source: double-conversion Version: 2.0.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd70+1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: debug Filename: pool/main/d/double-conversion/libdouble-conversion-dbg_2.0.1-1~nd70+1_i386.deb Size: 98322 SHA256: 0810e69157adddb6cfc6d929edc6dce3785c19ed134174a4c42a086caa8c0f01 SHA1: b9d468091d7490a25dadf4838c4ea4d52c35f3e4 MD5sum: 2ef7b9a88d58b1ea942e5f59ae05e1e0 Description: routines to convert IEEE floats to and from strings (debugging symbols) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains the detached debugging symbols of the library. Package: libdouble-conversion-dev Source: double-conversion Version: 2.0.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 181 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd70+1) Homepage: http://double-conversion.googlecode.com Priority: extra Section: libdevel Filename: pool/main/d/double-conversion/libdouble-conversion-dev_2.0.1-1~nd70+1_i386.deb Size: 58972 SHA256: 0cdf336ac535e3fd2350b0ee91bade5a35deb81031aa6d6998e3aacd5e8bc098 SHA1: e29445632a54b78306f998ac02dc0eb6258fff3c MD5sum: 4a06a7938f92d54d4f42897f28a3858b Description: routines to convert IEEE floats to and from strings (development files) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a static version of the library and development headers. Package: libdouble-conversion1 Source: double-conversion Version: 2.0.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 82 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: libs Filename: pool/main/d/double-conversion/libdouble-conversion1_2.0.1-1~nd70+1_i386.deb Size: 40008 SHA256: 6dfdb0c690514bd73433730ce1c230506d6acf1f5cbc933fc043da1eba4b673a SHA1: 67a70918610289860cafcade797a19c5db947f31 MD5sum: be6b030a0626b570089427c9f7bc5a2e Description: routines to convert IEEE floats to and from strings This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a shared version of the library. Package: libdrawtk-dev Source: drawtk Version: 2.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_2.0-2~nd70+1_i386.deb Size: 43580 SHA256: 469dae99619f15969da4e43b80c3ef83704ee8c5900bd37fb0439ea22e770a18 SHA1: 96cebf3665096e5b0aac3e3519e8fd8011b828f7 MD5sum: 0d7fa300dd54149f6aa61aefa929cb2d Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 2.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 60 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreeimage3, libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.11) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_2.0-2~nd70+1_i386.deb Size: 35586 SHA256: e003207a440be631fb2b65ce7eb9b4976754f2a3bd5996cb78713fa2474894b7 SHA1: e4782d433cd491b2713386714ab475e5dab54a5b MD5sum: 7ceeb946636a6d2704a1d6c404eaa2a8 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 2.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_2.0-2~nd70+1_i386.deb Size: 61412 SHA256: e3363ee8de955c8a0843f66f55af926c2cbd5111f9cf24bb14b4fced6334f42b SHA1: e523a40ce1d1892433122c2f7209c9e5764e98b8 MD5sum: 45fbfcf89622003af23553f045c2593c Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Package: libedac-dev Source: edac-utils Version: 0.18-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest, libedac1 (= 0.18-1~nd70+1) Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: libdevel Filename: pool/main/e/edac-utils/libedac-dev_0.18-1~nd70+1_i386.deb Size: 18658 SHA256: 541f4525513b772dbb242ba44b22566cff46d1c0de1b75f53d9273fef0e1ac30 SHA1: d384a32e9db061d58e6d9a5fc0adccbe655548c7 MD5sum: 1fc0d99d746284bdbb726d21f2883e9e Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package contains development files for the library Package: libedac1 Source: edac-utils Version: 0.18-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libsysfs2 Provides: libedac Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: libs Filename: pool/main/e/edac-utils/libedac1_0.18-1~nd70+1_i386.deb Size: 15030 SHA256: 162dd7d8bacdc0d5ba9ed03fb31d41fd0fb92ff9515e6921a3974a7d7ed3c0aa SHA1: c5f7e2cf9a3ce35a10d81bbbbe4d98f41a5e239c MD5sum: 5ee7257f13541d8a9ccbf5113d5c4a75 Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package includes shared library Package: libedac1-dbg Source: edac-utils Version: 0.18-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 58 Depends: neurodebian-popularity-contest, libedac1 (= 0.18-1~nd70+1) Provides: libedac Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: debug Filename: pool/main/e/edac-utils/libedac1-dbg_0.18-1~nd70+1_i386.deb Size: 31282 SHA256: 32298e876f31ea503e568b06dfc2a3bc2dbb0d89233226ce142a45f92732ea8e SHA1: 273187c50f6ce3ef75ba80854f09605f12d0fbf8 MD5sum: 0f3e16437aefd319327895e6cfef2a3c Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package includes shared library with debugging symbols not stripped Package: libeegdev-dev Source: eegdev Version: 0.2-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libdevel Filename: pool/main/e/eegdev/libeegdev-dev_0.2-3~nd70+1_i386.deb Size: 22432 SHA256: a855297f19d4a7419bfcce8f7ca9d7b24255ede952bb0da899b9eeda7fa55ba1 SHA1: 1ecb05ffcdca1550e8b17bb0d507266a73f1ae16 MD5sum: 9fbec4ae05d8141fd5ec99b85fa92505 Description: Biosignal acquisition device library (Developement files) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the files needed to compile and link programs which use eegdev. Its provides also the headers neeeded to develop new device plugins. The manpages and examples are shipped in this package. Package: libeegdev0 Source: eegdev Version: 0.2-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 75 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~) Recommends: eegdev-plugins-free Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/libeegdev0_0.2-3~nd70+1_i386.deb Size: 45432 SHA256: 02b662f733b417bcae9a270d7f0d46b19b97003faf92fbe442dca9ff9dd9ce27 SHA1: bade1fdbb40f80cbab24e0d2fbd7dad61b04ded3 MD5sum: 047181a8fbc5e330b30c4af1a8982e9f Description: Biosignal acquisition device library eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the core library Package: libeegdev0-dbg Source: eegdev Version: 0.2-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 154 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: debug Filename: pool/main/e/eegdev/libeegdev0-dbg_0.2-3~nd70+1_i386.deb Size: 136716 SHA256: 56d71de8349b19ea7ece753cae740a71561b00f69f4835acaad778287831c26a SHA1: b6dae3bc4e62b3b9d6990c0174f2afe7388a9b01 MD5sum: 6f6e4f7d9aa3d3b7b4b564072f3a175b Description: Biosignal acquisition device library (Debugging symbols) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package provides the debugging symbols for the library. Package: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd70+1_i386.deb Size: 509876 SHA256: ff86b3cfc5828d83864e0294226170c314c36b995883869520f2eb0e95136666 SHA1: 1d8b0679d5d0936eef23f1e8e03ed5ffc4a640d1 MD5sum: 01e5c31cf474862b8a332fcd83367025 Description: lightweight C++ template library for linear algebra Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . Unlike most other linear algebra libraries, Eigen 3 focuses on the simple mathematical needs of applications: games and other OpenGL apps, spreadsheets and other office apps, etc. Eigen 3 is dedicated to providing optimal speed with GCC. A lot of improvements since 2-nd version of Eigen. Package: libeigen3-doc Source: eigen3 Version: 3.0.1-1.1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10344 Depends: neurodebian-popularity-contest, ttf-freefont, libjs-jquery Suggests: libeigen3-dev Homepage: http://eigen.tuxfamily.org Priority: extra Section: doc Filename: pool/main/e/eigen3/libeigen3-doc_3.0.1-1.1~nd70+1_all.deb Size: 2377384 SHA256: a49fd82e5f6a6d048154bd60d83245d840e38ec31ca1c90607c04479eaf6f04a SHA1: 551f098e9a8eae57dc8ac6baceb92ff5c87871e9 MD5sum: aefa7c3d5f3f5bfd5e3a481d932d7477 Description: eigen3 API docmentation Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . This package provides the complete eigen3 API documentation in HTML format. Package: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6343 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd70+1), libfreeipmi16 (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd70+1_i386.deb Size: 1251904 SHA256: 430c0130f2f138a23e90135c9c6a37e02eb906369ba1c6bcbedd911544db428e SHA1: 65a84974399dcb37a7f24ec194d6ee99edac3535 MD5sum: 167b6f91a170a07eebede403cdebed46 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: libfreeipmi12 Source: freeipmi Version: 1.1.5-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3813 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.1.5-3~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi12_1.1.5-3~nd70+1_i386.deb Size: 987676 SHA256: 99c581e3037fd3edd83bd7b3a1b9357be84d2d699c9ccf69467ce90588c49399 SHA1: 1baa817c707b7519882efb498afd7441adaa8392 MD5sum: 0421ebd383d43d2576cda65e58ef8c87 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: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4139 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd70+1_i386.deb Size: 963476 SHA256: 7b4911679a1efd46e6b5aca81242a06077fe43bfefb621eae686eb2f658f3fe2 SHA1: 7ec68cbf5964734d5fa20b4afcf4438fe5643b5b MD5sum: 0abee32ead466ea28e529575529cc000 Description: GNU IPMI - libraries FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . OpenIPMI, KCS, SMIC, SSIF, LAN drivers, and an IPMI API in a C Library. Package: libfreenect-bin Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 249 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.5 (>= 1:0.5.2), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.4.0) Breaks: libfreenect-demos (<< 1:0.1.2+dfsg-1) Replaces: libfreenect-demos (<< 1:0.1.2+dfsg-1) Homepage: http://openkinect.org/ Priority: extra Section: utils Filename: pool/main/libf/libfreenect/libfreenect-bin_0.5.3-1~nd70+1_i386.deb Size: 75144 SHA256: 81996a599529a7d1c275570a03424ccb67673aa921142f5a4c173bbe74a38f9e SHA1: c12c50d8f45199a23b5b0060d547d9735a5b6279 MD5sum: ffdfa87f7169b854b4f26437173c8024 Description: library for accessing Kinect device -- utilities and samples libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package includes utilities and sample programs for kinect. Package: libfreenect-demos Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.5.3-1~nd70+1_i386.deb Size: 9194 SHA256: 5ffbc5ea8b5912208e555a148fb1e6c8e2601b55c9920f986cdf5d45b3443abc SHA1: b6953e61bde059dc347218a2ada92617992923a9 MD5sum: 84ddf3738e4366cb49abe4d4d177ed82 Description: library for accessing Kinect device -- dummy package libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package is a metapackage to do the transition from libfreenect-demos to libfreenect-bin. This package can be removed after installation. Package: libfreenect-dev Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.3-1~nd70+1), libusb-1.0-0-dev (>= 1.0.18~) Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.5.3-1~nd70+1_i386.deb Size: 21614 SHA256: 8ca66b9d30ffa0c1e15c85422b1510189a9ef03fd9b55e5d2a4632eb0c4b48b6 SHA1: f3aa3c56b259d3a55bf42b6dba8f9352d06e4fe4 MD5sum: 5c4e6f0d32261057481757773b11d3c3 Description: library for accessing Kinect device -- development files libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 591 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.3-1~nd70+1_all.deb Size: 125314 SHA256: c0dbeb0fa61eb81365dc6f4a14c6368f0ae2f800c10d3302e814381b227c68d7 SHA1: 50d172ed414072c52a35443c5610bc15b73b4bee MD5sum: 8c814d9eeeb7e8d158456cc9fffb1bf8 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 89 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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~nd70+1_i386.deb Size: 36974 SHA256: 1cf5f09c66bc91f5630c8d4b4801beec660a8f0e67fb9a1135f1235271fc6d26 SHA1: 60259a06537808bf5965131c7caaa652959ade6e MD5sum: 718fdc4d88e5944822c245deeebc29a0 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: libfreenect0.5 Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 156 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.12) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.5_0.5.3-1~nd70+1_i386.deb Size: 50924 SHA256: 9ae11ad853664831d47e9d713fdd5cb9581ead4ab135687466f48d6dd4453dd9 SHA1: 0cddb058ed0cce77bf693400d59a938286bd94fe MD5sum: b68eef2c06467d54d5942d12a3aff82a 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: libgdf-dev Source: libgdf Version: 0.1.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-2~nd70+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.2-2~nd70+1_i386.deb Size: 19766 SHA256: 967417ba81d31914995db73727469a23daf9f89b7b028a599a8a0a9da9606373 SHA1: 95cfbc768b60d5b669016c4ac5fbff216b0aa41b MD5sum: 2ecf861db67718ae557fb8582576100a Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 702 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.2-2~nd70+1_i386.deb Size: 220094 SHA256: f495574c8600a1088f3011f4500edf7830c6156e3d4ee04aa78bfb7e9cdf9d0a SHA1: f68bcd5b9494f9d6b7c9f76fc5daed6f490e0bc0 MD5sum: 1a9a84823ace804039433f0a2251177f Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1581 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-2~nd70+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.2-2~nd70+1_i386.deb Size: 454420 SHA256: 34413648a35b99d1282cc806a1ef11359eda6e7b57a26bd68e77dc3e709e0582 SHA1: 9717750a0803b01393770a65f3f7181710ded220 MD5sum: a8c3bbe0572415e8315922e5ad23c068 Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 210 Depends: neurodebian-popularity-contest, libgiftiio0 (= 1.0.9-2~nd70+1), libnifti-dev Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-2~nd70+1_i386.deb Size: 59398 SHA256: a5e67c43a31a465b7ed67f48edef1d907058a81bf68f476eef28c8bbaa72ddd1 SHA1: 42d8a9943dfc519250b3890501b35b3400b77a50 MD5sum: 97c4954fc1858d6624cd3c73a2ebd4b3 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 170 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), libexpat1 (>= 2.0.1), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-2~nd70+1_i386.deb Size: 54132 SHA256: c1112e3d1336828eb2939c69f1179eeb0d73dcd660f5409c6db340902e840416 SHA1: 47613609c2111929292a6aea00f5aac29ec7545c MD5sum: 5671614feb665b816be5fd2d31af71b8 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 542 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 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~nd70+1_i386.deb Size: 166944 SHA256: 9ba1f32ddcd73af1eae30856f37bb069a0a6f3cd010a04013f06e99c692fbd80 SHA1: 4273dcd06636cba15c13e58bd16c7a454d59ae91 MD5sum: 369e2974e50d56c322dfe6dd1e23eb3d 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd70+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd70+1_i386.deb Size: 40120 SHA256: ba5505edf03251d0fc413c07c87188adcd4d4e30ed128af99f8885d82cf2cd44 SHA1: b7089ee5e4e564f261899c5d3863222f38bf180b MD5sum: d459fb5e5d1beced1f7e5080437cbcec 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd70+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~nd70+1_i386.deb Size: 153180 SHA256: 833750d235946b0bab716fcd03cc5d8a128f1d284360574ddbc0409b294e0aaf SHA1: e6ed1b004d78f341becb9273525a529a19eb3462 MD5sum: 249a1d61b82e2dbe729e91f461b7ae21 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 482 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 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~nd70+1_i386.deb Size: 148618 SHA256: e3b4b19d5a6ea0bf1eeda6abd84e398cacbacbe40db7c37aff2fee2c6950b5a9 SHA1: b26bb616ab69464fd5ac96315f158c5d4ab5f3cc MD5sum: 3ed3def0b1017d985f262201eb962e6c 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd70+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd70+1_i386.deb Size: 32292 SHA256: 67efe54fdb9194f2e41ec9bbaa005b4235ffa6dd617355ad9f86709f0244b125 SHA1: 7769288a7a169c44f888bc823fb20e012378cdb4 MD5sum: 9ebadedc1781f9c4153a4494bfee314f 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd70+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~nd70+1_i386.deb Size: 8796 SHA256: 0b6d87917568f73061c152f72b67dfee512779b7b7f190aba3afe3764fa0b03b SHA1: 8381c2a6027c6148fcd970d85d41b4d8d094f681 MD5sum: e6c2bde87dca6caed35d4da96ac98938 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: libgoogle-glog-dev Source: google-glog Version: 0.3.3-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 341 Depends: neurodebian-popularity-contest, libgoogle-glog0 (= 0.3.3-2~nd70+1), libgflags-dev Homepage: http://code.google.com/p/google-glog/ Priority: optional Section: libdevel Filename: pool/main/g/google-glog/libgoogle-glog-dev_0.3.3-2~nd70+1_i386.deb Size: 102730 SHA256: 1ea8e3738d59e67a1da885c2e4ea13e960917fed3ba229471b00c4a9e7e381ca SHA1: 615c430c0e85fee6db16b144266955df8ffc6f56 MD5sum: b7f930369f6ee253fda728a15ccad4ea Description: library that implements application-level logging. This library provides logging APIs based on C++-style streams and various helper macros. . This package contains static and debug libraries and header files for developing applications. Package: libgoogle-glog-doc Source: google-glog Version: 0.3.3-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 30 Depends: neurodebian-popularity-contest Homepage: http://code.google.com/p/google-glog/ Priority: optional Section: doc Filename: pool/main/g/google-glog/libgoogle-glog-doc_0.3.3-2~nd70+1_all.deb Size: 14732 SHA256: 2fbceb6ae2102be2438e02e767a5c7b8c45fccd1a9bcb4695085b2b6b5628dff SHA1: 68ad48be2effa1bca2f0fc0879da5cfffe4c913c MD5sum: 313e64eb90ad1ced8dce64071e685060 Description: documentation of gloogle-glog This library provides logging APIs based on C++-style streams and various helper macros. . This package contains documentation files. Package: libgoogle-glog0 Source: google-glog Version: 0.3.3-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 165 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgflags2, libstdc++6 (>= 4.1.1), libunwind7 Homepage: http://code.google.com/p/google-glog/ Priority: optional Section: libs Filename: pool/main/g/google-glog/libgoogle-glog0_0.3.3-2~nd70+1_i386.deb Size: 67224 SHA256: dcca5cb91a758ddceda011d32e467288a666aeedb66d425df280f493bece37b2 SHA1: 3fc8401821992276e3059a388a9634b15d6d364e MD5sum: dcd8b189138a100a09190b7981183210 Description: library that implements application-level logging. This library provides logging APIs based on C++-style streams and various helper macros. . This package contains shared libraries. Package: libguac-client-rdp0 Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 90 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.6.0), libfreerdp1 (>= 1.0.1), libguac5, libogg0 (>= 1.0rc3), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2), ghostscript Recommends: libfreerdp-plugins-standard Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-rdp0_0.8.3-1~nd70+1_i386.deb Size: 37446 SHA256: 6e0482f8925a909935929ad956cca44fff01b6fd51a091930fa09f6a91140a71 SHA1: 13628a7fc20ca8d49596f47aac8c362cf3b922ab MD5sum: cc8fcbe084e3af2e06d45cdf86576882 Description: RDP support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the RDP protocol (Windows Remote Desktop). Package: libguac-client-ssh0 Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 55 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libguac5, libpango1.0-0 (>= 1.22.0), libssh-4 (>= 0.3.91) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-ssh0_0.8.3-1~nd70+1_i386.deb Size: 27150 SHA256: 4300acd92e69e080b492d3a5554fae0836ca7db5321528c6d4628014d6537ba3 SHA1: e1bb82fe983603463ce034fa2ca1840f7b88271d MD5sum: 230aa8a41ed9686efe094824310222e2 Description: SSH support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the SSH protocol. Package: libguac-client-vnc0 Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.6.0), libguac5, libpulse0 (>= 0.99.1), libvncserver0 Recommends: vnc4server Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-vnc0_0.8.3-1~nd70+1_i386.deb Size: 12366 SHA256: c675cedf8a4210be5169be13069715d8637e0e8805a15f035dda16d2d93d5b59 SHA1: eb540efeedeceab84b74bb448b30b382cfd60f89 MD5sum: df9f645f5a60b2c7faca5188381b6b75 Description: VNC support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 188 Depends: neurodebian-popularity-contest, libguac5 (= 0.8.3-1~nd70+1) Replaces: libguac1-dev Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libdevel Filename: pool/main/g/guacamole-server/libguac-dev_0.8.3-1~nd70+1_i386.deb Size: 43724 SHA256: 3c26cbfce0c1b3c99c361cddb2ded5b03023c00e1a24a1b287befbf1fa935eb2 SHA1: 8da579b23f2c352320f33b6e8f99572f276e8469 MD5sum: 4e94e137aaa38b639d8f7baec121bc43 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac3 Source: libguac Version: 0.6.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libpng12-0 (>= 1.2.13-4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac3_0.6.0-2~nd70+1_i386.deb Size: 18898 SHA256: 8ece96e808e6233682ecb92eee85f0ca5eb4a70bc93ddc637a04e2863d349c3c SHA1: 38307957a82a93873e9d4b4218f1a7e5c5ee3d77 MD5sum: 3ccf0c81208ae1ccd8778f89f49f299d Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libguac5 Source: guacamole-server Version: 0.8.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 63 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.2.4), libogg0 (>= 1.0rc3), libpng12-0 (>= 1.2.13-4), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac5_0.8.3-1~nd70+1_i386.deb Size: 27210 SHA256: 6249eb16110e194e6a81156506849ebd6402b925a383bc56c4d475a15e343c2e SHA1: 7f0e15e628394fc4ffe60d9f61c088748c59bb80 MD5sum: 3d300dfe67ee403f1b9843c6241b50c2 Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libinsighttoolkit4-dev Source: insighttoolkit4 Version: 4.2.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 25773 Depends: neurodebian-popularity-contest, libinsighttoolkit4.2 (= 4.2.1-2~nd70+1), libgdcm2-dev Recommends: libfftw3-dev, uuid-dev Suggests: insighttoolkit4-examples Conflicts: libinsighttoolkit-dev, libinsighttoolkit3-dev Replaces: libinsighttoolkit-dev Homepage: http://www.itk.org/ Priority: optional Section: libdevel Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4-dev_4.2.1-2~nd70+1_i386.deb Size: 5275622 SHA256: 40380ba2b9e552260e8bdcdb4289c53b401623800775ffa9a094548b684045a5 SHA1: 03b4f96ab446f5be31bcea6fe64d5db8dcf1abd4 MD5sum: 120277f1d4007aa68dc5b7567efbd07f Description: Image processing toolkit for registration and segmentation - development ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the development files needed to build your own ITK applications. Package: libinsighttoolkit4.2 Source: insighttoolkit4 Version: 4.2.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20738 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgdcm2.2, libhdf5-7, libjpeg8 (>= 8c), libminc2-1, libnetcdfc7, libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.3) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.2_4.2.1-2~nd70+1_i386.deb Size: 6987116 SHA256: 112fcf13c312f3c5a5d2413ef3d0689163a03f439c98cad396ac150a61e333ab SHA1: 8225d12caed33d7bd12776e316a5ac950aec95ab MD5sum: 626934b716b761fe516c58452eb39bb1 Description: Image processing toolkit for registration and segmentation - runtime ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the libraries needed to run ITK applications. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd70+1), libipmiconsole2 (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd70+1_i386.deb Size: 127682 SHA256: b3c7ca92eed9db7ffd1fd7ef0429ee7415deaa5aeaa8f5bacf09f1bece034258 SHA1: 98536b5cfe297763229ed380796686e6d078a16c MD5sum: 0c7280f62fd76af214dd8405ab59ca98 Description: GNU IPMI - ipmiconsole development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmiconsole. Package: libipmiconsole2 Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 257 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd70+1_i386.deb Size: 98242 SHA256: 18d73e97df5150e8263f0889c4bb7bdf3144373687e153e782f04c4391b166d7 SHA1: 4b5344975aae4062255c7736c58b8eb48d9c83fb MD5sum: 595f3b272ab02402b4669cad83ed7d55 Description: GNU IPMI - Serial-over-Lan library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for Serial-over-Lan (SOL). Package: libipmidetect-dev Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd70+1), libipmidetect0 (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd70+1_i386.deb Size: 37304 SHA256: 41a4b0bb07d08b0558ee358a206f9219f96468278f23fc412037aed999cd8f68 SHA1: b61cda3564d84824aa7e07598fac048f868bbf2c MD5sum: 97db643bf773909805f47ae8451e227e Description: GNU IPMI - ipmidetect development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmidetect. Package: libipmidetect0 Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), freeipmi-common (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd70+1_i386.deb Size: 29408 SHA256: 3b2d997800986cc3753fe974deb9742357f0ba95d984b1888caa6a604d5bfa54 SHA1: 6821a6e2c230c8b72cf3be7cf513dceefd5f6239 MD5sum: d06f3123886cc49338b65def51560acf Description: GNU IPMI - IPMI node detection library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for IPMI node detection. Package: libipmimonitoring-dev Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 266 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd70+1), libipmimonitoring5a (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd70+1_i386.deb Size: 77448 SHA256: 97854f0153f2c10ba21cd3071b94145048c29f59b6e9cc73b0a9c28c48c362ea SHA1: b48dd105d8bcb937f677e38fb0c67d12c936ee91 MD5sum: 2595c501dcf70e9eab9d4de5b2510fdf 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: libipmimonitoring5 Source: freeipmi Version: 1.1.5-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi12 (>= 1.1.5), libgcrypt11 (>= 1.4.5) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5_1.1.5-3~nd70+1_i386.deb Size: 190826 SHA256: 95338a6b36f630737109ef1a8a4246e693fa93560469729c15111e1e748856d9 SHA1: 535cd5bb636b8e4309787576623118ec0a08c213 MD5sum: 7439cfa506ad66ba7567f273fee18b5f 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: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 118 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.4.9-1~nd70+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd70+1_i386.deb Size: 51772 SHA256: 02cb9d233d1ea5e73a38e38d8f4481fd49bf9a08eaff661f9df2b2fcef32f957 SHA1: 7a5921914269f7676efbbcf3fd119a09451e4298 MD5sum: 39eb33d576f7aacdee50ae5652651c16 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: libisis-core-dev Source: isis Version: 0.4.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 260 Depends: neurodebian-popularity-contest, libisis-core0 (>= 0.4.7-1~nd70+1), libisis-core0 (<< 0.4.7-1~nd70+1.1~) Homepage: https://github.com/isis-group Priority: extra Section: libdevel Filename: pool/main/i/isis/libisis-core-dev_0.4.7-1~nd70+1_all.deb Size: 68948 SHA256: 71ba81e336312edd85331e45ad6c689d1133fe332506a79eb1d4e41946534675 SHA1: 7761d9efa1a6a2cadc67a0f2e546b165f088f855 MD5sum: cc18de68a3f8d8942ad55d38751a2d01 Description: I/O framework for neuroimaging data This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides headers and library to develop applications with ISIS. Package: libisis-core0 Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8962 Depends: neurodebian-popularity-contest, libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.10), libstdc++6 (>= 4.6) Recommends: libisis-ioplugins-common, libisis-ioplugins-dicom Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-core0_0.4.7-1~nd70+1_i386.deb Size: 2055198 SHA256: cecbe1ff06f1eeff1050c45d32a8f6ea82459aa37da0b0d313e5c335b3636b61 SHA1: 0b8f949b2057c3d7cfaa1fb54e5424dadc7cdff5 MD5sum: d86509b6afccd2632a5c2dd28fa0cbfe Description: I/O framework for neuroimaging data This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This Package provides the core library needed by all applications that are build upon ISIS. Package: libisis-ioplugins-common Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4950 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-iostreams1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libbz2-1.0, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libvia2, zlib1g (>= 1:1.1.4) Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-ioplugins-common_0.4.7-1~nd70+1_i386.deb Size: 1464592 SHA256: 93291909e6e93c8efaad9caf7b33b2322b7566dd846e39263c0555d6bf0b6d3c SHA1: 974109f3afcdb077023dabd05c24f6e3b808beb5 MD5sum: 9ffa35473fe1f4b7a1e54e202ee1cfa2 Description: data format plugins for the ISIS framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides plugins for data in NIfTI, PNG, VISTA format, raw-data access, as well as plugins for gzip-compression and tar-archive support. Package: libisis-ioplugins-dicom Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1267 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.1.3), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtiff4, zlib1g (>= 1:1.1.4) Homepage: https://github.com/isis-group Priority: extra Section: science Filename: pool/main/i/isis/libisis-ioplugins-dicom_0.4.7-1~nd70+1_i386.deb Size: 377378 SHA256: c2b91596b9ba07db2e45f47fd964cbac0df38c4562dbcfed28071785f80420d4 SHA1: 231ba57c10adbb38a54be6aea4e56ffcc7c28cf1 MD5sum: 2db20b5164d2025054fa04db533c7eb6 Description: dicom io plugin for the ISIS framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides a plugin to read data from dicom datasets. It reads single files, or whole directories (a DICOMDIR is not needed). Package: libisis-qt4-0 Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6) Conflicts: isis-qt4 Replaces: isis-qt4 Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-qt4-0_0.4.7-1~nd70+1_i386.deb Size: 49604 SHA256: f24cb7f02e6a68b174f3826d722027d2755344f04a803abbefaea0c15553ea63 SHA1: c8d349600e2847daa45c0960b9f4abaf92ff8f88 MD5sum: 2a6767e35d2c327115c42de7cdc05011 Description: Qt4 bindings for ISIS data I/O framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: libisis-qt4-dev Source: isis Version: 0.4.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Depends: neurodebian-popularity-contest, libisis-qt4-0 (>= 0.4.7-1~nd70+1), libisis-qt4-0 (<< 0.4.7-1~nd70+1.1~), libqt4-dev Conflicts: isis-qt4-dev Homepage: https://github.com/isis-group Priority: extra Section: libdevel Filename: pool/main/i/isis/libisis-qt4-dev_0.4.7-1~nd70+1_all.deb Size: 5992 SHA256: f848c976204b1b3090c9bcba159204365ee5620986f0cadd15bc6a6b8a9dde80 SHA1: a9cc9f1a3bd89a7545ffe60b6ccc874c874986a6 MD5sum: 96ef7f5956383a9fe46cea8c8843d7cd Description: Qt4 bindings for ISIS data I/O framework (development headers) This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libdevel Filename: pool/main/m/mcpanel/libmcpanel-dev_0.0-1~nd70+1_i386.deb Size: 2400 SHA256: 59eaff9f071cc4479b916da38622dc7b737d7512304167dc943cd9604a88fc07 SHA1: 3272017794c376eb4df5c62b441706757b7fccfb MD5sum: 38ede0b381de8202d37494388ad4515c Description: Library to display multichannel data in realtime (Developement files) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the files needed to compile and link programs which use mcpanel Package: libmcpanel0 Source: mcpanel Version: 0.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.14.0), libgtk2.0-0 (>= 2.14.0), libpango1.0-0 (>= 1.14.0), librtfilter1 (>= 1.0) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libs Filename: pool/main/m/mcpanel/libmcpanel0_0.0-1~nd70+1_i386.deb Size: 54116 SHA256: e06fd86a81cd02baadcb485648d6b032c9d11366e565d6509042ee1f2162a254 SHA1: b7f93d99947cac8c581c2d2efdc5e47d1dc7636b MD5sum: 78e6c3e38a85c5593e686c3ef50abfec Description: Library to display multichannel data in realtime This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. Package: libmcpanel0-dbg Source: mcpanel Version: 0.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 279 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: debug Filename: pool/main/m/mcpanel/libmcpanel0-dbg_0.0-1~nd70+1_i386.deb Size: 117516 SHA256: d7778f90e28ffc7628343940231d5c2711ff1ae624e535897f8c8de1af2b6e12 SHA1: 32f83467828f89c3f878c04b017e313a1b3274a5 MD5sum: 957b4b1c88b8444e04476ce4225a82f2 Description: Library to display multichannel data in realtime (Debugging symbols) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the debugging information of the library. Package: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 22841 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-serialization1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-test1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libdcmtk2 (>= 3.6.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.31.22), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp7, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2 (>= 2.1~), libtiff4 (>> 3.9.5-3~), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.34.2) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd70+1_i386.deb Size: 3695714 SHA256: 1d2f8266eaf281d5a0bfa2b118aceb5e926552114fb57095f727b8d3e83e407e SHA1: 5fa0d924b7ef3e032338a131413461d42f604c0e MD5sum: e559ff4e0aa73e7770ab6f0978fdbdeb 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 56256 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd70+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd70+1_i386.deb Size: 50871000 SHA256: 52b76a19468f60f0511f58fc322ed228f690571b38eba2f7d60aa3ba91c676d0 SHA1: 41e17b0d303e204186d2155d48e36c92e5cd59cd MD5sum: a2aafe34a1f894c9f4c695fb82e6a44a 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1093 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd70+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~nd70+1_i386.deb Size: 177524 SHA256: effd67c9ff25774d2ae67076a048a22e87bb03142ce1c0e1e3b045bcb03eedac SHA1: ab9c1c7a5451589b61c70a4aef7ef9a52cd9132a MD5sum: b484a6d85a997c56d428113924fb71d6 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12253 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~nd70+1_all.deb Size: 748032 SHA256: 8527b0bb4b3aa25c0cf0b7549c919d530721984768142b1c9cbe54bc501b2f60 SHA1: 9f0eb7c3aee4244a01b217c48fe20aa6e2f8b4ee MD5sum: bc5873ea130b7d109b727560d966df3a 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: libmialm-dev Source: libmialm Version: 1.0.7-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 285 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd70+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libm/libmialm/libmialm-dev_1.0.7-2~nd70+1_i386.deb Size: 114046 SHA256: 90332e94fd7cf0f765a5297f0374de66639b917dc7b6479ef422ee99bc16fccb SHA1: 1797a57cfb5ec3e016dfb0b3f5f249df5ecb2ea0 MD5sum: 32f6cddea07ab2230224684e665be327 Description: Development files for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the development files - headers, shared libraries, and pkg-config files. Package: libmialm-doc Source: libmialm Version: 1.0.7-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: neurodebian-popularity-contest Suggests: devhelp Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/libm/libmialm/libmialm-doc_1.0.7-2~nd70+1_all.deb Size: 25632 SHA256: 53dfaf199e159648ef41671c3db6a6db19903b7ab23a5f0c3320deed90205c08 SHA1: 7d71dc5cbe43db379c6e192de9e11aff59904350 MD5sum: 443952d2baa93870673c8bf9dba721e9 Description: Documentation for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the library documentation. Package: libmialm3 Source: libmialm Version: 1.0.7-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libglib2.0-0 (>= 2.16.0), libxml2 (>= 2.7.4) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libm/libmialm/libmialm3_1.0.7-2~nd70+1_i386.deb Size: 22900 SHA256: a9e6a782a763c86d3bd56c9ae2a0ef71616b4974eec61ef4a3951ed44b719fb4 SHA1: 2877c9597fb075d908c67748a77c24e449884994 MD5sum: b273059f244bd351a4dfea88fa3bbe1e Description: Landmark handling for the MIA tool chain This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. Package: libmialm3-dbg Source: libmialm Version: 1.0.7-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd70+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libm/libmialm/libmialm3-dbg_1.0.7-2~nd70+1_i386.deb Size: 58194 SHA256: 9ddf1cd8b0176eb7c5ae2fae3bbd9baacf4fd21668083c29e7233351150208d0 SHA1: 45ef4d7c5298453c766f173d10cde4b92b15a5de MD5sum: e685920bb6255c3b702309c7e6f59882 Description: Debug information for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package provides the debug information of the library. Package: libmtcp-dev Source: dmtcp Version: 1.2.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libmtcp1 (= 1.2.5-1~nd70+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libmtcp-dev_1.2.5-1~nd70+1_i386.deb Size: 5562 SHA256: 272dd7e21fd4a7b12df8e30b02b124462865c9d5c52aa7a6a6d37019e018f626 SHA1: 1b345aec4c9a1234e1d5e6d5c0405468c8c535ea MD5sum: 4e37350dfa1afc8e106e006be188b94b Description: Developer package for libmtcp 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 OpenMPI, 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 provides header files needed for building programs with libmtcp. Package: libmtcp1 Source: dmtcp Version: 1.2.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libmtcp1_1.2.5-1~nd70+1_i386.deb Size: 40744 SHA256: 7c0d0c39e91866daa0cddd51343b03ed366d17b14a63735ae0fe771f5614c21f SHA1: 97bfd4d56a98eae8e2b2a19fe62324b92de3d5de MD5sum: 59cbd18177e671c4f4f99b394bd32254 Description: DMTCP library needed for checkpointing a standalone process 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 OpenMPI, 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 provides libmtcp which is needed by DMTCP to checkpoint a single standalone process. Package: libnifti-dev Source: nifticlib Version: 2.0.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 443 Depends: neurodebian-popularity-contest, libnifti2 (= 2.0.0-2~nd70+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~nd70+1_i386.deb Size: 157440 SHA256: 66bc2bdabab08ae952f2184005c7baae3de279167ea314f49149d6dbfce50e1c SHA1: 01d0dc3c32143a766d7eb3c8632e0283938d87c2 MD5sum: 8b07ac2321948b1a7f1925350f2c17b5 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1537 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~nd70+1_all.deb Size: 252296 SHA256: 11a4a201e5e15312469bb279c5bc9cacafc822353fdbc14d760e8c98eec0d892 SHA1: 90350f4a2203772a84b66713b14600b032d5f2cc MD5sum: 7476594f01c396eb51e340187d187ef4 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 288 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-2~nd70+1_i386.deb Size: 114214 SHA256: 50bac127b015ac73bff5a09218de102ec1146fd2b7c9cfa59860fd1ed3ffb01e SHA1: d1675125a8d527615c7edc86d7a62f4439c68c33 MD5sum: 48bbaebe93531219f4963202176b72cc 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: libnlopt-dev Source: nlopt Version: 2.4.1+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 529 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd70+1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libdevel Filename: pool/main/n/nlopt/libnlopt-dev_2.4.1+dfsg-1~nd70+1_i386.deb Size: 200848 SHA256: c5c993264eae4e30cc992ff4f0db5684492fb0a68a323c9ab68cf1c2073461c3 SHA1: 0410d673e09246421a5f700ca590662e104773c4 MD5sum: 7680a61b36dc4c46837caf5575e6515d Description: nonlinear optimization library -- development package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the header files, static libraries and symbolic links that developers using NLopt library will need. Package: libnlopt-guile0 Source: nlopt Version: 2.4.1+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 132 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd70+1), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), guile-1.8 Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt-guile0_2.4.1+dfsg-1~nd70+1_i386.deb Size: 49702 SHA256: 6be8243f1df26e4fe89a0aa1320d1999d5cc60b02bdf29a5058eb4c87153e93f SHA1: 186743c935f2570176dc0e818bf7ab7f9c307a2a MD5sum: 742c6ae402abe9c7180971df77c52bc1 Description: nonlinear optimization library -- Guile bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the bindings for GNU Guile. Package: libnlopt0 Source: nlopt Version: 2.4.1+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 421 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt0_2.4.1+dfsg-1~nd70+1_i386.deb Size: 182016 SHA256: f003950b1efbd0622e462e39a8033b243e5489bb52bc802609535bc33bf19f7b SHA1: ae0dcfaaa5772aa907baa93e19bd71e7b7018adb MD5sum: 3c59913a9c0be7b068396359efeaf70e Description: nonlinear optimization library NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package provides the shared libraries required to run programs compiled with NLopt. To compile your own programs you also need to install libnlopt-dev. Package: libodin-dev Source: odin Version: 1.8.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 15881 Depends: neurodebian-popularity-contest Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.5-1~nd70+1_i386.deb Size: 4259704 SHA256: 18d1bd79cb5b723961e56976280138b1cf7e7b9c4a260cfe1885d9921aa15181 SHA1: 2c7379b426d1f0ed1ec2fb4f7a6dfb00bc0c6cbf MD5sum: 2f5bd48c71b828bf4450c1e362071ed7 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 197 Depends: neurodebian-popularity-contest Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-4~nd70+1_i386.deb Size: 42584 SHA256: 1b138256f37bacdb0e0ee52c85b109d94fb74ab9fd373d0c768d7f54940b320e SHA1: 5b7fc51b5f0f712c1ff7c72099d0d255d9f44646 MD5sum: ca8bad6ee7da2cd8fa95cd049c5f6c21 Description: openmeeg library -- development files OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1276 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.6) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-4~nd70+1_i386.deb Size: 259942 SHA256: 59afb52c5b48857db66b5dc041d762c15f0d8a86bac8471ff5ec0be5fdf01edc SHA1: 37e92d6e4dc204ad4097e3964db474773f155c0a MD5sum: c949750ac5614883f7b6a79918ecd878 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides dynamic libraries. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7351 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.49.0 (>= 1.49.0-1), libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph80, libopenthreads14, 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~nd70+1_i386.deb Size: 2057138 SHA256: 4b2d3ede35fe50312692b13d1e0e97939352ad0132ee823b41efc31fc53c6cc8 SHA1: d184f95630dee05b6c12d594737282b6ddccc25c MD5sum: 0f804589d2b38ffa193db954b328de65 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd70+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~nd70+1_i386.deb Size: 339156 SHA256: b70f47717e5a3f5ae3876b559268328e13c3e82ec4eb80c9f4a23c83a5293d7c SHA1: 2265a7b5e349baed71b90184c7981ca272123ba4 MD5sum: a9596397c455cf069068e7873a16b6f5 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 43478 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~nd70+1_all.deb Size: 5036628 SHA256: 9706d2dae1174bcb73c71fd2e55cd6e028953976d2ac3dedc08a0b89e510eb20 SHA1: 1108143f738996653844f935c3a678e96ea2913e MD5sum: 7643d3db48c92efd846dfd839d293b36 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: liborthancclient-dev Source: orthanc Version: 0.7.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, liborthancclient0.7 (= 0.7.2-1~nd70+1) Homepage: https://code.google.com/p/orthanc/ Priority: optional Section: libdevel Filename: pool/main/o/orthanc/liborthancclient-dev_0.7.2-1~nd70+1_i386.deb Size: 19248 SHA256: 6751765ec5bf7067a22700628f9f47cd960e40117392e3391979d3b0ab6f05c7 SHA1: 82d12b861e185909cf0a68aa9ce3230ff679bf40 MD5sum: 308f6c42cec0856136c549d9882b2bc1 Description: Orthanc Client development files Orthanc Client is a library to access the content of a remote instance of Orthanc. Orthanc is a lightweight, RESTful DICOM server for healthcare and medical research. . This package includes the header files for C++ code. Package: liborthancclient-doc Source: orthanc Version: 0.7.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 510 Depends: neurodebian-popularity-contest Homepage: https://code.google.com/p/orthanc/ Priority: optional Section: doc Filename: pool/main/o/orthanc/liborthancclient-doc_0.7.2-1~nd70+1_all.deb Size: 86952 SHA256: 3ae389d4aae2cb043286f7dec3e7e7062a7a8869df0c6fd5c0e18ae61b6c071c SHA1: 9e675411af8f126bf8f543e8966cfc8e0a7c2936 MD5sum: c939a250e91f44d048d300aa31a9ebcb Description: Orthanc Client documentation Orthanc Client is a library to access the content of a remote instance of Orthanc. Orthanc is a lightweight, RESTful DICOM server for healthcare and medical research. . This package includes the documentation and the sample codes. Package: liborthancclient0.7 Source: orthanc Version: 0.7.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 297 Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.7), libcurl3 (>= 7.16.2), libgcc1 (>= 1:4.1.1), libjsoncpp0, libpng12-0 (>= 1.2.13-4), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Homepage: https://code.google.com/p/orthanc/ Priority: optional Section: libs Filename: pool/main/o/orthanc/liborthancclient0.7_0.7.2-1~nd70+1_i386.deb Size: 133914 SHA256: 34d817970150e34504de1f2177e761eba0b7dd6dfb37c99e95d4b41a43b913a4 SHA1: cf20c2ce6dbbf9f4befa0d2f0192dbe07ed108a6 MD5sum: 3343aa142bf1b891061cb10da505595e Description: Orthanc Client runtime library Orthanc Client is a library to access the content of a remote instance of Orthanc. Orthanc is a lightweight, RESTful DICOM server for healthcare and medical research. . This package includes the client library. Package: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd70+1_i386.deb Size: 7736 SHA256: 43edd9f78ecd184519e27e823e8ed79372ec88de80c8e30faf2b7f08682bdef3 SHA1: 870b32d375fb1f355eedd9b48cbd6aeda1ad2c10 MD5sum: fb6eabcb8ea493d52a1fe096b0c0d7f3 Description: PAM module to move a user session into a cgroup Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This PAM module will move a user session into an existing cgroup by attempting to match uid and gid against the defined cgroup rules configuration. Package: librtfilter-dev Source: rtfilter Version: 1.1-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-4~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-4~nd70+1_i386.deb Size: 12594 SHA256: 0091bc1405858774f7ed04ca1bf63d9afae550bc9395790cedecdeb78ac7b72f SHA1: 15700373cbb733ebec71e28dd400579cb3ab7908 MD5sum: 328e00e1b0fd0b142f67f3c31abbc400 Description: realtime digital filtering library (development files) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package contains the files needed to compile and link programs which use rtfilter. Package: librtfilter1 Source: rtfilter Version: 1.1-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 52 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-4~nd70+1_i386.deb Size: 28264 SHA256: 4b1e14387b3533fa1fd36882a1fa3ec01483b5923b6d1e47d110c2d608bbc8fa SHA1: c1785da4fb64746b19b7439677826b800afdc936 MD5sum: 4955cf072ce3df42382185c3f22ce567 Description: realtime digital filtering library rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). Package: librtfilter1-dbg Source: rtfilter Version: 1.1-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 34 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-4~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-4~nd70+1_i386.deb Size: 31870 SHA256: 690416197701c661edd03fc695c767dd4a5a88184d932a63442c21d44b94f860 SHA1: 36dbe92a53af4f4e96bc7822c53392b8316c66c6 MD5sum: 0a2e684a32cc512d6d1c805a8234db7e Description: realtime digital filtering library (debugging symbols) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package provides the debugging symbols of the library. Package: libshogun-dev Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13269 Depends: neurodebian-popularity-contest, libshogun11 (= 1.1.0-6~nd70+1) Homepage: http://www.shogun-toolbox.org Priority: optional Section: libdevel Filename: pool/main/s/shogun/libshogun-dev_1.1.0-6~nd70+1_i386.deb Size: 2697136 SHA256: d60463fb3bdd20532eb9d40510fcbff83c0e4250167fc3e675347c388ff27d7e SHA1: 147cbdd5fe749d023c8777114e737ac436d5a7f5 MD5sum: ceb379e733e1ed8262aaf10acf903dbe Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This package includes the developer files required to create stand-a-lone executables. Package: libshogun11 Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5217 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20120614), liblzo2-2, libstdc++6 (>= 4.6), libxml2 (>= 2.7.4), zlib1g (>= 1:1.1.4) Conflicts: libshogunui0, libshogunui1, libshogunui2, libshogunui3, libshogunui4, libshogunui5, libshogunui6 Homepage: http://www.shogun-toolbox.org Priority: optional Section: libs Filename: pool/main/s/shogun/libshogun11_1.1.0-6~nd70+1_i386.deb Size: 1559954 SHA256: cbd98c3cc6e672375456fe96fd10379a1aeb3ac37a12629274d31b3ac3c87f01 SHA1: 006115e334eb9bcb47052c5683400fca431cc69e MD5sum: 4ae2b2998ebc2c818cc33b9c2fe5dcb1 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the core library with the machine learning methods and ui helpers all interfaces are based on. Package: libusb-1.0-0 Source: libusb-1.0 Version: 2:1.0.19-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 110 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libudev0 (>= 146) Multi-Arch: same Homepage: http://www.linux-usb.org/ Priority: optional Section: libs Filename: pool/main/libu/libusb-1.0/libusb-1.0-0_1.0.19-1~nd70+1_i386.deb Size: 54728 SHA256: c508f7cb5398f0984ff6337e9afea0d6cd08be744b76c69d16094b6ef98edbe6 SHA1: 94f8d55faa1a0fa606571ca29c20faf53899b21f MD5sum: 1efffa4f74d89dc0a3f7d115872afec2 Description: userspace USB programming library Library for programming USB applications without the knowledge of Linux kernel internals. . This package contains what you need to run programs that use this library. Package: libusb-1.0-0-dbg Source: libusb-1.0 Version: 2:1.0.19-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 223 Depends: neurodebian-popularity-contest, libusb-1.0-0 (= 2:1.0.19-1~nd70+1) Multi-Arch: same Homepage: http://www.linux-usb.org/ Priority: extra Section: debug Filename: pool/main/libu/libusb-1.0/libusb-1.0-0-dbg_1.0.19-1~nd70+1_i386.deb Size: 106294 SHA256: 4672ba2f87fc9aa5e9e61c5a236bb8dfee5986862a7cbc201e8cf3e22875693a SHA1: d44c1a232faa7219af44a9fa1062ce48be223b92 MD5sum: 0883ed98bea6ab2f3c87546f18984518 Description: userspace USB programming library development files Library for programming USB applications without the knowledge of Linux kernel internals. . This package contains unstripped shared libraries. it is provided primarily to provide a backtrace with names in a debugger, this makes it somewhat easier to interpret core dumps. Package: libusb-1.0-0-dev Source: libusb-1.0 Version: 2:1.0.19-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 201 Depends: neurodebian-popularity-contest, libusb-1.0-0 (= 2:1.0.19-1~nd70+1) Recommends: libusb-1.0-doc Multi-Arch: same Homepage: http://www.linux-usb.org/ Priority: optional Section: libdevel Filename: pool/main/libu/libusb-1.0/libusb-1.0-0-dev_1.0.19-1~nd70+1_i386.deb Size: 75506 SHA256: 9f5d2daad0a99c411d9293c35fe53db76619f12466360835dd643030c822aeed SHA1: 1acf01adadbaae37bac80eed7e151b0d29d418e4 MD5sum: aab7e5dc6be7e37834b3e12f641e6c1b Description: userspace USB programming library development files Library for programming USB applications without the knowledge of Linux kernel internals. . This package contains what you need for compiling sources that use this library in your own code. Package: libusb-1.0-doc Source: libusb-1.0 Version: 2:1.0.19-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1027 Depends: neurodebian-popularity-contest Conflicts: libusb-1.0-0-dev (<< 1.0.16) Replaces: libusb-1.0-0-dev (<< 1.0.16) Homepage: http://www.linux-usb.org/ Priority: optional Section: doc Filename: pool/main/libu/libusb-1.0/libusb-1.0-doc_1.0.19-1~nd70+1_all.deb Size: 169912 SHA256: 37d978b18cec514b1062bf2e70a5097bc4c5a0b02d8a3817aa25fe4ef8e9e1f1 SHA1: d3138ac53ff6cb795e9323ba861ff61872f32177 MD5sum: e97aee0b7b134da88ca705ca5884f0d0 Description: documentation for userspace USB programming Library for programming USB applications without the knowledge of Linux kernel internals. . This package contains the libusb 1.0 API reference manual in HTML format. Package: libvia-dev Source: via Version: 2.0.4-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 715 Depends: neurodebian-popularity-contest, libvia2 (= 2.0.4-2~nd70+1), x11proto-core-dev Conflicts: via-dev Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_2.0.4-2~nd70+1_i386.deb Size: 189806 SHA256: 56917504d3260063837d25b74fc16b6c01b1a92d83877fd258c68d4485fe7978 SHA1: d63b2a90c4533d53b284e31c4aae2a83ceaa4f1c MD5sum: 43d9a788ebe3e545add5a4506c9f2370 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 2.0.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 903 Depends: neurodebian-popularity-contest Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_2.0.4-2~nd70+1_all.deb Size: 118466 SHA256: c508ad5f2de2d726a6ec321a5dda11ae53d8d1991ad9d407c85cfd9190a25184 SHA1: 20c0141728ccf9539a2a460c758d63970ddd85a2 MD5sum: 7094bbe0e4041f7c7ad8b07781132693 Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia2 Source: via Version: 2.0.4-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 477 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia2_2.0.4-2~nd70+1_i386.deb Size: 155636 SHA256: 0c8833f1a723876f521fe85dbe323bf90ffd4090ed1ca1ecce3dbb4b40bd0c27 SHA1: d21db7fdb806ad20e1edf544353fd74d6d83a334 MD5sum: a3535443735035b0356991e7ef14b767 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: libvistaio-dev Source: libvistaio Version: 1.2.16-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 173 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd70+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libv/libvistaio/libvistaio-dev_1.2.16-1~nd70+1_i386.deb Size: 112328 SHA256: f631bea06a2671046a99a5452533288c2d9e9e8df3dbb2700251d23c58caa9b3 SHA1: 0453c4db7094a3e2bd607690288a04993432024d MD5sum: 60f1e3872839924b053c8e61214ff77e Description: Development files for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is the development package containing the header files, and pkg-config script, and man pages. Package: libvistaio14 Source: libvistaio Version: 1.2.16-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 93 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libv/libvistaio/libvistaio14_1.2.16-1~nd70+1_i386.deb Size: 43380 SHA256: 363c3e1c345138ce2cadbf5f7c7b4b2532e4137628946b76b78313f4ccb82922 SHA1: 7b4a13fb61b578033030976ece3ec934ae336622 MD5sum: 7f6bc47007d7d07edbb6947e383beb27 Description: Library for loading and storing various types of binary data Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. Package: libvistaio14-dbg Source: libvistaio Version: 1.2.16-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd70+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libv/libvistaio/libvistaio14-dbg_1.2.16-1~nd70+1_i386.deb Size: 80142 SHA256: 7f72d7e2780fda3104b6b058f2f0f515f97455b3f5d04fb151fa0914307196c2 SHA1: b56cefe0d94aec5622da445042a8f1d9c2213c9f MD5sum: 255a66294774c1aad4c3845c085f2b78 Description: Debug information for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is package containing the debug information. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 702 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd70+1), libvrpnserver0 (= 07.30+dfsg-1~nd70+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd70+1_i386.deb Size: 218318 SHA256: bad2b52596dab124b81aeecfda196792a53db5eaccdc6923e4e0812abdc4278a SHA1: 7e10a6e4b056a65cbd4e78c6ba66b9069e08ad84 MD5sum: a03dd59c1dcf7a1b444dc91ba97acb6e 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 560 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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~nd70+1_i386.deb Size: 234300 SHA256: 99984854a957d8ea9b12f78f52a46004f1ba2f88ff8d452a1942eca270bf1f0a SHA1: 21c4848bef48468722c5ad64d4e10cd8416671a9 MD5sum: c586ad152d4f6dd5ff6f5132dc89a5d9 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1281 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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~nd70+1_i386.deb Size: 479352 SHA256: 3ef7edde055153945a0595fbaaece3cd54c0cb1ea9a66c0d104c58e53e4f87b0 SHA1: d8f7a02da2f201d47031b52806cbbd172dda6a06 MD5sum: e7fcf08d42ca6512ea1edef0f162c47e Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-java Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 11334 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libvtk5.8, zlib1g (>= 1:1.1.4) Suggests: libvtk5-dev (= 5.8.0-7+b0~nd70+1), vtk-examples, vtk-doc, java-virtual-machine Homepage: http://www.vtk.org/ Priority: optional Section: java Filename: pool/main/v/vtk/libvtk-java_5.8.0-7+b0~nd70+1_i386.deb Size: 5114824 SHA256: 3cff83fc76452905b2145f2d567169ca2ad9826c48a465d6475fb7ddb0697c55 SHA1: 41471ccea4cc893d326f7e2e847dc324e7c6e5f1 MD5sum: 6e9783ed43bf4f59379875ad28acbe93 Description: Visualization Toolkit - A high level 3D visualization library - java The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK Java language support. Package: libvtk5-dev Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12834 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd70+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev, libx11-dev, libxt-dev, x11proto-core-dev, libc6-dev, libxss-dev, libxft-dev, libexpat-dev, libjpeg-dev, libpng-dev, libtiff-dev, zlib1g-dev, tcl8.5-dev, tk8.5-dev, libavformat-dev, libavutil-dev, libavcodec-dev, libswscale-dev, libgl2ps-dev, libfreetype6-dev, libxml2-dev, libpq-dev, libnetcdf-dev, libmysqlclient-dev, mpi-default-dev, libqt4-dev Suggests: vtk-examples, vtk-doc Conflicts: libvtk-dev, libvtk32-dev, libvtk4-dev Replaces: libvtk-dev, libvtk32-dev, libvtk4-dev Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-dev_5.8.0-7+b0~nd70+1_i386.deb Size: 2557364 SHA256: 81300df0471fd7a17d11b410e1fef6c330879bcefff5f863e31acecdc5bcf49c SHA1: 468a20cdeb68191cf823aaf78a26948b465c4076 MD5sum: 198407ed22d818f753f563356db16fbb Description: VTK header files for building C++ code The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK to do 3D visualisation. Package: libvtk5-qt4-dev Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 537 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libvtk5.8-qt4 (= 5.8.0-7+b0~nd70+1), libvtk5-dev (= 5.8.0-7+b0~nd70+1) Conflicts: libvtk5-qt3-dev Breaks: libvtk5-qt4 (<< 5.4.2-8) Replaces: libvtk5-qt4 (<< 5.4.2-8) Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-qt4-dev_5.8.0-7+b0~nd70+1_i386.deb Size: 108490 SHA256: 36f68fb320dfab9cd977d16f4b9aac5dac5310e8b69a05e02b434d53405d497e SHA1: f36fe016d9e114b6dbe4e51c7af9a44cf492ed18 MD5sum: c7e1ac6d56bc1a939a62495f7141b008 Description: Visualization Toolkit - A high level 3D visualization library - Qt devel The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK GUI support for Qt4. Package: libvtk5.8 Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 45213 Depends: neurodebian-popularity-contest, libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libgl2ps0, libjpeg8 (>= 8c), libmysqlclient16 (>= 5.1.50-1), libnetcdfc++5, libnetcdfc6, libopenmpi1.3, libpng12-0 (>= 1.2.13-4), libpq5, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libtiff4 (>= 3.9.5-2), libx11-6, libxml2 (>= 2.7.4), libxt6, zlib1g (>= 1:1.2.3.3) Suggests: openmpi-bin | lam-runtime, libvtk5-dev, vtk-examples, vtk-doc Conflicts: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5, python-vtk (<< 4.4) Replaces: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8_5.8.0-7+b0~nd70+1_i386.deb Size: 15082554 SHA256: 9c829ad7f9f50216c1a7411b815e8cc661a2cc84e7a1f692e5aed66b7cf3ad5b SHA1: 664b76b9535327b2108087fb2c60c7da3290cc3e MD5sum: a527f99783e410446feaf8549504d602 Description: Visualization Toolkit - A high level 3D visualization library - runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . VTK enables users to concentrate on their work by providing a large number of excellent and feature packed high level functions that do visualization. The library needs OpenGL to render the graphics and for Linux machines Mesa is necessary. The terms/copyright can be read in /usr/share/doc/vtk/README and README.html. VTK-Linux-HOWTO has information about using vtk, getting documentataion or help and instructions on building VTK. . This package provides the shared libraries needed to run C++ programs that use VTK. . To compile C++ code that uses VTK you have to install libvtk5-dev. Package: libvtk5.8-qt4 Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1262 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libqt4-network (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.8 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8-qt4_5.8.0-7+b0~nd70+1_i386.deb Size: 500040 SHA256: 704b23fd6cd57820989ddce5b9cdb3b3453b5fa328eeb03be2fbd7fd4ad8145b SHA1: 2912165e6d1eb451e56e9b2d723e98cf0c37d456 MD5sum: 56b31c3653351aeffec9be754c8953a5 Description: Visualization Toolkit - A high level 3D visualization library - Qt runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK GUI support for Qt4. Package: libvw-dev Source: vowpal-wabbit Version: 7.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1898 Depends: neurodebian-popularity-contest, libvw0 (= 7.3-1~nd70+1) Homepage: http://hunch.net/~vw/ Priority: optional Section: libdevel Filename: pool/main/v/vowpal-wabbit/libvw-dev_7.3-1~nd70+1_i386.deb Size: 535018 SHA256: bf84b75371f0cbb36f04a7a07b20871759f3a568b341336996c98bfd25b9cf38 SHA1: 52408de60b198038e550f104bff64cb030636b76 MD5sum: cb9a40483357b4875957053581c5709f Description: fast and scalable online machine learning algorithm - development files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains development files needed to compile and link programs which use vowpal-wabbit's libraries. Package: libvw0 Source: vowpal-wabbit Version: 7.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 722 Depends: neurodebian-popularity-contest, libboost-program-options1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.2.3.3) Homepage: http://hunch.net/~vw/ Priority: optional Section: libs Filename: pool/main/v/vowpal-wabbit/libvw0_7.3-1~nd70+1_i386.deb Size: 305222 SHA256: 709bf7750bc502200c8498b4cb1e96b9d8f3afa7be01fe4d5ae13ce252ebe99c SHA1: f8ab48302071a034ee78ee7f896a7fd98361b887 MD5sum: b2e2f56d2da73b2f75eedcd0279e185e Description: fast and scalable online machine learning algorithm - dynamic library Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains vowpal-wabbit's dynamic libraries. Package: libxdffileio-dev Source: xdffileio Version: 0.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.3-1~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.3-1~nd70+1_i386.deb Size: 27768 SHA256: 00dfeb55310cf224fd6c1678ef2fa74af694e0f691aba93422fb0d8c20b8b97b SHA1: 25e87725d92be7a09cadf7e4c77b6410355e2bf5 MD5sum: bc00e7a4b45fdac86acea168cff9eaaf Description: Library to read/write EEG data file formats (development files) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package contains the files needed to compile and link programs which use xdffileio. Package: libxdffileio0 Source: xdffileio Version: 0.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 82 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libs Filename: pool/main/x/xdffileio/libxdffileio0_0.3-1~nd70+1_i386.deb Size: 45470 SHA256: be2f239b1e916bd7b92f256fcbe3ad146611186124a1b985a4ba370221fe0177 SHA1: 6f5dfe360e47bce362e1210fb51b98b75fe993b6 MD5sum: a9250c821f7040a2698e085add1a7f53 Description: Library to read/write EEG data file formats xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead of the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. Package: libxdffileio0-dbg Source: xdffileio Version: 0.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 66 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.3-1~nd70+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.3-1~nd70+1_i386.deb Size: 60314 SHA256: 4e7bcedf458d900cf67582b264058bee7bc1506808593c0972798eb7fe6e0a4d SHA1: fb592be35ac62d039ce614d0147f58c4e16a37f6 MD5sum: a9bab68580d0e6c0233d0eeac6fad862 Description: Library to read/write EEG data file formats (debugging symbols) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package provides the debugging symbols of the library. Package: lua-cnrun Source: cnrun Version: 2.1.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2, dpkg (>= 1.15.4) | install-info Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.1.0-1~nd70+1_i386.deb Size: 51202 SHA256: ed3eefc4b4b5372c40e1d303e1bcc07b07fb5e60d409a305bccf78ebb2d29e10 SHA1: f5c64438c779f05c95d4c6d5ac5c73cf8d7cf3be MD5sum: 6c9eb6fff70ac26ee41a9eba65016884 Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: matlab-support-dev Source: matlab-support Version: 0.0.21~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 39 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.21~nd70+1_all.deb Size: 7690 SHA256: f41deabbc97632c06372fd1f235e6e078e382c0a1aa64f8940d72688b0b3f294 SHA1: 734c5a8f3838d53e5dfe96de1736da3680cc9821 MD5sum: 914d38f498cd9dfb1b0f7bafd9889664 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mia-tools Source: mia Version: 2.0.13-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8285 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd70+1), libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-serialization1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-test1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.31.22), 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 (>= 2.1~), libtiff4 (>> 3.9.5-3~), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.34.2) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd70+1_i386.deb Size: 1524492 SHA256: 28915129d9722e67337e8f9928a0a8daea9563385adcd859c7b91085f761dff8 SHA1: 2a16e096b90ba56b77e329187409fcf18d8a8b05 MD5sum: 16b14fbd7d7118caa9d0ef70c6c71f07 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 24991 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd70+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd70+1_i386.deb Size: 22818824 SHA256: 8ccbe851dcefa23ae70f4a8b41feefbb96af322773e4cbec944a1668ddbf5b50 SHA1: 285c1bbd68842178dc7456e7799ae60c6a7ee00c MD5sum: 81d9cecac853899c1ec197172f3991a0 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1140 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~nd70+1_all.deb Size: 79662 SHA256: 6392fa517b571c424994013005f9108c237351f18e2b64547c20e2e76b93fd9e SHA1: cd3ff76293659d5b20799f84e1ef618eef56ebab MD5sum: f19386bf836a60acfcac219f32d04a54 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: mialmpick Version: 0.2.10-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.1), libglib2.0-0 (>= 2.31.18), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd70+1_i386.deb Size: 82040 SHA256: a228791f91a1588f0b71c79e684f5485e3c223403a0a618f297b618b4ea0a595 SHA1: c26c666934e744934f87e125001712f5f86a46f2 MD5sum: 370215543e35a9ed0c71aa49e10a0afc Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 187 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd70+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd70+1_i386.deb Size: 167826 SHA256: 1d30ca59d6bc7446cd306d4f08ddae01ba6049730b35b335839282060aeccc20 SHA1: 63269b2121a89d56c7793406c642b55190b167b7 MD5sum: 71446a242eea9e45a168f333fc2cf687 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Package: mitools Source: odin Version: 1.8.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6745 Depends: neurodebian-popularity-contest, libatlas3gf-base, libblitz0ldbl, libc6 (>= 2.3.6-6~), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti2, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.5-1~nd70+1_i386.deb Size: 2648412 SHA256: 81bfabd5c6fa7160ad6f45d0d096a32196f3272b553ca6ea81a5c782ab2be974 SHA1: 0a37b62cc0d25c1d1f205cfac5c44b5774081288 MD5sum: 36e7734a02871b83c7ca4590dae73d6d Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mriconvert Version: 1:2.0.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 3199 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.7-1~nd70+1_i386.deb Size: 1060600 SHA256: 81414d2e88c4aff3345754e2e5f20fee8f3cee8b84cfefa5e9f2e71fdb6293d4 SHA1: 81be4b1c69ecbdfd57f7bf3fc576b3f5cd62118e MD5sum: 7bf6145e42103398e9b315da55bf39d0 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20140804.1~dfsg.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 14577 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango1.0-0 (>= 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~nd70+1_i386.deb Size: 5633082 SHA256: 312a078753327a67ca33efdd3c84cce0bfff438a97846d33e4dfdfb6dc4b6e5e SHA1: 641287e195377e11396008454e9705e9ea45d4ce MD5sum: 57f487873863cb3bf38aa46d46accc15 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1710 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~nd70+1_all.deb Size: 1665984 SHA256: d6052de157674400136cbdee21c83c526731797620cd0a53be019cf5daa974f6 SHA1: 703892b09c0d6430b6b9b35f450f81d5e2a76df2 MD5sum: 0d67d2e7ff88723243653afa12a4b0a2 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1022 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd70+1_all.deb Size: 740790 SHA256: 6cef9b52694701bdf50300409c40d50a0e0eb52dab809f080c3ebb9cd73de8f9 SHA1: f82ba2d98a2241084fcc9be1d315fe3596ffa5bd MD5sum: 018b8ab025c7f4c5df919b6c6030dd17 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mridefacer Version: 0.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 674 Depends: neurodebian-popularity-contest, num-utils, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.2-1~nd70+1_all.deb Size: 637608 SHA256: c746f865d554b763ebb3f1593422ac9ff1b4f8ba91900860d5074cf588b386a6 SHA1: 838af23a1fdb02b723736498570ede9a4507a742 MD5sum: f5f3424dc237799b1c16b3d10a5371ad Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: mrtrix Version: 0.2.12-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 8860 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.31.22), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.27.1), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.6), libx11-6, libxmu6, libxt6, 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~nd70+1_i386.deb Size: 3048130 SHA256: ecea73277632d1a3a5c299041416b68d8c1478ea98a7fb4b45009f3a5bf8baaa SHA1: 5312b477f6b279653eacaf4ac9c6a55b2a983b25 MD5sum: 9d63cfdf56592a17099d99168be11ce8 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3528 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~nd70+1_all.deb Size: 3323460 SHA256: d0ee577119384d1b54f950a6af309d70376785856583cbe54399de4098f8edb5 SHA1: 7b977b2a960b56ff708e1000453e1e1cd47c3188 MD5sum: 18943d52a05ce45055f7cbff15b8eb46 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: mwrap Version: 0.33-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 274 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Recommends: octave Homepage: http://www.cims.nyu.edu/~dbindel/mwrap/ Priority: extra Section: devel Filename: pool/main/m/mwrap/mwrap_0.33-1~nd70+1_i386.deb Size: 218300 SHA256: 84e97d28ee1c712f121d4a89924819c33e9886ac869b4d242bfb27fcfef737ba SHA1: bcf5b838cb9bb28386d4b9d96d2a3ba271885c7d MD5sum: 298901fcaccae4b65b8cc5c42efd3202 Description: Octave/MATLAB mex generator MWrap is an interface generation system in the spirit of SWIG or matwrap. From a set of augmented Octave/MATLAB script files, MWrap will generate a MEX gateway to desired C/C++ function calls and Octave/MATLAB function files to access that gateway. The details of converting to and from Octave/MATLAB's data structures, and of allocating and freeing temporary storage, are hidden from the user. Package: ncdu Version: 1.11-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 113 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libncursesw5 (>= 5.6+20070908), libtinfo5 Homepage: http://dev.yorhel.nl/ncdu/ Priority: optional Section: admin Filename: pool/main/n/ncdu/ncdu_1.11-1~nd70+1_i386.deb Size: 44470 SHA256: abcd137805d7d6f9179957ecbb5a400277dac1f75a5118d33ba2b5b2be3d77b0 SHA1: 15693565f9737b519549c58646d44f942a7e8d28 MD5sum: 3c35666e2942123feec8a36b97780011 Description: ncurses disk usage viewer Ncdu is a ncurses-based du viewer. It provides a fast and easy-to-use interface through famous du utility. It allows one to browse through the directories and show percentages of disk usage with ncurses library. Package: netselect Version: 0.3.ds1-25~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: neurodebian-popularity-contest, libc6 (>= 2.1), 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~nd70+1_i386.deb Size: 32210 SHA256: 3b2a4978133b5d274d51faa1d301b08e3b26fcc819792fab39dcca1ad8cff4c5 SHA1: af78016181ad01fba829a4e3989489ed19804691 MD5sum: c34fa592129a67d4cf2ab34b75c0d046 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~nd70+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~nd70+1_all.deb Size: 17856 SHA256: db383e91d00a8162f9d9263e141800c4a58a0b2223826869c1cba57a79b5588e SHA1: 4d96b2698446fb7e07aaf5752bad5a7b28521f11 MD5sum: bd2f9ed8074a39ec7b8f92f15b47d48d Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.5~nd70+1_all.deb Size: 36080 SHA256: 6ddb53757367505f47e4e59fdc74ca11c888b437996e45f7cf5f66b6294df5f1 SHA1: 63a79119ddd2e252d62c4c410e7483854e6798b7 MD5sum: d6ce94f591da3f8b19b65a2a9e6ea416 Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: gnupg2 | gnupg, dirmngr Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.5~nd70+1_all.deb Size: 10728 SHA256: dbe981dace4d16ae881ed81e153c53802a81a7a22d15b7d1426610e6a37f53a1 SHA1: cbfe39ebf9352af6a6b026ab0db26f40fcddc555 MD5sum: 103dbf98838107eb2d7bbdb03041b9da Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 223 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.5~nd70+1_all.deb Size: 119240 SHA256: e884c9f50a62d6b24c68a4ac73df689114b703c75cf0cb5d7e613d4dfee2b04b SHA1: dcfe2a6ac8841340b8ba9c2894008e096757a77a MD5sum: d0f65802e899db0925e35013c56a9539 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.5~nd70+1_all.deb Size: 36298 SHA256: ed741d35ccc2b41123dfa6650cf15fbac80c26930decf234eca2b9b1397eb704 SHA1: 4d0d8acdb8e4ca16e16342093e82c5c173248611 MD5sum: 42e9a7c410b0cb89dfd36ea478377504 Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 195 Depends: virtualbox-guest-utils, virtualbox-guest-x11, virtualbox-guest-dkms, sudo, neurodebian-desktop, lightdm | x-display-manager, zenity Recommends: chromium, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.37.5~nd70+1_all.deb Size: 18550 SHA256: f01c14980fc575dc8883476c85bdf1263ae83d9f0974e300d4bebb57d687275a SHA1: 58cc93a660b45588102d3c1463ecd000d3c9e858 MD5sum: 8779e09ab77ea9652ce09d1e7fe1b019 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~nd70+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~nd70+1_all.deb Size: 7622 SHA256: 348ac2ebb354d9666b66e0bc5c796dbe18b77bce6af28cd3af7c96da52d1c114 SHA1: 4474f374987937f645a2d731986bb78f82c3644f MD5sum: b4c1e764964bf07f648c6a78e4d6a7ca 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: 0.37.5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 50 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.5~nd70+1_all.deb Size: 12742 SHA256: 042908d746c3cad8174577efbd264462820d57ec3c0233ade4effde2f144a49d SHA1: 845868c3a6147eaea44babaaef842a763016feb4 MD5sum: e161f1e425e4acc5602c7085803fd545 Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nifti-bin Source: nifticlib Version: 2.0.0-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 174 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~nd70+1_i386.deb Size: 62528 SHA256: 28d0274dd937a681d22d1631fbfe3d5852d7128ac3b7e6fedcea8701b6a7cd52 SHA1: c26726a7c507826b6df4da9fd77238e93e87cdfc MD5sum: 4ea87d1eff0e8f68be57bff14c5c57d2 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: 0.4.11-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2132 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit3.20, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.11-1~nd70+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.11-1~nd70+1_i386.deb Size: 485992 SHA256: eefc0a173865a997139735be71ab9a2c955ea90738ea24d71118759e72ddbf06 SHA1: be95b1100e1161f9e2cef86153feeb0695390247 MD5sum: d58d005865423befc0636ba244a93873 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: 0.4.11-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 732 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.11-1~nd70+1_all.deb Size: 616680 SHA256: f8ab8a599351d982abcaf1b319703973ac88042a8c0ed159be28556c38b4d97c SHA1: 1ed539ce98f925d2a658719d992a8852f194786e MD5sum: fb709121f380ea0a79f6c0a5dd6691d3 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: nifti2dicom-dbg Source: nifti2dicom Version: 0.4.11-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21931 Depends: neurodebian-popularity-contest, nifti2dicom (= 0.4.11-1~nd70+1) | qnifti2dicom (= 0.4.11-1~nd70+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: extra Section: debug Filename: pool/main/n/nifti2dicom/nifti2dicom-dbg_0.4.11-1~nd70+1_i386.deb Size: 6969944 SHA256: 214f5261d90a4faae00faee36459903ca5928f976986fbc1af0aa31a97ca256b SHA1: d1703c6c6edf4ef72d2565ae6d05e99886765ce1 MD5sum: 7887c755d7bca3e91188d6f100d98a20 Description: convert 3D medical images to DICOM 2D series (debug symbols) 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 debugging symbols necessary to debug crashes in nifti2dicom. Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: nuitka Version: 0.5.27+ds-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3583 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-appdirs | base-files (<< 7.2), python3-appdirs | base-files (<< 7.2), python-dev (>= 2.6.6-2), python (>= 2.6.6-7~) Recommends: python-lxml (>= 2.3), python-pyqt5, strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.27+ds-1~nd70+1_all.deb Size: 849768 SHA256: 1e5502fb16eb829640c6942351793c8909b48eaa24b659610154db2fb16adbae SHA1: b2073e05424bb92afca3d596c606601d3531f71d MD5sum: 76292d57fd61952dbd43d90fc4bfe604 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: numdiff Version: 5.9.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 935 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.9.0-1~nd70+1_i386.deb Size: 633474 SHA256: 9df3ae967f5ca507b7073ac25819f0be3b1be36c253384708d25f8ad6b55f633 SHA1: e2ce2b4bd97a03df87757d2f5aa92d575bc2528c MD5sum: 0863ec78bd0f442d44834bd8815092c5 Description: Compare similar files with numeric fields Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), liboctave1, libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd70+1_i386.deb Size: 24046 SHA256: 66bdfe7f79c9edb6fb3d39ccf66424ba97eb4ff2b45f1b2ea77241e2ffc45de9 SHA1: 936e12a4676ab34a5aec63d8fbe14838338df16c MD5sum: 5eb007b94fbcc801bb9614d43a042f78 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-gdf Source: libgdf Version: 0.1.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 287 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, liboctave1, libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.2-2~nd70+1_i386.deb Size: 121594 SHA256: b34ec80e9dc94b7fe0b9655fdd5cd4201f1f5b0a9d4083634001ed1d7e92a6cb SHA1: 8cb47dca9e06723a80985ee04b71620f5c06b0ad MD5sum: 1fe9b1c81062100727476ef465ad700f Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. Package: octave-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd70+1), libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), liboctave1, libstdc++6 (>= 4.1.1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: math Filename: pool/main/n/nlopt/octave-nlopt_2.4.1+dfsg-1~nd70+1_i386.deb Size: 31702 SHA256: 5f4702b185dbb2d59ce500986f6f220ee9f0d50f1c3bc1b653002ba5e6d8e479 SHA1: 2bd872aa40aa5a36bdb1c37ab83c7489532d62b4 MD5sum: 6ea363708cab48e1e01bafe2c3584f5e Description: nonlinear optimization library -- GNU Octave package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the module for the GNU Octave. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.11.20140816.dfsg1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2737 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.1 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.9 (>= 1.9.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), liboctave1, libopenal1, libpciaccess0 (>= 0.8.0+git20071002), libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libxext6, libxfixes3, libxi6 (>= 2:1.2.99.4), libxml2 (>= 2.6.27), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.11.20140816.dfsg1-1~nd70+1), psychtoolbox-3-lib (= 3.0.11.20140816.dfsg1-1~nd70+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~nd70+1_i386.deb Size: 905418 SHA256: 01f3e2cde004c1bb2691c11d8f4e364f9cb2c241d0df2a1fb96099e0a20358c3 SHA1: 743cb927ff21a32b596d3e001d039710eeb8fc50 MD5sum: dbb4403ac477b97362145e1aa1cb5654 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: odin Version: 1.8.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4061 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, mitools (= 1.8.5-1~nd70+1), zlib1g (>= 1:1.1.4), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.5-1~nd70+1_i386.deb Size: 1649310 SHA256: 531260e45bdc6453fa1f14d57634cf5641cbbb932b8f513e4df21c9cbf1a4a3b SHA1: 5c13518235ccaf26d5d379b44ebecda3dce4f442 MD5sum: 5d1a6e7af2d6021bc125ef0e512b74f8 Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 544 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.1.1) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-4~nd70+1_i386.deb Size: 184400 SHA256: 25fc04997cd71a3c7e041f1fc1f77e2afc173d5e7d89a6a1860e04adcf17d55e SHA1: e0ac6dc8ecc0694e0e912f28e859420cea33f313 MD5sum: 4512fa93a8486a08228ea800861ba254 Description: openmeeg library -- command line tools OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides command line interface to openmeeg functionality. Package: opensesame Version: 0.27.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26639 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd70+1_all.deb Size: 25359168 SHA256: d4a3a47eb33a46f3ce6dfab7ff0c68cf8b4a50b524036a193dbcb74d37d66b78 SHA1: 314c22fe8ee10f62bfb07e5d4bcc767e0ca05062 MD5sum: 2cf1184acc7c84d31652bde5ecdc31f4 Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Package: openstack-pkg-tools Version: 52~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, autopkgtest, libxml-xpath-perl, madison-lite, pristine-tar Priority: extra Section: devel Filename: pool/main/o/openstack-pkg-tools/openstack-pkg-tools_52~nd70+1_all.deb Size: 59610 SHA256: fb53163bfa87e2bc6b9c2fdc7817a2bc652b7b18336217e03e8a92037aac6281 SHA1: 681a5b2a2c4970f6241df371d5674a2ecfc2303b MD5sum: 056cb34246f6a95e964257f536f083bc Description: Tools and scripts for building Openstack packages in Debian This package contains some useful shell scripts and helpers for building the Openstack packages in Debian, including: . * shared code for maintainer scripts (.config, .postinst, ...). * init script templates to automatically generate init scripts for sysv-rc, systemd and upstart. * tools to build backports using sbuild and/or Jenkins based on gbp workflow. * utility to maintain git packaging (to be included in a debian/rules). . Even if this package is maintained in order to build OpenStack packages, it is of a general purpose, and it can be used for building any package. Package: openvibe-bin Source: openvibe Version: 0.14.3+dfsg2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1182 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd70+1), openvibe-data (= 0.14.3+dfsg2-1~nd70+1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.18.0), libopenal1, libpango1.0-0 (>= 1.14.0), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Homepage: http://openvibe.inria.fr Priority: extra Section: science Filename: pool/main/o/openvibe/openvibe-bin_0.14.3+dfsg2-1~nd70+1_i386.deb Size: 451510 SHA256: e528dda72ed2e161e6e9bec3ae970f580f418cf4b2de07502d901a64fad20c91 SHA1: 7a9f32d06cc62296036e2902448c891975aad66e MD5sum: b9427052e27ad19baff7ad7874f7537d Description: Software platform for BCI (tools and demos) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains differents executable including acquisition server, tools and demos. Package: openvibe-data Source: openvibe Version: 0.14.3+dfsg2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9328 Depends: neurodebian-popularity-contest Homepage: http://openvibe.inria.fr Priority: extra Section: science Filename: pool/main/o/openvibe/openvibe-data_0.14.3+dfsg2-1~nd70+1_all.deb Size: 2024456 SHA256: 7b72cf2a61f9764f3d6d4b8c632db691ffb517dcdb6d500c521b8a1eec381302 SHA1: 107a4c5c7588594034039a389571a77eb3914d1d MD5sum: b10cbfaf7110dfa2a5582c30cbe29212 Description: Software platform for BCI (Data files) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the data files. Package: openvibe-dev Source: openvibe Version: 0.14.3+dfsg2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 715 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd70+1) Homepage: http://openvibe.inria.fr Priority: extra Section: libdevel Filename: pool/main/o/openvibe/openvibe-dev_0.14.3+dfsg2-1~nd70+1_i386.deb Size: 100670 SHA256: 7bd5e4580de5f4c009dcb41983adad7bc29c8218ce6bf92af909bcd80a296940 SHA1: 81206fea13ee6f25ee8be1eb8588d49bb16423e3 MD5sum: 8aada141b8aa36e29b50340d3febcfe4 Description: Software platform for BCI (development files) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the development files. Package: openvibe-libs Source: openvibe Version: 0.14.3+dfsg2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2084 Depends: neurodebian-popularity-contest, openvibe-data (= 0.14.3+dfsg2-1~nd70+1), libc6 (>= 2.4), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libogre-1.7.4, libstdc++6 (>= 4.6), libx11-6 Homepage: http://openvibe.inria.fr Priority: extra Section: libs Filename: pool/main/o/openvibe/openvibe-libs_0.14.3+dfsg2-1~nd70+1_i386.deb Size: 642118 SHA256: 18260d8a12d0bbb7c02edfae43305fc2a3d87b2d0b9a9618f5f64b2407da7f2d SHA1: d9da2889afa8500acc8aa72164412a6132f526b0 MD5sum: 7eb3018f66b715ecd65c2fbe2722bde2 Description: Software platform for BCI (shared libraries) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the shared libraries. Package: openvibe-plugins Source: openvibe Version: 0.14.3+dfsg2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5367 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd70+1), openvibe-data (= 0.14.3+dfsg2-1~nd70+1), libalut0 (>= 1.0.1), libboost-regex1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.18.0), libitpp7, liblapack3 | liblapack.so.3 | libatlas3-base, libopenal1, libpango1.0-0 (>= 1.14.0), libstdc++6 (>= 4.6), libvorbisfile3 (>= 1.1.2), libvrpnserver0, libx11-6 Homepage: http://openvibe.inria.fr Priority: extra Section: libs Filename: pool/main/o/openvibe/openvibe-plugins_0.14.3+dfsg2-1~nd70+1_i386.deb Size: 1664640 SHA256: 83edf8e9f79f1da4ef9f8f284e60264df78e0598b7e49b1674f304457cc81c99 SHA1: 653d0756c7a07ac463f03bfa6800731e0f0a2534 MD5sum: b34326af5a15862cddfc8738839994f4 Description: Software platform for BCI (plugins) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the plugins. Package: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21148 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph80, libopenthreads14, 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~nd70+1_i386.deb Size: 6984000 SHA256: 5cff34f867d571f044fd7b93999df16b2704e7a6327a548095d182456fe84b45 SHA1: 7640ae01ada17197f45d90663d9854e61cab1dde MD5sum: f315a04a3fa0343ce7763d5b15559e7a 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2160 Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-program-options1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libopenscenegraph80, libopenthreads14, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4 (>= 2.1.0~2011week13), libstdc++6 (>= 4.6), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd70+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd70+1_i386.deb Size: 975256 SHA256: 4003150e7706c817bd9321219a9f23d84d83f841d9ba93f98a2e40c808a5613c SHA1: dca79108643abaaa0f78e72246a620c2addf1672 MD5sum: 93fc6dbc18aae08ef4a8a4cdf927c9c8 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: orthanc Version: 0.7.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1549 Depends: neurodebian-popularity-contest, adduser, dcmtk, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.7), libcurl3 (>= 7.16.2), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libgoogle-glog0, libjsoncpp0, liblua5.1-0, libpng12-0 (>= 1.2.13-4), libsqlite3-0 (>= 3.7.3), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libuuid1 (>= 2.16), zlib1g (>= 1:1.2.0) Homepage: https://code.google.com/p/orthanc/ Priority: optional Section: science Filename: pool/main/o/orthanc/orthanc_0.7.2-1~nd70+1_i386.deb Size: 591938 SHA256: b5b161b6188e5cc02ce43d2a2a35d9d09f76d83f9b626d6409c40abaa9316bb2 SHA1: 5703f2c9ae615bce309987f8b62dc42d3a98dbda MD5sum: 360749f16162ede01b53f00a34fe40c3 Description: RESTful DICOM server for healthcare and medical research Orthanc aims at providing a simple, yet powerful standalone DICOM server. Orthanc can turn any computer running Windows or Linux into a DICOM store (in other words, a mini-PACS system). Its architecture is lightweight, meaning that no complex database administration is required, nor the installation of third-party dependencies. . What makes Orthanc unique is the fact that it provides a RESTful API. Thanks to this major feature, it is possible to drive Orthanc from any computer language. The DICOM tags of the stored medical images can be downloaded in the JSON file format. Furthermore, standard PNG images can be generated on-the-fly from the DICOM instances by Orthanc. . Orthanc lets its users focus on the content of the DICOM files, hiding the complexity of the DICOM format and of the DICOM protocol. Package: packaging-tutorial Version: 0.8~nd0 Architecture: all Maintainer: Lucas Nussbaum Installed-Size: 1550 Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.8~nd0_all.deb Size: 1488332 SHA256: 491bc5917f698fee06888998e8a295a6caac2950148bb160b457aff72437eadb SHA1: c5d75d04b01f681ead660ce8d8fe068ab887fba0 MD5sum: 8fbf7c362fd4091a78c50404eb694402 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: patool Version: 1.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 162 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: file Suggests: arj, bzip2 | lbzip2 | pbzip2, cabextract | lcab, ncompress, cpio | bsdcpio, lzop, p7zip-full, rar | unrar | unrar-nonfree, zip | unzip, rpm2cpio, binutils, lha, unace | unace-nonfree, arc | nomarch, unalz, lrzip (>= 0.551), tar (>= 1.26) | star | bsdtar, rzip, zoo, xdms, orange, lzip | plzip | clzip | pdlzip, sharutils, flac, shorten, unadf, archmage, genisoimage, python-argcomplete Homepage: http://wummel.github.io/patool/ Priority: optional Section: utils Filename: pool/main/p/patool/patool_1.7-1~nd70+1_all.deb Size: 33452 SHA256: e60ea509694f98fddc8e07452935a9067ee71d94d8921774791413c7b66a1cb1 SHA1: f0c73d2a9a743eee10a0a59b3d7ba0ea59f7cf49 MD5sum: 675b88890fd3df1241c7cfa4806c7d26 Description: command line archive file manager Various archive formats can be created, extracted, tested, listed, compared, searched and repacked by patool. The archive format is determined with file(1) and as a fallback by the archive file extension. . patool supports 7z (.7z), ACE (.ace), ADF (.adf), ALZIP (.alz), AR (.a), ARC (.arc), ARJ (.arj), BZIP2 (.bz2), CAB (.cab), compress (.Z), CPIO (.cpio), DEB (.deb), DMS (.dms), FLAC (.flac), GZIP (.gz), ISO (.iso), LZH (.lha, .lzh), LZIP (.lz), LZMA (.lzma), LZOP (.lzo), RAR (.rar), RPM (.rpm), RZIP (.rz), SHAR (.shar), SHN (.shn), TAR (.tar), XZ (.xz), ZIP (.zip, .jar) and ZOO (.zoo) formats. . It relies on helper applications to handle those archive formats (for example bzip2 for BZIP2 archives). . The archive formats TAR, ZIP, BZIP2 and GZIP are supported natively and do not require helper applications to be installed. Package: psychopy Version: 1.83.04.dfsg-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15993 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.83.04.dfsg-2~nd70+1_all.deb Size: 9002868 SHA256: 4cc36daf7b7cbbd669c64b041dca430b4ba9057121e48fd32d3289680d12e172 SHA1: 4e781ed28f10225ea6bcef1ced0b2bc4b36926b5 MD5sum: 111c6e96f8649a104166e15b076c4409 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58457 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~nd70+1_all.deb Size: 24807576 SHA256: d039d632bb720f85cb1c582f41903a5c3ef59dcb27ae0f39fee1f8ccd9579695 SHA1: 53e0c9fada0f9d805538f48b063a00758efd191e MD5sum: 84699c4676de2245b6d2f37317db83c8 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2410 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.11.20140816.dfsg1-1~nd70+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.11.20140816.dfsg1-1~nd70+1_i386.deb Size: 849802 SHA256: 678d976fbdd9e5882235741726f9eeb389a9ea16e9486e970192d8d2fdf7af9a SHA1: bee754a4bcae42df745ce4c0858845cf243e4a1d MD5sum: 7cc3d26e17d650e8fb75c2f4d76fd1c4 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 142 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~nd70+1_i386.deb Size: 65406 SHA256: 1867c55f60049b875aa72c17715b0145e547f7ac56d74b79ec91a82e863763c5 SHA1: 4284441a3ca3d65f4e363094d307fdf18386c9ac MD5sum: 9ab923c687b56e1e2e698dadc661d58c Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-argcomplete Version: 1.0.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 181 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (>= 2.7) | python-argparse, python (<< 2.8) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd70+1_all.deb Size: 27640 SHA256: 5d8c82e19c64bfdacc68dad1bbdd740853f103fb3f1875820b13718777d38a24 SHA1: 3f5b339c3f5eed501d16e0ecdd694c761bd082b6 MD5sum: 7e027f8251f010188fed83a8271abf0a Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-biosig Source: biosig4c++ Version: 1.4.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.3.6-6~), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_1.4.1-2~nd70+1_i386.deb Size: 55654 SHA256: e15f635ba5fd20241e4d76a6d9d254c37168ea1fa5740cc205298c02c7c9de65 SHA1: c41332b6cf31a1f93ac8264aa7e2f27045d162b8 MD5sum: 4f76693d172bb3577a56483bcc2ec62e Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-boto3 Version: 1.2.2-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1058 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python-futures, python-jmespath, python-botocore, python (<< 2.8), python-requests, python-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python-boto3_1.2.2-2~nd70+1_all.deb Size: 81248 SHA256: 443e06e41132221da88d4cd6f51aa84fb791559174ada1e063ff7971d785be67 SHA1: 27f212ba8befa6fe03c7d9c64b71908554b12ebc MD5sum: 8580568c679dfd02c26b31247bbd9c19 Description: Python interface to Amazon's Web Services - Python 2.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python-brian Source: brian Version: 1.4.1-1~nd70+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~nd70+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~nd70+1_all.deb Size: 549130 SHA256: 7c9586033503713d95ee640005799fd631ebc23b9857fa54739f713c13945ddc SHA1: 8df0debf188bacd59bf8e48470edc079ea401c5b MD5sum: 4d38a81ea37270a2ac871681b3c124b6 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6798 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~nd70+1_all.deb Size: 2245550 SHA256: bbff81c2bf503166de3140452772e3684fcef15a172b12d230b1199a7333719d SHA1: 141fc07a2f6c5c65177d701a0612d7e1ba06f65d MD5sum: 99633747e0f9db0d78f345974120c115 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 224 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), 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~nd70+1_i386.deb Size: 92804 SHA256: 261e0fa45f855317185177cec1c7eb114c99414b02988e8cd79ca1fa9bff6e3c SHA1: 0b4d361b8d5065c57a4348a20aef5a18e96cd966 MD5sum: 799aa6719d866c2f1902c9fb694fa2fc 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-cfflib Source: cfflib Version: 2.0.5-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 768 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-numpy, python-networkx (>= 1.4), python-nibabel (>= 1.1.0) Recommends: python-nose, python-sphinx, python-tables, python-h5py Provides: python2.6-cfflib, python2.7-cfflib Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd70+1_all.deb Size: 217682 SHA256: 315d0c9976626dc452d7a4f03c9ff782c4caa12e182713db2c33d71233777b37 SHA1: 2f09d150c91742140a16fba4f03eceb4ad364e04 MD5sum: 34ba30e9fe7f1e59a608e67b241ca26c Description: Multi-modal connectome and metadata management and integration The Connectome File Format Library (cfflib) is a Python module for multi-modal neuroimaging connectome data and metadata management and integration. . It enables single subject and multi-subject data integration for a variety of modalities, such as networks, surfaces, volumes, fiber tracks, timeseries, scripts, arbitrary data objects such as homogeneous arrays or CSV/JSON files. It relies on existing Python modules and the standard library for basic data I/O, and adds a layer of metadata annotation as tags or with structured properties to individual data objects. Package: python-citeproc Source: citeproc-py Version: 0.3.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 754 Depends: neurodebian-popularity-contest, python-lxml, python (>= 2.6.6-3), python (<< 2.8) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python-citeproc_0.3.0-1~nd70+1_all.deb Size: 105698 SHA256: 3968ddd09277d712a599913ccfdc14cb8f1b429e9a85ab1cb8f7a2c96cf9d66d SHA1: 826e267ee916367a238d8671fea48d7330279e85 MD5sum: 79ad51fa6f365ead69cbd205537c25d4 Description: Citation Style Language (CSL) processor for Python Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python modules. Package: python-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python-contextlib2_0.4.0-3~nd70+1_all.deb Size: 9430 SHA256: 8d33322efbe1d55462415d6cba0405e95ea2c05b6f39e85d361428bac216a618 SHA1: 563616421704be5d0146af3184690de9601604fa MD5sum: 99b34fe3f6e50deea68190ea9a38db4d Description: Backport and enhancements for the contextlib module - Python 2.7 contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 2.7 module. Package: python-dicom Source: pydicom Version: 0.9.9-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1583 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://pydicom.org/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.9-1~nd70+1_all.deb Size: 434126 SHA256: c51abf6dec4298b7bf24bf20d5c37add7c78ed8f0f57fd7e3f285a4d8a4fd7dd SHA1: 2bf2dc94e841547a572a4df8f235895d84093507 MD5sum: fabba1c9b3061334b0a3cda582034cd4 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: 0.9.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4663 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-dipy-lib (>= 0.9.2-1~nd70+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_0.9.2-1~nd70+1_all.deb Size: 2504204 SHA256: 5b9f78c06ac4aba77da059e734646bb13c1a5dba3a8797fdbce59cdeb8497e7a SHA1: add4f1b0fe4e743080840beb2ac13ceb75472eda MD5sum: 2ae607765dbd0304fc4993189f2465ca 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: 0.9.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12482 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_0.9.2-1~nd70+1_all.deb Size: 11078680 SHA256: 45cb1fd7627c17de59e40ac83436dd320b56693543ddb9439deab84447ca5378 SHA1: df1601cd477f5798aa5d17f50ea8e34f6a1f1a95 MD5sum: 49b0e087422282c5ef0deff099d1780b 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: 0.9.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5028 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.3.6-6~), 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_0.9.2-1~nd70+1_i386.deb Size: 1848518 SHA256: b8a320652f51dcd0e3e7b3963457e514095bfd7169a23b4d7626a72dc209e4e6 SHA1: 50fa893b99779dd43eafd1edb1e7cc17c4ebc5db MD5sum: 1c46f2056db53ab61625ed40910e869d 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-docopt Source: docopt Version: 0.6.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://docopt.org Priority: optional Section: python Filename: pool/main/d/docopt/python-docopt_0.6.1-1~nd70+1_all.deb Size: 29124 SHA256: d8e9f19ba2c635359ce3dfd824ebbd4dbf86ed6f0a3f2a8364f82459cb4dbac5 SHA1: 8249f74a28e8133599b90f4d4d177bc087ac0fa0 MD5sum: 93d577bdbf2c6900f426a8423ad4904c Description: Creates beautiful command-line interfaces docopt helps you: . * define interface for your command-line app, and * automatically generate parser for it. . docopt is based on conventions that are used for decades in help messages and man pages for program interface description. Interface description in docopt is such a help message, but formalized. Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2443 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd70+1_all.deb Size: 841718 SHA256: 84b05bab270dfe59e32432bfe9e62e956575f65f3711092048a51f44fa11e310 SHA1: ed3e5fcd48c3c02c5eb9223076a3b8b67dad8109 MD5sum: 6b9e610629e9e6dc2b78408e1e093beb Description: Python library for cognitive and neuroscientific experiments Expyriment is a light-weight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments. The major goal is to provide a well-structured Python library for a script-based experiment development with a high priority on the readability of the resulting programme code. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones. Package: python-freenect Source: libfreenect Version: 1:0.5.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.3-1~nd70+1) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.3-1~nd70+1_i386.deb Size: 42834 SHA256: c8bc591eb9b789971c4b08c35f1d9961135fe9da24ffb2f43b2545a545c909dc SHA1: f582b91997691fbf1442ee5467607dec91151d96 MD5sum: 257cb025b637c798b23b1962bc572794 Description: library for accessing Kinect device -- Python bindings libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-funcsigs Version: 0.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 118 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python-funcsigs_0.4-2~nd70+1_all.deb Size: 14278 SHA256: e0b266026103ff7d8b181b84b4b7d7a6d7d276696e0ddfb84b30cf1bd8503a67 SHA1: 318e6cc4debed34e261648c3d582635c25aba454 MD5sum: 2fb5a6c83ee6d1892aaac70057589b05 Description: function signatures from PEP362 - Python 2.7 funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 2.7 module. Package: python-funcsigs-doc Source: python-funcsigs Version: 0.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://funcsigs.readthedocs.org Priority: optional Section: doc Filename: pool/main/p/python-funcsigs/python-funcsigs-doc_0.4-2~nd70+1_all.deb Size: 27700 SHA256: c6b369abea90b67d2493972f9be1748ed04601cd7def24b849d6297953770dbf SHA1: f3aec646df0ce7df6bd112b576a8fe01ebf8f7e4 MD5sum: 81c67e45697097fdc05cf6bf938778bf Description: function signatures from PEP362 - doc funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the documentation. Package: python-future Version: 0.15.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2149 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python (>= 2.7) | python-argparse, python-importlib, python (>= 2.6.6-3), python2.7, python (<< 2.8) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python-future_0.15.2-1~nd70+1_all.deb Size: 430246 SHA256: 8cb241f594de609f64ce4dcbd7c6de276f403ea510095763f06a64f141f4eaa4 SHA1: 2db5485755219edae09dd9a069f109cefea6ad52 MD5sum: 4ac3becdefa27ca32c99be67813b8d72 Description: single-source support for Python 3 and 2 - Python 2.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 2.x module. Package: python-future-doc Source: python-future Version: 0.15.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1470 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://python-future.org Priority: optional Section: doc Filename: pool/main/p/python-future/python-future-doc_0.15.2-1~nd70+1_all.deb Size: 386416 SHA256: 9898a2ab790b5ddc84dd41412ea65ebc26ee9805963bf0442bf566b7ccb79603 SHA1: 29f315b38da52dea7e61bfac6032206dcbfba79f MD5sum: 29a61873d5cde71f8c77ef85386985a7 Description: Clean single-source support for Python 3 and 2 - doc Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the documentation. Package: python-git Version: 2.0.5-1~nd0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1677 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 0.6.4), python-ordereddict, python (>= 2.6.6-3), python (<< 2.8) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.0.5-1~nd0~nd70+1_all.deb Size: 397436 SHA256: f3eac97320f6929d67c8a4b2ed1e781ae173c68430e125a488b76f3d364e97c9 SHA1: 4ef4a03f9de6778c0228f37edc846dab0d14cf35 MD5sum: 153fdee008ec8d5891c7f919f154495d Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.6, 2.7 Package: python-git-doc Source: python-git Version: 2.0.5-1~nd0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 925 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.0.5-1~nd0~nd70+1_all.deb Size: 164532 SHA256: eb06ffb4cfb67740eec1caf87a97df2bf3a866bd66ba4b966b841a6460cb9a22 SHA1: bcf795ec9436014737e96d8be917ba8d4ba77f0f MD5sum: 2c31b6a6f4cc236ac343041362c1f10c Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-gitdb Version: 0.6.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.6.6-7~), python (<< 2.8), libc6 (>= 2.3.6-6~) Provides: python2.6-gitdb, python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_0.6.4-1~nd70+1_i386.deb Size: 67738 SHA256: 1e732231748af01f975d0620dc0f9389a9abf4b57308f11e5416ab8f2f38f031 SHA1: 1391f6240c0081b46299e597263a1d2353d18fbc MD5sum: bfa349097ac52d84ee7ef830f832280f Description: pure-Python git object database The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. Package: python-github Source: pygithub Version: 1.26.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 640 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Conflicts: python-pygithub Replaces: python-pygithub Provides: python-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python-github_1.26.0-1~nd70+1_all.deb Size: 66524 SHA256: de55cad7c05376275697219cd697c73f1d284205d5290904ee3aa4d1395bab61 SHA1: f6044b00048d05cd873973c70ccd358803b7615c MD5sum: 245b9d1affe5823b2578b1ab645e75dd Description: Access to full Github API v3 from Python2 This is a Python2 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python-humanize Version: 0.5.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 158 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python-humanize_0.5.1-2~nd70+1_all.deb Size: 15924 SHA256: 0e5d8a165c78481653c5b89606d5aaec0e7b5737fec72c42b69cd41334b72fff SHA1: ac76e3f605f1c0a0f4ce2c9a9b80f6cecf4ffefc MD5sum: 0ee2859b8df7e1ee3cf927ff5087209f Description: Python Humanize library (Python 2) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 2 version of the package. Package: python-isis Source: isis Version: 0.4.7-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10713 Depends: neurodebian-popularity-contest, libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-python1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libisis-core0, liboil0.3 (>= 0.3.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.6) Conflicts: isis-python Replaces: isis-python Homepage: https://github.com/isis-group Priority: extra Section: python Filename: pool/main/i/isis/python-isis_0.4.7-1~nd70+1_i386.deb Size: 2514564 SHA256: 78c53aa5fd1ff2cbf3829ae40378a3556e8ba5ff8b11f491c6a579721ce65c13 SHA1: 6bce29c49ccbe7fdf3715eed6f55d5aa3817cf89 MD5sum: fd2b4724800ae17da1160bda3cc36455 Description: Python bindings for ISIS data I/O framework (development headers) This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: python-jdcal Source: jdcal Version: 1.0-1~nd70+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~nd70+1_all.deb Size: 8348 SHA256: da8ea685906de9fc1ef1b8e03c49e5c9616a69121f094ca951962ee4dccbc8e2 SHA1: 952b8f6c71d382846c596dcfe81e0876290e4288 MD5sum: d1fb40edfb0623f6fb312b1191eec462 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 275 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.8.4-1~nd70+1_all.deb Size: 76760 SHA256: 4e8b7bbbfa5fc5cc2cad078c9e61c2f173e0886eaa917da8411a13e4c9648699 SHA1: 047158f64b9c646a4df039cd4ff3755c1eaea63c MD5sum: f340138ccc2493d2f687f2bece4edcdc 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-lazyarray Source: lazyarray Version: 0.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Homepage: http://bitbucket.org/apdavison/lazyarray/ Priority: optional Section: python Filename: pool/main/l/lazyarray/python-lazyarray_0.1.0-1~nd70+1_all.deb Size: 7334 SHA256: 72dadd7fab4a8d37309793af8b50d73a7ea93f6c223509fe58ad502936fa852d SHA1: 3a45ca7b469e524691c3ed6ec708b24bd59391a8 MD5sum: 80d3117e7a8b1fa74d6551c6f2f306ed Description: Python module providing a NumPy-compatible lazily-evaluated array The 'larray' class is a NumPy-compatible numerical array where operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Consequently, use of an 'larray' can potentially save considerable computation time and memory in cases where arrays are used conditionally, or only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array). Package: python-mdp Source: mdp Version: 3.3+git19-g4ec2f29-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1553 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Recommends: python-scipy, python-libsvm, python-joblib, python-scikits-learn | python-sklearn, python-pp Suggests: python-py, shogun-python-modular Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.3+git19-g4ec2f29-1~nd70+1_all.deb Size: 501106 SHA256: 59b5767f5015a0f7d5982db6e0d6e3c13cd1c6a97ba5a5f800ddbbfefcfdec40 SHA1: 825ec52f638b53ca984e99510fb99756a30d24b1 MD5sum: 1e9db109b66789708b2bb7ee870e7c8b Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-mne Version: 0.10.1+dfsg-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9492 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui Recommends: python-nose, mayavi2 Suggests: python-dap, ipython Provides: python2.6-mne, python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.10.1+dfsg-1~nd70+1_all.deb Size: 4797094 SHA256: 8bf5f37db1c6ceb2be1fe173bb0f78cb7b23f1f5b9eb7a67853c959ba0cb4983 SHA1: 0ba1642327d0db2e1bff5ea85e962a86da3f6092 MD5sum: 98f17c598f7bff80d0482c20d97adb0c 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2872 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libopenmpi1.3, zlib1g (>= 1:1.1.4), python (>= 2.6.6-7~), python (<< 2.8), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.3.1+hg20131106-1~nd70+1_i386.deb Size: 923892 SHA256: 241f20983c6b7411989b4f8c3d83458a7dddf6175c387dd0938474d37bdd33ba SHA1: 96f2a2459dad9e1bfc03356367bcb766bc884f15 MD5sum: 5236d59009d92e1e72cc7e28e1d0ebdd 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6562 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3.1+hg20131106-1~nd70+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~nd70+1_i386.deb Size: 2226698 SHA256: 2a921ce6abccbc3265495e6ced55f818d2a7f926ca2cee827cdd0b1eea75419d SHA1: d82f2c562ba2158d7f7b8b81b915a52f2a51c591 MD5sum: beb49f2631afe6330a8bce84888e90f7 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 256 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~nd70+1_all.deb Size: 73296 SHA256: 23cfd5ae13016514e28312e197117270c06838479f8cb616d7a8618f81b5a500 SHA1: bb8a201cac4ec1a465fa2a76b2d8e06458941208 MD5sum: 8f4b56dde1e544c71a843c43b944e2d4 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 282 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) 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~nd70+1_i386.deb Size: 119232 SHA256: d17464aae91e478fddf174d2c413b047df1664b2047f9dcdc201eac4371ae43e SHA1: 1f2d082d2f55c1c803064b462a4e8f8548dfd94e MD5sum: 3b8c524c4268d1c8aaacca24dbdc2d04 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-mvpa Source: pymvpa Version: 0.4.8-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3547 Depends: neurodebian-popularity-contest, python (>= 2.5), python-numpy, python-support (>= 0.90.0), python2.7, python-mvpa-lib (>= 0.4.8-1~nd70+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.6-mvpa, python2.7-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.8-1~nd70+1_all.deb Size: 2204982 SHA256: d11d2301a31c5906b71d199f1d0c084f8b9cf9ac33bb537e24ab2b469b9099a4 SHA1: b362bf026b65424993dc7e63229b8670b55f487c MD5sum: e1bcf9e0206de77156760bbd52d0452f Description: multivariate pattern analysis with Python 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, GNB, 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. Python-Version: 2.6, 2.7 Package: python-mvpa-doc Source: pymvpa Version: 0.4.8-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 37572 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.8-1~nd70+1_all.deb Size: 8475162 SHA256: 650e2c780f78250bf58fada5c40a799f5b05cc59c640faac1f210075f4dc4102 SHA1: 01df95b2235666e3922f97ccfc582d42fa04e77d MD5sum: 6f013cc65b4edae93e4b62095cf568eb Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.8-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 173 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-mvpa-lib, python2.7-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.8-1~nd70+1_i386.deb Size: 71336 SHA256: f5339913330bd1f9f210a2b3c45425f4f99ab2331e110d7df77a6bcae79d864f SHA1: cc74c2c796228a2df90718eb6262be917391e7a3 MD5sum: fdc698f978bc80c4b5f0a2b56289d8a1 Description: low-level implementations and bindings for PyMVPA 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. Python-Version: 2.6, 2.7 Package: python-mvpa2 Source: pymvpa2 Version: 2.6.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8794 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.6.0-1~nd70+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib, python-duecredit Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.6.0-1~nd70+1_all.deb Size: 5356972 SHA256: 74498897ba9180f03978bdc822104fe92320ca26f30c33713d01ce2774df9b82 SHA1: a9133bdc805a9f635c1305bf1607c0fc5fa6b0da MD5sum: 1fa2979bc98f3c59ba4e6b046860c538 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.6.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31251 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.6.0-1~nd70+1_all.deb Size: 7623596 SHA256: c68f3344acc9a59d0a84ee1a289dd46b55fa1d35322542072fa68a3c33a18646 SHA1: 3648ee409bc74ffdfe7d825abb0b28df2cfd2f34 MD5sum: 9086b9cc015d752452e7a0fae7b634f3 Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.6.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 186 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.6.0-1~nd70+1_i386.deb Size: 56526 SHA256: 2f157aa1ba459e36115dcafdaddbaf22dc7522ec635128297df4ec4035a44692 SHA1: dff98b2413d825786976f6138d0b4af2b0811815 MD5sum: ba57a724e4f55184f92259aba93a6a02 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-neo Source: neo Version: 0.3.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2935 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Suggests: python-nose Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.3.3-1~nd70+1_all.deb Size: 1502424 SHA256: 8a6e0b290d15ba1061c397e29f6d39948afda5bf8d2e0e232f6cef4729b77dd3 SHA1: f82c30ca58b1659395e216ced99521c6f38df351 MD5sum: 5ee645804ad02f06ef1c6693e0353251 Description: Python IO library for electrophysiological data formats NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples. . NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab). . Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement. Package: python-networkx Version: 1.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: http://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.4-2~nd70+1_all.deb Size: 647240 SHA256: d330d947a368e24c1c211bb38680d39b541734610380b2eae4295581dc4cd792 SHA1: b2038a2f713e9b53f792369bacc2b37b26f406e1 MD5sum: 80ada5a82a23d92f2ce8d69d952d4f7f Description: tool to create, manipulate and study complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-networkx-doc Source: python-networkx Version: 1.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15840 Depends: neurodebian-popularity-contest Homepage: http://networkx.lanl.gov/ Priority: optional Section: doc Filename: pool/main/p/python-networkx/python-networkx-doc_1.4-2~nd70+1_all.deb Size: 6234176 SHA256: 8a284c712351861f561505f6f7a85a6d6b86732f9020951066fca67be022c7a9 SHA1: d7da2a947abc8026e87191c4ff5893cdbd013adb MD5sum: d0470a135f7b7ae6fbb4252e2b688f86 Description: tool to create, manipulate and study complex networks - documentation NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains documentation for NetworkX. Package: python-neuroshare Version: 0.8.5-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0) Homepage: http://www.g-node.org/neuroshare-tools Priority: extra Section: python Filename: pool/main/p/python-neuroshare/python-neuroshare_0.8.5-1~nd70+1_i386.deb Size: 19588 SHA256: dbd833d4a008d040daa01f199748530a2b9eba3be68d016164cc1b26be445faa SHA1: e543f9cc38340e55da5d6dff51d0507848164df1 MD5sum: a41f71de9787d82f42e289e751a8afdf Description: Python interface and tools for Neuroshare The Neuroshare API is a standardized interface to access electrophysiology data stored in various different file formats. To do so, it uses format- specific shared libraries. . This package provides a high-level Python interface to the Neuroshare API that focuses on convenience for the user and enables access to all available metadata and data. The data is returned in NumPy arrays, which provides a quick route to further examination and analysis. . In addition, this package contains the ns2hdf converter tool that converts neuroshare-compatible files into the HDF5 (Hierarchical Data Format, ver. 5) file format. Python-Version: 2.6, 2.7 Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd70+1_all.deb Size: 32506 SHA256: e312e91ad5c3a552adf31946ac5d1c8b49511eacb9672d6d3e5fe95c67d2cf47 SHA1: 7c9148867c7d28312897d698b64bae996c8cd021 MD5sum: b003531676715edf0f1e1a459f3d6084 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 2.0.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63504 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python2.6, python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.0.2-1~nd70+1_all.deb Size: 2392368 SHA256: bed1adc272b96e9df97195ed290250c72f5c6d39961f672b3437eed54faee1f2 SHA1: 00c29a5f0dc5a1c1527ea9a8413baa79e08806c6 MD5sum: 3816d76964e43a83425812c7488d4184 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Package: python-nibabel-doc Source: nibabel Version: 2.0.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5561 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_2.0.2-1~nd70+1_all.deb Size: 3086694 SHA256: 88a7aaf890a045fd89354a2ec2a4379f03744757b05c4dd47413ce3ddee2e036 SHA1: 8cb705eec397aada137d17644e1154f39ef10e45 MD5sum: 9ac89c6242e9a9825c4e45ff03df3a10 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-nifti Source: pynifti Version: 0.20100607.1-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1424 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libnifti2, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python2.7, python-numpy, libjs-jquery Provides: python2.6-nifti, python2.7-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-4~nd70+1_i386.deb Size: 376566 SHA256: c7f0a800b13969aa5c9fea44746c75bc1b625782c1f0ed4b038f032a3c7f61a6 SHA1: ad8a836ac5e240cdd905c5da53a93b6b67bb1245 MD5sum: c25a388a86f23b154944c5e2cdc83391 Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.6, 2.7 Package: python-nipy Source: nipy Version: 0.4.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4332 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.6.6-7~), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.1-1~nd70+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.6-nipy, python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.1-1~nd70+1_all.deb Size: 990806 SHA256: 8fe8bce52d0533172b010152a0eac361e1d200088dcd8a348b37a2b5b553a5e8 SHA1: 2abbf0c689861445f76c7008b78d398dd412cc4e MD5sum: 613539fbf21f7d8d2cf99f90fa397c93 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: 2.6, 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10486 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.1-1~nd70+1_all.deb Size: 3864404 SHA256: d78ac716f8eacc481f5755344e2d33d3933baca8d99828885908c5cc61cd5465 SHA1: cf85f22ec9832c716bd8cced25bd0f2c99504abe MD5sum: 910472390fea74e64de8d893e3babcea Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.4.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4857 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.6), python (<< 2.8) Provides: python2.6-nipy-lib, python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.4.2-2~nd70+1_i386.deb Size: 1927912 SHA256: 1e6586504b57288ed15c973c9975592f0fbf18c5f82c2f2c63b4b1d47ed576b5 SHA1: 7e85416db824dae19f4f992e9e332914b8ad902a MD5sum: 2c0dfcb0ac5e1701c020c6206aa22462 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: 2.6, 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.4.2-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5086 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-dbg (>= 2.6), python-dbg (<< 2.8), python-nipy-lib (= 0.4.2-2~nd70+1) Provides: python2.6-nipy-lib-dbg, python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.4.2-2~nd70+1_i386.deb Size: 2092772 SHA256: fc2a8888a1dd2b253c4d6281ae8b34b435e53afa3d1cdaeb9db9bf1d7d6b6817 SHA1: 090c28f9d0e3da8aacb387b314b088123250546d MD5sum: 26717f77164a014c95d797467e0aa75c 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: 2.6, 2.7 Package: python-nipype Source: nipype Version: 0.10.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4884 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants Provides: python2.6-nipype, python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.10.0-1~nd70+1_all.deb Size: 1410670 SHA256: ddde92e42d320ad723d5c51946be6bc45df26288c7aa4263d66db21abb07b431 SHA1: 802f3a5ced7d553b4e0ac3d95d754401a04c6022 MD5sum: 8775c298d91c76cf7bd1cab209d42aa0 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20344 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~nd70+1_all.deb Size: 10548596 SHA256: 2bc2b7c66f45dc1ee73c5d412eecd9d1bceb20f0074b71965e89e74387c1dc48 SHA1: 9a81a39b14874a1a530cda5479642f01fca5caab MD5sum: 51a2db48e05db26d9cb94957e861edcf Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9497 Depends: neurodebian-popularity-contest, python-matplotlib, python (>= 2.6.6-3), python-numpy, python-scipy, python (<< 2.8) Recommends: python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.7-1~nd70+1_all.deb Size: 3929322 SHA256: dfc8999a89221b25dc6edbb27d6f60c97352b74a8a468f92048c5e9df7b935d9 SHA1: 8252b6a9235d637da1bd8bbfa1e8966a88230cdc MD5sum: b70d4ce1eba5886bd06392594ddfd996 Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7674 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.7-1~nd70+1_all.deb Size: 6038004 SHA256: d3e542ab42368aaef200f58c2ad293da0082b822f08952e4419046422be472e7 SHA1: 702d1877a8de8ba9c68f6f86cafbad8a2c0b674c MD5sum: 1eba05bba5641dc30865d259eac85cd2 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-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 486 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd70+1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.6.6-7~), python (<< 2.8) Provides: python2.6-nlopt, python2.7-nlopt Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: python Filename: pool/main/n/nlopt/python-nlopt_2.4.1+dfsg-1~nd70+1_i386.deb Size: 166320 SHA256: f39d0fe418824c63f5836a8167001088e73552d283f64e172de53db91b827272 SHA1: 5f0a8a9d1b6ae7c3759c0830ef2b4d00360ef590 MD5sum: d2e60d56900f4b3993f32c516af68ecb Description: nonlinear optimization library -- Python bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the Python bindings. Package: python-numexpr Source: numexpr Version: 2.6.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 989 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.6.6-3), python (<< 2.8), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.6.1-2~nd70+1_i386.deb Size: 268122 SHA256: f2a9a41e3039fb659974f435940b50e9e5b25919b7f1729567911be907f5d4bd SHA1: ed687e8d873ddc96190df9247a865a18123f5310 MD5sum: ddfe5be4d4fdb5d43d4d5b02838710b5 Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 823 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python-dbg (>= 2.6), python-dbg (<< 2.8), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numexpr (= 2.6.1-2~nd70+1), python-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.6.1-2~nd70+1_i386.deb Size: 234648 SHA256: 434434ce20f214449f00680ef09ac59cfc96416976c8a8197f40aa686a99762b SHA1: a238ac845db8384c7946ccc25c5ba40b04fb7293 MD5sum: f902a4032f7f6be4804daa36f684bf70 Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-numpydoc Source: numpydoc Version: 0.4-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 123 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-sphinx (>= 1.0.1) Suggests: python-matplotlib Homepage: https://github.com/numpy/numpy/tree/master/doc/sphinxext Priority: optional Section: python Filename: pool/main/n/numpydoc/python-numpydoc_0.4-1~nd70+1_all.deb Size: 30716 SHA256: 8648d709597fb78a38f6841b93b85eaae140766681e339038a65d36b540fb613 SHA1: f768d4b4ce1d0584845f1f240f4a0209485645d7 MD5sum: 7b6112f1cb570e854c22fc8c8ddba749 Description: Sphinx extension to support docstrings in Numpy format This package defines several extensions for the Sphinx documentation system, shipped in the numpydoc Python package. In particular, these provide support for the Numpy docstring format in Sphinx. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-4~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 596 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.7-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-4~nd70+1_i386.deb Size: 161580 SHA256: b513fa782f6433090860e42a0fb32134dd7918543a418dcd6519fd547f88ec01 SHA1: 8963619574323765ab2afc7ea54f59216f56c2cc MD5sum: c38a280ffc8e6a5b33626e40ff2ac382 Description: openmeeg library -- Python bindings OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides Python bindings for OpenMEEG library. Python-Version: 2.7 Package: python-openopt Source: openopt Version: 0.38+svn1589-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 954 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib, python-setproctitle Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.6-openopt, python2.7-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.38+svn1589-1~nd70+1_all.deb Size: 245060 SHA256: 19a135e4be8de62b737ca038370ef26c98892482f2291ec50c700b1ca2a5c996 SHA1: 847bd52591836b097723a48e910c63f5abb60272 MD5sum: f4ba9ac3e1c8940039fdb02678385adb Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: 2.6, 2.7 Package: python-openpyxl Source: openpyxl Version: 1.7.0+ds1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 453 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose, python-pil, python-imaging Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.7.0+ds1-1~nd70+1_all.deb Size: 92736 SHA256: 0be52cec70c06585ee53c9f160c3239676bb2ddf5f357afaf46cae9b7e134d88 SHA1: 75554545c097b272398af1be0e2549ba120f7c54 MD5sum: ba95b41b529c58a1e01bb77b74ea534c Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-ordereddict Source: ordereddict Version: 1.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~) Provides: python2.6-ordereddict Homepage: http://pypi.python.org/pypi/ordereddict Priority: optional Section: python Filename: pool/main/o/ordereddict/python-ordereddict_1.1-1~nd70+1_all.deb Size: 3952 SHA256: 3ff583bb0a490def26a417dd91df57e567f0e50fa5c4dcf1fbac845b18971ddd SHA1: 10bfe94590ba8a1dda88cc2c3070d50b79be35b0 MD5sum: e0bbf41a9314c3f50dda3c57f4d2e3c2 Description: big-oh performance that matches regular dictionaries OrderedDict is the recipe has big-oh performance that matches regular dictionaries (amortized O(1) insertion/deletion/lookup and O(n) iteration/repr/copy/equality_testing). OrderedDict that works in Python 2.4-2.6. Package: python-pandas Source: pandas Version: 0.14.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8987 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.6~), python-pandas-lib (>= 0.14.1-1~nd70+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~nd70+1_all.deb Size: 1666494 SHA256: be035dcbcbbd63810eac73063065584081e92bbb7997c4d57d6ce31d299a6670 SHA1: ee7d3ce3127e95983c32db6cc0f2c45e17c6962d MD5sum: 8a9a2a18bcd2221c77b84f57ec2ee562 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4882 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.6.1), 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~nd70+1_i386.deb Size: 1729006 SHA256: 69a78a9b1c7151a3eceb4b663b0e98bde604d177d75fb1ea5bfbd85322189837 SHA1: 2306ff177e6f064c684ed3fb011d3e3936594821 MD5sum: f2787c3deac8c72da9935c4c30a9b8b5 Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 825 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-six, python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.4.1+git34-ga5b54c2-1~nd70+1_all.deb Size: 227248 SHA256: 7a9b78ff32840ad28d089bd80b7e47ed170cabba81088b7120cbf315bcbc05d5 SHA1: 227ea4f8dbc8c89bb26700795d8f394b766f84b5 MD5sum: 0d46757b2f82d8647487ceff1aab18a4 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1308 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.4.1+git34-ga5b54c2-1~nd70+1_all.deb Size: 569414 SHA256: c652840f08911e1cedc3a990bc4f0ac0d116b0f283c8483c8763c63cfdb4b892 SHA1: f6fa92e09e508adb35631f4b159f1b6ed288ca0d MD5sum: e19a986b8deb16abc00d07fd6a1c06fc Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pp Source: parallelpython Version: 1.6.2-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.parallelpython.com/ Priority: optional Section: python Filename: pool/main/p/parallelpython/python-pp_1.6.2-2~nd70+1_all.deb Size: 34272 SHA256: 076297344fdb2aad569d128266cbb592689458ac0e2ec4d78a5e8ca14bf8d5b7 SHA1: 910e6bf6e2bb4575f1e378cb1af24d0f91b2bd44 MD5sum: ed9536ef265e9d7e3cd7356d561e2f60 Description: parallel and distributed programming toolkit for Python Parallel Python module (pp) provides an easy and efficient way to create parallel-enabled applications for SMP computers and clusters. pp module features cross-platform portability and dynamic load balancing. Thus application written with PP will parallelize efficiently even on heterogeneous and multi-platform clusters (including clusters running other application with variable CPU loads). Python-Version: 2.6, 2.7 Package: python-pprocess Source: pprocess Version: 0.5-2~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 775 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8) Provides: python2.6-pprocess, python2.7-pprocess Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-2~nd70+1_all.deb Size: 113950 SHA256: a6ea2f2db79eca231f45112402ad716f51fe95568fc1e0576fd38cdb06fbfc21 SHA1: e5558cab7c4525e5cabe088d052da95ca9491f2c MD5sum: b2423e0694aea240e37128c9920fc518 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Package: python-psutil Version: 2.1.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 567 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python (>= 2.6.6-3), python (<< 2.8) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python-psutil_2.1.1-1~nd70+1_i386.deb Size: 152930 SHA256: c054c39de2824924f6ba68050871d3716a0f98e70157b718270d2253bc2dbad7 SHA1: 529e528107311129633108d0273d8cba9c32c99b MD5sum: 9e85142ff91905315a67e649a23c9d35 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-py Version: 1.4.30-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 282 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.30-1~nd70+1_all.deb Size: 78518 SHA256: d837bce3fffea2c17a9008060fa43875e7d3ec81ae7bf8a74a65826c982070e9 SHA1: 8c8b268aa93282740de764cce5953501173fb932 MD5sum: faad94c179d18166fe86e06e58fb0ccf Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pyentropy Source: pyentropy Version: 0.4.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy (>= 1.3) Recommends: python-scipy Suggests: python-nose Provides: python2.6-pyentropy, python2.7-pyentropy Homepage: http://code.google.com/p/pyentropy Priority: extra Section: python Filename: pool/main/p/pyentropy/python-pyentropy_0.4.1-1~nd70+1_all.deb Size: 21330 SHA256: af5c1ea7542c31abb491d792b1bfaef5d5a74aef7402c4659297bec687394d72 SHA1: d0b06b12f69cf46fc8a2db6c3ec5cdc548da2fe0 MD5sum: fbbf7aeb5538f3b546599d3eb9e9a81b Description: Python module for estimation information theoretic quantities A Python module for estimation of entropy and information theoretic quantities using cutting edge bias correction methods, such as * Panzeri-Treves (PT) * Quadratic Extrapolation (QE) * Nemenman-Shafee-Bialek (NSB) Python-Version: 2.6, 2.7 Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1923 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd70+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>= 1.0.16), libc6 (>= 2.3.6-6~), 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: python2.6-pyepl, 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~nd70+1_i386.deb Size: 565170 SHA256: 4e04a4102a9b5cc6d2ccad3de41f4be15184c2764f5bd87a47df3d48dd5a5c80 SHA1: 09a5f6a963518f8298afd4be0a2830bd242e38e0 MD5sum: 9bd617e5bc38f1c2e55f68fe14680635 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~nd70+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~nd70+1_all.deb Size: 818246 SHA256: e75f811ed7831fb6d98f234c78dc1c7f238d96b8316e66c35703156f8c83aadf SHA1: eaa324f7ed77db6a1388c5e25e6cd5290f75f33d MD5sum: 051b80b1ebeb8634798c114172ef8638 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: 2.2+ds-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2579 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0), libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3 | libatlas3-base, libquadmath0 (>= 4.6), 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_2.2+ds-1~nd70+1_i386.deb Size: 787318 SHA256: e54ecb8c4b737bc6da963c4932f17ef94ebdc72e76db6ed7309c6fa7a2e00bc0 SHA1: 5da2aa5d377f8a78c8802b871f6ff49e3f6ea971 MD5sum: a65d396347277d7ce591ed6d794f3eb4 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: 2.2+ds-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1840 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_2.2+ds-1~nd70+1_all.deb Size: 903858 SHA256: e58138742a6d440f1e36740ba231cfafd2740becf4917a1fc3554258e8a243ac SHA1: 32d42e11b09c7b7959422447a866a01cc90f2610 MD5sum: 0d85f78c49384678bdad75cbfa1d44ea 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 777 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~nd70+1_all.deb Size: 192128 SHA256: 3ed89b456870d6b6530e6662b034a3906298a8b612109135b96518fc3837c8bc SHA1: fa36b5bb19a5cf7b87a4fe9d12d43fccd90b1844 MD5sum: fc397ee0c6e5376bda371cc680f0c56a 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-pyo Version: 0.6.6-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 14607 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), libc6 (>= 2.3.6-6~), liblo7 (>= 0.26~repack), libportaudio2 (>= 19+svn20101113), libportmidi0, libsndfile1 (>= 1.0.20), python (<< 2.8) Recommends: python-tk, python-imaging-tk, python-wxgtk2.8 Homepage: http://code.google.com/p/pyo/ Priority: optional Section: python Filename: pool/main/p/python-pyo/python-pyo_0.6.6-1~nd70+1_i386.deb Size: 6090158 SHA256: 3d8bbbd2b8c71d2208d9c954bd8d8f866ab6059acc66b58213e2424f24f76597 SHA1: 7d1e8dae8d4c058280f64eb053f42a7049b11fe4 MD5sum: 921ab6b0b5558bfaabaeaccbdd161e3a Description: Python module written in C to help digital signal processing script creation pyo is a Python module containing classes for a wide variety of audio signal processing types. With pyo, user will be able to include signal processing chains directly in Python scripts or projects, and to manipulate them in real time through the interpreter. Tools in pyo module offer primitives, like mathematical operations on audio signal, basic signal processing (filters, delays, synthesis generators, etc.), but also complex algorithms to create sound granulation and others creative audio manipulations. . pyo supports OSC protocol (Open Sound Control), to ease communications between softwares, and MIDI protocol, for generating sound events and controlling process parameters. . pyo allows creation of sophisticated signal processing chains with all the benefits of a mature, and wildly used, general programming language. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2304 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.6), 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~nd70+1_i386.deb Size: 676608 SHA256: c5ebf23ac6bacd1ef9e8f8f55f60983a55c68c8cf486900ff34a7715751f71f0 SHA1: 3e0b1f8c24844ffabca8c1c659068101720af1a0 MD5sum: 5466a1c8a89486dc8c86e434a1ec3488 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-pyxid Source: pyxid Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Homepage: https://github.com/cedrus-opensource/pyxid Priority: optional Section: python Filename: pool/main/p/pyxid/python-pyxid_1.0-1~nd+1_all.deb Size: 11020 SHA256: 1031c0d69dd73cb38f3e0b826193211706a94bfd04da4287288418b257e54249 SHA1: 0f0d0524354e5d07eb89efcb11779d9acd9d57e2 MD5sum: 1f2a9bc07952b1f5c6b65fc5c092f75c Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-pyxnat Source: pyxnat Version: 0.9.1+git39-g96bf069-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1722 Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd70+1_all.deb Size: 376574 SHA256: f3143d606791308341d10dd7752b4f8a89d4d962ddc1bfdfb43324c11b19e0fb SHA1: b35f0b369867653fb22853d37c7b2e56825267ae MD5sum: c172162c217fd132f93dfebf701445c5 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-quantities Version: 0.10.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy (>= 1.4) Homepage: http://packages.python.org/quantities/ Priority: extra Section: python Filename: pool/main/p/python-quantities/python-quantities_0.10.1-1~nd70+1_all.deb Size: 62650 SHA256: 7105f0be0bad6a6896943c81ffc4f7ebd4e7ce36829bf3747f8fbb603246e059 SHA1: c36035905534efefa681ab02a9b30a297c46c3fc MD5sum: 370baf01ebbe89b0e73e46b3b3dee9e2 Description: Library for computation of physical quantities with units, based on numpy Quantities is designed to handle arithmetic and conversions of physical quantities, which have a magnitude, dimensionality specified by various units, and possibly an uncertainty. Quantities builds on the popular numpy library and is designed to work with numpy ufuncs, many of which are already supported. Package: python-scikits-learn Source: scikit-learn Version: 0.16.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 51 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_0.16.1-2~nd70+1_all.deb Size: 48292 SHA256: 33b215caa3cdb459a4e715f574b96e90f6c011e9bd9852a5ad5f45fc08ad4b6b SHA1: 8fc410c4f8a2d86552b494ae35e14f17a263b179 MD5sum: e054964ba8035b57c516841bfbfedc58 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-scikits.statsmodels Source: statsmodels Version: 0.5.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, python-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: oldlibs Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.5.0-1~nd70+1_all.deb Size: 5622 SHA256: aced9ca8fc74948bddce3d3e4fa88a02399e8def6e504a27cebbb30ee20c9cbe SHA1: 9727dbe8d94182dacbf491e3523cd0cea4b4c5a0 MD5sum: a0f89341a8a53f73562b6963e703829a Description: transitional compatibility package for statsmodels migration Provides old namespace (scikits.statsmodels) and could be removed if dependent code migrated to use statsmodels for clarity of the namespace. Package: python-seaborn Source: seaborn Version: 0.7.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 809 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 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_0.7.1-2~nd70+1_all.deb Size: 158624 SHA256: 3f58ccea59385b220c72e9252d27990c840d0a73cbfa7661f7b4f0c0f8131b81 SHA1: a2acb55fefae47294327641eb7c0111afb30200f MD5sum: ec617bc0528030dd53eba50b963cc907 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-simplegeneric Source: simplegeneric Version: 0.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Provides: python2.6-simplegeneric, python2.7-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd70+1_all.deb Size: 9810 SHA256: c0bf53d256b2a9520f7c40efd3af9d01c92802949256bdc3ddcbe6f8c809ba45 SHA1: b9a5abab569c8269207372b91c7e89a7230efc84 MD5sum: 46e1c70528d4fd5c5636ec720f54787f Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-six Source: six Version: 1.8.0-1~bpo70+1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.8.0-1~bpo70+1~nd70+1_all.deb Size: 14696 SHA256: 85a096bc08b78353f0e48fdc3e9530dc31f71a44c3e1a0f01f18ccd7b407a355 SHA1: e8f04d36980afc332b0e0f4ae9e3932c98d98e8c MD5sum: 8035179f515d89a0f9160e565cfad726 Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-skimage Source: skimage Version: 0.8.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4550 Depends: neurodebian-popularity-contest, python (>= 2.6), python-numpy, python-support (>= 0.90.0), python2.6, python-scipy (>= 0.10), python-skimage-lib (>= 0.8.2-1~nd70+1), libfreeimage3 Recommends: python-nose, python-matplotlib (>= 1.0), python-imaging, python-qt4 Suggests: python-skimage-doc, python-opencv Provides: python2.6-skimage, python2.7-skimage Homepage: http://scikits-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.8.2-1~nd70+1_all.deb Size: 3236984 SHA256: 4cc4e72a077f813caa0f133b07fcbf853e70be393ecd116c3b3eb2afe80ee388 SHA1: d8b3de267988fdd0cd941950805fed0f9b621ed6 MD5sum: 58c15b49a237e4bf5fbb8840c97cfa86 Description: Python modules for image processing scikits-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. Package: python-skimage-doc Source: skimage Version: 0.8.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14193 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-skimage Homepage: http://scikits-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.8.2-1~nd70+1_all.deb Size: 11823562 SHA256: 741c4e348522a251cacc1904c8b2b39eb40a94247654f3d6621245a8e3a31577 SHA1: 88c1efd39024f137d2641babf0bba0c79419fa4f MD5sum: 442a5fc7b4e0138a641dd1fa9c2be83a Description: Documentation and examples for scikits-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.10.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7411 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) 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_0.10.1-1~nd+1_i386.deb Size: 982388 SHA256: 83280730f9df605f66d977c739ce7aa0d73fd1767f134c8d291aa6fc4ef599f5 SHA1: 2e4534cc9093f56dac786064ae17ce303e20b706 MD5sum: 9e9046ee03889bee0c75b6c331520edf 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: 0.16.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4795 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8), python-numpy, python-scipy, python-sklearn-lib (>= 0.16.1-2~nd70+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: python2.6-sklearn, python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.16.1-2~nd70+1_all.deb Size: 1359418 SHA256: 19c182857444f9fe155d94195ea9c25154300e8dca87ca82c1e3e8808bc3210d SHA1: 2f0a9fcee15dd21a30c4dafde236f235564a1c6d MD5sum: 967c8a7a9dd8ca2e4cb12213c8f78561 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: 0.16.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23446 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_0.16.1-2~nd70+1_all.deb Size: 5746322 SHA256: 9e9a509129fe0df15c8f9b113f8c70c21b454f7e82e102ac83c97bf7e55bf5ba SHA1: 43acb0286ee7b6f0af117942738f6c7739bc954f MD5sum: b48bac5df403e032e2ff72667d2b7ef6 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: 0.16.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8149 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.6.1), python-numpy-abi9, python (<< 2.8), python (>= 2.6) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.6-sklearn-lib, python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.16.1-2~nd70+1_i386.deb Size: 3269738 SHA256: 8b162a01f2f277cdeab23b99fc80826beaee6deda6c81d6c5299a74e0c9f2f3d SHA1: a586adae64f535fd7d592a4ffe8f7b76ffce9c19 MD5sum: d559990352891a0efc864c5a1b1319e2 Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-smmap Version: 0.9.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 71 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8) Suggests: python-nose Provides: python2.6-smmap, python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-1~nd70+1_all.deb Size: 22572 SHA256: 09e7c68b4d8ab6d4201fc9481db5e33523fadda79f05fb7013ba1d27e0597e6a SHA1: 6409d1036c76863bf1b7fdc08670f98bc5e8b854 MD5sum: 9e3699860d6b62221e7fc79b3dc51cf4 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. Package: python-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 151 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8), python-rdflib Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python-sparqlwrapper_1.7.6-3~nd70+1_all.deb Size: 27416 SHA256: 3d2ed84fc93b91d2353c11d682de8daec641d5500116806657559cf6fe118a0e SHA1: a4e28a38b876a54947ccd31ad100c2dd53aeddb9 MD5sum: ac2fe4de8135dd7ec320d8235a73b65b Description: SPARQL endpoint interface to Python This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 2 version of the package. Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4188 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-docutils (>= 0.5), python-pygments (>= 0.8), python-jinja2 (>= 2.2), libjs-jquery Recommends: python (>= 2.6) | python-simplejson, python-imaging Suggests: jsmath Homepage: http://sphinx.pocoo.org/ Priority: optional Section: python Filename: pool/main/s/sphinx/python-sphinx_1.0.7-2~nd70+1_all.deb Size: 1260232 SHA256: 648244da9a934daaee709edb7cd2d109551e93e215ebd43730a5a0bff017a035 SHA1: a878bb9a26d7085fd2ec3e02fa606ae3a44a9528 MD5sum: 9be86574fc484fd49d5be81bd6deba03 Description: tool for producing documentation for Python projects Sphinx is a tool for producing documentation for Python projects, using reStructuredText as markup language. . Sphinx features: * HTML, CHM, LaTeX output, * Cross-referencing source code, * Automatic indices, * Code highlighting, using Pygments, * Extensibility. Existing extensions: - automatic testing of code snippets, - including doctrings from Python modules. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 874 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python (>= 2.7), python (<< 2.8) Recommends: python-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python-sphinx-rtd-theme_0.1.8-1~nd70+1_all.deb Size: 420206 SHA256: 6cfce4ae32123360637185ec78c09578788ed2e0885bf1c6aef95f34491c83e9 SHA1: b86cb05537331ca6d2035b523b1d2ec0e63323fe MD5sum: 3772e10a1393efc6d2ee8915581717f2 Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-spyderlib Source: spyder Version: 2.2.5+dfsg-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4106 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), python (<< 2.8), libjs-sphinxdoc (>= 1.0), libjs-jquery, libjs-mathjax, python-qt4 Recommends: ipython-qtconsole, pep8, pyflakes (>= 0.5.0), pylint, python-matplotlib, python-numpy, python-psutil (>= 0.3.0), python-rope, python-scipy, python-sphinx Suggests: tortoisehg, gitk Breaks: spyder (<< 2.0.12-1) Replaces: spyder (<< 2.0.12-1) Provides: python2.6-spyderlib, python2.7-spyderlib Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: python Filename: pool/main/s/spyder/python-spyderlib_2.2.5+dfsg-1~nd70+1_all.deb Size: 1877078 SHA256: c68eb60a149c6a838ec9fc509eeb4b98657dd2df46997afb9a9594a001163929 SHA1: f55ea33d3c104c0fcaf457d2699cfeabfada76f4 MD5sum: fe747979f715bb209d47b4f5681c5571 Description: python IDE for scientists Originally written to design Spyder (the Scientific PYthon Development EnviRonment), the spyderlib Python library provides ready-to-use pure-Python widgets: source code editor with syntax highlighting and code introspection/analysis features, NumPy array editor, dictionary editor, Python console, etc. It's based on the Qt Python binding module PyQt4 (and is compatible with PySide since v2.2). Package: python-spykeutils Source: spykeutils Version: 0.4.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2117 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-scipy, python-quantities, python-neo (>= 0.2.1), python-nose, python-sphinx Recommends: python-guidata, python-guiqwt, python-tables, libjs-jquery, libjs-underscore, python-sklearn (>= 0.11), python-joblib (>= 0.4.5) Provides: python2.7-spykeutils Homepage: https://github.com/rproepp/spykeutils Priority: extra Section: python Filename: pool/main/s/spykeutils/python-spykeutils_0.4.3-1~nd70+1_all.deb Size: 407372 SHA256: a33ea754249038ef08a3ce9d4c4399b018b539cdaa611b0d7a220e7a05993291 SHA1: b5cd70c9ca78969ca71b650c4b6f4c18fe3a7ecd MD5sum: a0694656192237d901d05290048b4438 Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.5.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20309 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd70+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.5.0-1~nd70+1_all.deb Size: 4669242 SHA256: 5e8a0bf317654408b38a6f568052ea60bbef40a69e1ed5f155a779e0cfe81e90 SHA1: a7d322d6197262cefc2a28ea26092b1ff6be048e MD5sum: e90c2216b3d0959c1a028e71084c8683 Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.5.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29891 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.5.0-1~nd70+1_all.deb Size: 7076508 SHA256: d1f7a1276f9462a71a4f641b6f61351787acac117b1c60f618d0b4a446d70915 SHA1: 922be3a869fbbf826d6da7b61277f0afc4dd4108 MD5sum: 74f6a3c21cd7be2438a1eb31c5d4f255 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-statsmodels-lib Source: statsmodels Version: 0.5.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.3.6-6~) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.5.0-1~nd70+1_i386.deb Size: 82060 SHA256: 6dbb4492a6a0a0286696e4b3c9053a8f4f557aa7a8518278c34ff70f587f1322 SHA1: 0c6b0da4686b47c82a4dc4a71a006b42a7822a34 MD5sum: 09a246e402aa1579a0401f96c5cbe439 Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.15.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1493 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3 | libatlas3-base, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.1.4), libsuitesparse-dev, zlib1g-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.15.4-1~nd70+1_i386.deb Size: 625652 SHA256: 4586be94671543912c489d5789f45ebc91f3cb645db2d2230d5e2dc087272b15 SHA1: 7c2e7a04902f4aece41f049753b9330e54b05f7c MD5sum: e0415f2e6e56f93827fcd4a9c960ee67 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: 0.3+git15-gae6cbb1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 95 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd70+1_all.deb Size: 28900 SHA256: 4df80f80d2fed01ef90c5a916faa87e6b6a6a8b5a3c2e659f25c1ea01ced3924 SHA1: 835637f3ec260432045cda17ac0eec30b2cc0cca MD5sum: 1b138ca525cf57a2410e515ea217bbe7 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: 2.6, 2.7 Package: python-tornado Version: 2.1.0-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, python2.6 | python2.7, python (>= 2.6.6-7~), python (<< 2.8), python-pycurl, ca-certificates Recommends: python-mysqldb Homepage: http://www.tornadoweb.org/ Priority: optional Section: python Filename: pool/main/p/python-tornado/python-tornado_2.1.0-1~nd70+1_i386.deb Size: 223258 SHA256: 05a2da61d06c5539b61fff62e2355a39d407963418a33727578acc8058d005c1 SHA1: db9ba05e2fda6dd2cd50a5ae17cd48c025d32b82 MD5sum: 9db167fb4a1d563aa24741863f66d64a Description: scalable, non-blocking web server and tools Tornado is an open source version of the scalable, non-blocking web server and tools that power FriendFeed. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the underlying non-blocking infrastructure. Package: python-tqdm Source: tqdm Version: 4.4.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: neurodebian-popularity-contest, python (>= 2.6.6-3), python (<< 2.8) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.4.1-1~nd70+1_all.deb Size: 40528 SHA256: 97f05516c5a22ff566271f8f14988f60fa85ff22da691d6c9465ed997b5e8d84 SHA1: 544e5e3ca03301b32593da837a0ab1891e028240 MD5sum: 3b893f13a4381d0c93c84aaf9c4df40c Description: fast, extensible progress bar for Python 2 tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 2 version of tqdm . Package: python-tz Version: 2012c-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, tzdata, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://pypi.python.org/pypi/pytz/ Priority: optional Section: python Filename: pool/main/p/python-tz/python-tz_2012c-1~nd70+1_all.deb Size: 39000 SHA256: 4d99b0c0de79ceca4b307484afb320bed4f244d51252ae87a29f931d16f93959 SHA1: 67aa4d3871f125fa3f04b2f0fddee56d9bcdb8db MD5sum: 7766a106c9f3ea0f29222f96da871952 Description: Python version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). Package: python-visionegg Source: visionegg Version: 1.2.1-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1787 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgl1-mesa-glx, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://www.visionegg.org Priority: optional Section: python Filename: pool/main/v/visionegg/python-visionegg_1.2.1-1~nd70+1_i386.deb Size: 687712 SHA256: 3e3b130d45a729baec74750aa638e3aa317c79141058faa66b86fda0b18354b9 SHA1: cf45b8cc3f2a28fd8fe2acecdb047afcc83b9c23 MD5sum: d58840cd1d28b1042889e51b336edf0d Description: Python library for 2D/3D visual stimulus generation The Vision Egg is a programming library that uses standard, inexpensive computer graphics cards to produce visual stimuli for vision research experiments. Package: python-vtk Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 28222 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libopenmpi1.3, libpq5, libpython2.7 (>= 2.7), libstdc++6 (>= 4.2.1), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libvtk5.8, libx11-6, tcl-vtk, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc, mayavi2 Homepage: http://www.vtk.org/ Priority: optional Section: python Filename: pool/main/v/vtk/python-vtk_5.8.0-7+b0~nd70+1_i386.deb Size: 6785548 SHA256: 1ba181f0fcbdd9f4770dc969ba35cf925277022b22c04aa83a26e57ecc64b715 SHA1: fecd82192e44c2d68061a99aeb8c524165c99b7e MD5sum: e505844b62d4d167adab024912249116 Description: Python bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries that enable one to use VTK from Python scripts. You will need Python and vtk installed to use this. Some useful information may be available in /usr/share/doc/python-vtk/. Python-Version: 2.7 Package: python-w3lib Version: 1.11.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: neurodebian-popularity-contest, python (>= 2.7), python-six (>= 1.6.1), python (<< 2.8) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python-w3lib_1.11.0-1~nd70+1_all.deb Size: 15404 SHA256: c4bc028f0a6d04b9a46d3e339d22c90f407aac1807f2ec6faa1c8a03e5eb637a SHA1: 1067a91aa1180df1f27249431007dc594635d2b6 MD5sum: 12f69a3f5347d40b9872571e5cd5e653 Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-workqueue Source: cctools Version: 3.4.2-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: python Filename: pool/main/c/cctools/python-workqueue_3.4.2-1~nd70+1_i386.deb Size: 137504 SHA256: e04c3b75609a700aed12e82c8a5aa3f595b86e84a0aaaaecc91e272019b93103 SHA1: b5d98774de8efce2c14caa63e810ad3ba1c13831 MD5sum: d46b70a88e0acf0f53a57a362d76e743 Description: cooperative computing tools work queue Python bindings CCTools's Work Queue is a system and API for building master-worker style programs that scale up to thousands of processors. This package provides bindings to access this system from Python. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 123 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd70+1_all.deb Size: 22890 SHA256: cb68f19e7958a84aedcab829048f2a9b20247fc1754dda942d2aa96d3f5679ff SHA1: 665a559292d9c58fb924b387b1fa2797faf8c3e4 MD5sum: 21a8445a97a1dffc9b219dafb6733fc8 Description: bash tab completion for argparse (for Python 3) Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 3.x. Package: python3-boto3 Source: python-boto3 Version: 1.2.2-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 805 Depends: neurodebian-popularity-contest, python3-jmespath, python3-botocore, python3 (>= 3.2.3-3~), python3-requests, python3-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python3-boto3_1.2.2-2~nd70+1_all.deb Size: 78628 SHA256: d3a36fe7a9167e01a9f47bb6c8760fb91daa23ba97a430218cf65c345d507b4e SHA1: 9a01e2e3dbc54ed92c13bd696ffba8f52ce9243a MD5sum: 9b299c3f90c8221649281c39582e817d Description: Python interface to Amazon's Web Services - Python 3.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python3-citeproc Source: citeproc-py Version: 0.3.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 731 Depends: neurodebian-popularity-contest, python3-lxml, python3 (>= 3.2.3-3~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd70+1_all.deb Size: 100194 SHA256: a11abe60616dca3775afe584697028e71b2ffe7f4174838e5f6ad58b36ecf934 SHA1: 7551cbfd4a28ddc18470e0c9ff2eba2befd53a2d MD5sum: d44443de45859c09cddee8bfcdb2d2ec Description: Citation Style Language (CSL) processor for Python3 Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python 3 modules and the CLI tool csl_unsorted. Package: python3-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python3-contextlib2_0.4.0-3~nd70+1_all.deb Size: 9206 SHA256: 8aa17d9297a6c42407ada617fc543f80d0ec8fdb3fbc0e2bf412b57e94df7249 SHA1: 6c5662a08f1e20e4eb6c3c195b7c1ffe3f24f2ad MD5sum: 1ae96a8bd925a164ec1038d36809d2a7 Description: Backport and enhancements for the contextlib module - Python 3.x contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 3.x module. Package: python3-datalad Source: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4665 Depends: neurodebian-popularity-contest, git-annex (>= 8.20200309~) | git-annex-standalone (>= 8.20200309~), patool, p7zip-full, python3 (>= 3.7), python3-annexremote, python3-distro, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners (>= 0.14~), python3-gitlab, python3-humanize, python3-importlib-metadata | python3 (>> 3.10), python3-iso8601, python3-keyring, python3-keyrings.alt | python3-keyring (<= 8), python3-mock, python3-msgpack, python3-pil, python3-platformdirs, python3-requests (>= 1.2), python3-secretstorage, python3-simplejson, python3-six, python3-tqdm, python3-chardet, python3-packaging, python3:any Recommends: python3-boto, python3-exif, python3-html5lib, python3-httpretty, python3-jsmin, python3-libxmp, python3-lzma, python3-mutagen, python3-pytest, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, datalad-container, datalad-crawler, datalad-neuroimaging, python3-bs4, python3-numpy Breaks: datalad-container (<< 1.1.2) Homepage: https://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.17.5-1~nd+1_all.deb Size: 958872 SHA256: 1f3e16c16863bab40ba92405109ab26c78f19e3e86e2b38733a035221c4e7744 SHA1: 873da190eb5ee83576ff519c2d564e1f841abe5b MD5sum: 7a97a6f55929cc103dd60d7783a9565e Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python3-docopt Source: docopt Version: 0.6.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 45 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Homepage: http://docopt.org Priority: optional Section: python Filename: pool/main/d/docopt/python3-docopt_0.6.1-1~nd70+1_all.deb Size: 15816 SHA256: 1b62134d98edd3913c9f63e95459fd4060a7605ba86b2681224e3b67d871d3e6 SHA1: 3b4a7537708129cfeff5dd576495ff49ad273c6c MD5sum: 9e083f57d7df454be40cbd47ceccfeee Description: Creates beautiful command-line interfaces (Python3) docopt helps you: . * define interface for your command-line app, and * automatically generate parser for it. . docopt is based on conventions that are used for decades in help messages and man pages for program interface description. Interface description in docopt is such a help message, but formalized. . This is the Python 3 compatible version of the package. Package: python3-funcsigs Source: python-funcsigs Version: 0.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 89 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python3-funcsigs_0.4-2~nd70+1_all.deb Size: 13976 SHA256: 6669bfb5b4602f6a920aada2542f45c5533b4573a88208bdff8fee57a63f5345 SHA1: 3a16578c6aecb3c0fc20cbc6b90cd3dd3b935b11 MD5sum: 1caeae1ebdfcf14bdd50b6ed3651f267 Description: function signatures from PEP362 - Python 3.x funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 3.x module. Package: python3-future Source: python-future Version: 0.15.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1663 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3.2 Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python3-future_0.15.2-1~nd70+1_all.deb Size: 414730 SHA256: 61799689907b299825a057073a62c642ff9ffca2f373109beb045a1a3d632384 SHA1: 1e95ec8d0e4a2f91cad2dbb2b6f7d2ab4331bce9 MD5sum: 6b60038675fb2473c47fcc8dc13fcae5 Description: Clean single-source support for Python 3 and 2 - Python 3.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 3.x module. Package: python3-git-annex-adapter Source: git-annex-adapter Version: 0.0.0~pre1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 58 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160726~) | git-annex-standalone (>= 6.20160726~), python3 (>= 3.2.3-3~) Homepage: https://github.com/alpernebbi/git-annex-adapter Priority: optional Section: python Filename: pool/main/g/git-annex-adapter/python3-git-annex-adapter_0.0.0~pre1-1~nd70+1_all.deb Size: 7006 SHA256: 568d1bbfcfd9296681afbe1731edb3535e46755863b115ad9cf0a01b69f69db2 SHA1: fb74d25c1979c1fd0208ef1aeedf4ea1d570d11b MD5sum: 3fbc298f1b817325c1072e9a5582a72e Description: call git-annex commands from within Python This is a minimalistic interface to git-annex. Commands are executed using subprocess and use their batch versions whenever possible. Package: python3-github Source: pygithub Version: 1.26.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 622 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Conflicts: python3-pygithub Replaces: python3-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python3-github_1.26.0-1~nd70+1_all.deb Size: 64772 SHA256: 759827630844e82e111e2d4edc8d20fc345437f9b23df4998d533d0cdcadebd6 SHA1: a7f45d33c315e26f94cd4d82aacf8f02d6f5f6a5 MD5sum: 663c4effe9a4710f04f48a9390b79497 Description: Access the full Github API v3 from Python3 This is a Python3 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python3-humanize Source: python-humanize Version: 0.5.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 114 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python3-humanize_0.5.1-2~nd70+1_all.deb Size: 14230 SHA256: 802cae58085919690f244c2b002dc6128e3e153b3b616a9052de742a78485a90 SHA1: 1921d412e6b4abdb2377ca04f29939000d380b1f MD5sum: 79d29249e95f0b1b5b5dbec47f75db7b Description: Python Humanize library (Python 3) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 3 version of the package. Package: python3-jdcal Source: jdcal Version: 1.0-1~nd70+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~nd70+1_all.deb Size: 7824 SHA256: 5bdfff822ef6095bc30f5e76758383e0618bad3e5508df67dcd01fcd159279f4 SHA1: d9f536955c46dad67c027ee9ddfde648141a72a4 MD5sum: 11511c0a1f0275aa7786e081b6400b3c 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 252 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) 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~nd70+1_all.deb Size: 71652 SHA256: bbf364d28dab9165d64f37d99a23641605e9512f73d96b9e3371ca73a0d9fb3c SHA1: 48d6edc53fe21796317768c747f29421f4366f86 MD5sum: 74e90fd0c96b1e3ac2e7286b9cc47970 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1461 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libopenmpi1.3, zlib1g (>= 1:1.1.4), python3 (>= 3.2.3-3~), python3 (<< 3.3) 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~nd70+1_i386.deb Size: 468682 SHA256: c89d7f98c2a3df69d33be851912208ba6aee1450d0600d7641d2161e8a714d2c SHA1: 7a6cf9906d5cb9174b57ad910a113aa490eea299 MD5sum: 827384d7d2cee0916361c38c01645ab9 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3249 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3.1+hg20131106-1~nd70+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~nd70+1_i386.deb Size: 1103052 SHA256: 8485dd1c82f32576249e30d5323d93071b8603739ff04da116abc32d8bb39a37 SHA1: 3beaccbec28f48e9e1640e682607aef09464192d MD5sum: e240b31fdcc9baeac05494629036edcd 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 163 Depends: neurodebian-popularity-contest, python3 (<< 3.3), python3 (>= 3.2.3-3~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python3-msgpack_0.4.2-1~nd70+1_i386.deb Size: 64738 SHA256: 7faa5f3b626fb47045fb2fcb272d6030b1d661ae09c8f20623556a5f11178ddc SHA1: 315b48339564dcf99c335e40f7cb859667c0cab6 MD5sum: 2aef5eb18adf24d782c9634e150b8822 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-nibabel Source: nibabel Version: 2.0.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63280 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy Suggests: python-nibabel-doc, python3-dicom, python3-fuse Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.0.2-1~nd70+1_all.deb Size: 2371322 SHA256: e24ccbeb4f838fb308de8a19af9ea11ebd8bdd369c83f58c9a292a61579c8371 SHA1: fe9268feaa33fb614d56d689a72d2ff66054a2d9 MD5sum: 89ba158f3d639745169f99c1cc9c1883 Description: Python3 bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. Package: python3-numexpr Source: numexpr Version: 2.6.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 551 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.6.1), python3-numpy-abi9, python3 (<< 3.3), python3 (>= 3.2.3-3~), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.6.1-2~nd70+1_i386.deb Size: 153372 SHA256: 1f8543c3ad58d8607284477a38710acf567a3d42ff8a5d0eefdbed3f0fe14930 SHA1: 563188da13d3051a303f013212fa631f73778f85 MD5sum: 0a7e20a38f6414251644546df35dff05 Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.6.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 433 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.6.1), python3-numpy-abi9, python3-dbg (<< 3.3), python3-dbg (>= 3.2), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.6.1-2~nd70+1), python3-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.6.1-2~nd70+1_i386.deb Size: 124466 SHA256: 7cb89947cd0c4afb0cf76a88a48c25f6e64a63f43d4549ae42cd73a18d4d6ab9 SHA1: 61e9cf83dbfa09576b2a6a1b4968c26b6c35a90b MD5sum: 18a5b2d12b6886307b3c1015b6ec8f24 Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-pandas Source: pandas Version: 0.14.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8918 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3-dateutil, python3-tz, python3-numpy (>= 1:1.6~), python3-pandas-lib (>= 0.14.1-1~nd70+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~nd70+1_all.deb Size: 1660916 SHA256: e3deb0e300bdc36e9c14edff51f90c7c447ba1adbb9ae95111732561499c98e5 SHA1: 34bff3e467ea08fc5b1c70701f03da30b04e058c MD5sum: cb66079236f59bd830bbab1f586b3105 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4826 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numpy (>= 1:1.6.1), python3-numpy-abi9, python3 (>= 3.2), python3 (<< 3.3) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.14.1-1~nd70+1_i386.deb Size: 1721502 SHA256: dd14662f6081deedc7936f687ab547ceb660bfa197d7298e417b4c21998423cf SHA1: 8d63113ce6300b59802faa1afd82674b889b99f3 MD5sum: 5adb19a159983f3734b87d75365cd698 Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 794 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3-six, python3-numpy Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1+git34-ga5b54c2-1~nd70+1_all.deb Size: 225286 SHA256: 644fe8e01c2e0e3d20ca676dc33fe6d5e87c7d47b47ed5363480a8d08a42adbc SHA1: 0b35c2e5c3bc1d1c31621cebfb8064392368e238 MD5sum: f298f46ac6128f08e8002d50a67acd69 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 242 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python3 (<< 3.3), python3 (>= 3.2.3-3~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python3-psutil_2.1.1-1~nd70+1_i386.deb Size: 70160 SHA256: fba0ed7d9ee05d44ef8654c48e84162ebed67ad1b8241ca40fb1ada393a60ce6 SHA1: 150fc4422cb9967b8d764ebe5cb53465b883c7b1 MD5sum: c06e1ca9d7bddcba115521708bfc7805 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-py Source: python-py Version: 1.4.30-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 269 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.30-1~nd70+1_all.deb Size: 76620 SHA256: a74e4468475c5f0bdf1a51714d99807f5f879d57735116a5009d04f083c43ceb SHA1: f9d34fd617c836286fb8eaf93e554f6cf040f94d MD5sum: 11294264841fbaaf65482c3ba36db38c Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-seaborn Source: seaborn Version: 0.7.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 787 Depends: neurodebian-popularity-contest, python3-matplotlib, python3 (>= 3.2.3-3~), python3-numpy, python3-scipy, python3-pandas Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.7.1-2~nd70+1_all.deb Size: 157798 SHA256: 148b7de7874f361a3626f7c2dad1a6acfe0c6f4f32c8444c555242ee945cadba SHA1: 6bc6c1eb949a87a319ebe23938808770cbce021b MD5sum: aec0ca54277fab13a757ef1a3b4d6009 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-six Source: six Version: 1.8.0-1~bpo70+1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.8.0-1~bpo70+1~nd70+1_all.deb Size: 13904 SHA256: c8d8b91b4850a797b976b16b009366e605939fc3af9fcec65f34ec1ecaca8c64 SHA1: 3894f1a468f505895b479473901378f9468757de MD5sum: 4bb2eef11fa797628724b6b9d5ef210e Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-skimage-lib Source: skimage Version: 0.10.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6883 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.4) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.10.1-1~nd+1_i386.deb Size: 905700 SHA256: 27be3eefe96e8c1754b96646fa70e371b1591252f34764203a9de515b9d6fc52 SHA1: 4bc5d6a4a4dbed47658f1c4ffee0680e4f152318 MD5sum: 95b2fb523aa05ad91dda93474ddf14c2 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: python3-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: neurodebian-popularity-contest, python3-rdflib, python3 (>= 3.2.3-3~) Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python3-sparqlwrapper_1.7.6-3~nd70+1_all.deb Size: 25208 SHA256: c0eff514b9f9c7f0756388beee6bc940a00c8f51a18a5187801714b0a562a87c SHA1: b7b59442b3f5b07c3e4a11b541227ba60e2f7195 MD5sum: a454100e2e11345227a88afd0fb21893 Description: SPARQL endpoint interface to Python3 This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 3 version of the package. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3 (>= 3.2.3-3~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd70+1_all.deb Size: 145052 SHA256: 43bb2696de87bbbfeba92a081d6d4e8140f5171d54747e183520cbe6bbf112b0 SHA1: c97f0a51dd909a2d425fc580d3d7b6537c46d355 MD5sum: 024cd5a3a245d9bb758779b9c7ea66e8 Description: sphinx theme from readthedocs.org (Python 3) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 3 version of the package. Package: python3-tqdm Source: tqdm Version: 4.4.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 164 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.4.1-1~nd70+1_all.deb Size: 41062 SHA256: 9e7e2ec0e1ad82a4401f662c5035773b37cf783aae8811746ed0667addd6c186 SHA1: 49055229670fe531ff3c3fec464ebef852d021cf MD5sum: 8c20e5a97ef7d3797c7b7fd99639382e Description: fast, extensible progress bar for Python 3 and CLI tool tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 3 version of tqdm and its command-line tool. Package: python3-tz Source: python-tz Version: 2012c-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, tzdata, python3 (>= 3.2.3-3~) Homepage: http://pypi.python.org/pypi/pytz/ Priority: optional Section: python Filename: pool/main/p/python-tz/python3-tz_2012c-1~nd70+1_all.deb Size: 31954 SHA256: 3e97caf66172c67dea29b32d60a6a976e032f2e3cb18dfea5ec7bb0c1a7618af SHA1: 4c06117f76e0b1ad499102b3844bd8cf2357cb7a MD5sum: 464ec516d7b9cbcf1f82127ecd56ebb7 Description: Python3 version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). . This package contains the Python 3 version of the library. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, python3-six (>= 1.6.1) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python3-w3lib_1.11.0-1~nd70+1_all.deb Size: 3162 SHA256: 5ccdebd7e96456781e94b4d02fc309e93e13a3d3d9fa4023e945e662e27fa785 SHA1: b76868afdcd8740fb74c2099a3e5e6086bf78b0e MD5sum: 63d2face39f9da53a28d8702fc587f25 Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.11-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2925 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit3.20, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.8, libvtk5.8-qt4, nifti2dicom (= 0.4.11-1~nd70+1), nifti2dicom-data (= 0.4.11-1~nd70+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.11-1~nd70+1_i386.deb Size: 632956 SHA256: 74bdb1b446ce467f42880cca810728f2bc99e8b46f9c4ad5cad92d5f6d9e199d SHA1: 6ced8c365b3c5201714ccca75a779d2bba0ca63a MD5sum: 6a4ebe0c69612c335b3998b5ee1438a3 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: rclone Version: 1.41-1~ndall0 Architecture: i386 Maintainer: Debian Go Packaging Team Installed-Size: 16874 Depends: libc6 (>= 2.3.6-6~) Built-Using: go-md2man (= 1.0.8+ds-1), golang-1.10 (= 1.10.3-1), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-github-a8m-tree (= 0.0~git20171213.cf42b1e-1), golang-github-abbot-go-http-auth (= 0.0~git20150714.0.46b9627-2), golang-github-aws-aws-sdk-go (= 1.12.79+dfsg-1), golang-github-azure-azure-sdk-for-go (= 10.3.0~beta-1), golang-github-azure-go-autorest (= 8.3.1-1), golang-github-coreos-bbolt (= 1.3.1-coreos.5-1), golang-github-davecgh-go-spew (= 1.1.0-4), golang-github-dgrijalva-jwt-go-v3 (= 3.1.0-2), golang-github-djherbis-times (= 1.0.1+git20170215.d25002f-1), golang-github-dropbox-dropbox-sdk-go-unofficial (= 4.1.0-1), golang-github-go-ini-ini (= 1.32.0-2), golang-github-google-go-querystring (= 0.0~git20170111.0.53e6ce1-4), golang-github-jlaffaye-ftp (= 0.0~git20170707.0.a05056b-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kardianos-osext (= 0.0~git20170510.0.ae77be6-5), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-mattn-go-runewidth (= 0.0.2+git20170510.3.97311d9-1), golang-github-ncw-go-acd (= 0.0~git20171120.887eb06-1), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-google-cloud (= 0.9.0-5), golang-goprotobuf (= 0.0~git20170808.0.1909bc2-2) Homepage: https://github.com/ncw/rclone Priority: optional Section: net Filename: pool/main/r/rclone/rclone_1.41-1~ndall0_i386.deb Size: 4618876 SHA256: f3d9fca60ef0cfd3221be8ef088af8a9fc3a2a2c99955034fe6b29a9e18eb42e SHA1: 50b47feb7ce2f1441e1a5cef84f91ef20d1e104f MD5sum: 8c73c00b1e80467960cb535af6d6e58f Description: rsync for commercial cloud storage Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers: . - Google Drive - Amazon S3 - Openstack Swift / Rackspace cloud files / Memset Memstore - Dropbox - Google Cloud Storage - Amazon Drive - Microsoft One Drive - Hubic - Backblaze B2 - Yandex Disk Package: remake Version: 3.82+dbg0.9+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 285 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_3.82+dbg0.9+dfsg-1~nd70+1_i386.deb Size: 174220 SHA256: 16dc2cb50299e87ab0d77c7410ae6cb37cbe2fb55368224d77cf62c6c80378df SHA1: 33ba0ff05c142b82a6cc32747e3ed6d4f79f5c1f MD5sum: 293eeed71510b5cc618f2475eb777f5e Description: GNU make fork with improved error reporting and debugging Modernized version of GNU make utility that adds improved error reporting, the ability to trace execution in a comprehensible way, and a debugger. Some of the features of the debugger are: * see the target call stack * set breakpoints on targets * show and set variables * execute arbitrary "make" code * issue shell commands while stopped in the middle of execution * inspect target descriptions * write a file with the commands of the target expanded Package: shogun-cmdline-static Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 139 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libreadline6 (>= 6.0), libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4) Conflicts: shogun-cmdline Replaces: shogun-cmdline Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-cmdline-static_1.1.0-6~nd70+1_i386.deb Size: 44436 SHA256: 2f66f11dd4f28724d347186cff4e521c53515fa2a5b4ff24aa9938affe26ef84 SHA1: bdf4d1ba7412f575fa7738f62b02d428bebd5c56 MD5sum: f1a8f4de11ed8a927002f042fce7ebd7 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the Readline package. Package: shogun-csharp-modular Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7564 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libshogun11, libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), libmono-corlib4.0-cil (>= 2.10.1) Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-csharp-modular_1.1.0-6~nd70+1_i386.deb Size: 1610202 SHA256: ecb779a20f581bc99789a5a957ddbba5b382f37322d7c8f49075cbae514a1176 SHA1: 4de58df824c725bd35aa941a9c72abb313103365 MD5sum: 62d3113cfa50c6f968d0486b226402f9 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the modular csharp package employing swig. Package: shogun-dbg Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67467 Depends: neurodebian-popularity-contest, libshogun11 (= 1.1.0-6~nd70+1) Homepage: http://www.shogun-toolbox.org Priority: extra Section: debug Filename: pool/main/s/shogun/shogun-dbg_1.1.0-6~nd70+1_i386.deb Size: 15946416 SHA256: 52ab8b93ed54edbd436b4fb6599632be4a5a2af8b85dce43e406867095553e01 SHA1: e36d49c92c4bcc609a5728c6523a6e9a597b826f MD5sum: fc183071c99dff11f6cebbf3ea1c77f0 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This package contains debug symbols for all interfaces. Package: shogun-doc-cn Source: shogun Version: 1.1.0-6~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1545 Depends: neurodebian-popularity-contest Recommends: shogun-python-modular, libshogun-dev Homepage: http://www.shogun-toolbox.org Priority: optional Section: doc Filename: pool/main/s/shogun/shogun-doc-cn_1.1.0-6~nd70+1_all.deb Size: 556068 SHA256: f8376758069c8e22fedb758202fea6063d95aa3aa4400f084c4f8e10b9118796 SHA1: 3f5b5ae50cc2dcf41c120bb995369dcda3e5cddd MD5sum: 44dcec822faa27167037f325ff2be792 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the Chinese user and developer documentation. Package: shogun-doc-en Source: shogun Version: 1.1.0-6~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 85407 Depends: neurodebian-popularity-contest Recommends: shogun-python-modular, libshogun-dev Conflicts: shogun-doc Replaces: shogun-doc Homepage: http://www.shogun-toolbox.org Priority: optional Section: doc Filename: pool/main/s/shogun/shogun-doc-en_1.1.0-6~nd70+1_all.deb Size: 17119184 SHA256: 3f07ea2441ab9f83d787f60ddb9cd08f4fc9394f062ac584ffe7e2a14e9b437f SHA1: d0333cc59cb4433eefd2ba5123fe7384b6430041 MD5sum: 4462916c2cb8bd9f994d83f46f465022 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the English user and developer documentation. Package: shogun-elwms-static Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 203 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libpython2.7 (>= 2.7), libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), r-base-core, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9 Conflicts: shogun-elwms Replaces: shogun-elwms Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-elwms-static_1.1.0-6~nd70+1_i386.deb Size: 59994 SHA256: 39303c945b5d825b6801e810fd93dec9e56537da08e14edf788806a32b115835 SHA1: f156bb65304c0d74c3261cb0e57d280940ed4d1b MD5sum: 64f68e82b41d23c6e71a6a02c19d5d34 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the eierlegendewollmilchsau package, providing interfaces and interoperability commands to R, Octave and Python all at once. Package: shogun-java-modular Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8016 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4) Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-java-modular_1.1.0-6~nd70+1_i386.deb Size: 2376476 SHA256: 929e165f834c1e8c0fb3db53ac79f5db398dd3777139c429511ea7f155f75087 SHA1: 14007d2254bfb577fb5ebb81dd536cf838cceea9 MD5sum: 917f8c82dd311e585ea0292e0f8d2d30 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the modular java package employing swig. Package: shogun-lua-modular Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12760 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblua5.1-0, liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4) Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-lua-modular_1.1.0-6~nd70+1_i386.deb Size: 2514456 SHA256: adb2e2b86217572730a45d189187401e6235208d5dbd0377d6fb38e8899aaf2a SHA1: d0b7097f3b30e33b73e9724f993220e91ab3192d MD5sum: 22c1efe3e06637e4213cc6e87b733d29 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the modular lua package employing swig. Package: shogun-python-modular Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 26876 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libpython2.6 (>= 2.6), libpython2.7 (>= 2.7), libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), python (<< 2.8), python (>= 2.6.6-7~), python-numpy (>= 1:1.6.1), python-numpy-abi9 Recommends: python-matplotlib, python-scipy Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-python-modular_1.1.0-6~nd70+1_i386.deb Size: 6022350 SHA256: acbf195a7a7de514b8ce1c0d9967ef8d398174802a8c1ca615557384d4f59f68 SHA1: 57735f39db18c23ac3d836cb2910a490d0d554fc MD5sum: 5e10388f2b1106c2b07543469272e975 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the modular Python package employing swig. Package: shogun-python-static Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 229 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libpython2.6 (>= 2.6), libpython2.7 (>= 2.7), libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.6.1), python-numpy-abi9 Recommends: python-matplotlib Conflicts: shogun-python Replaces: shogun-python Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-python-static_1.1.0-6~nd70+1_i386.deb Size: 64668 SHA256: 206ca944624e937002b2d7c2ba8e724435fd2750998821875b473abab6d98603 SHA1: 41875c4eab9ff34bbe49bac7e46998dac62390bd MD5sum: 5b7deea53ffa72e332e59b135670cd92 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the static Python package without using swig. Package: shogun-r-static Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 256 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), r-base-core Conflicts: shogun-r Replaces: shogun-r Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-r-static_1.1.0-6~nd70+1_i386.deb Size: 65066 SHA256: e4b2980fb21ca6e8cb36f7d1274826bac6f5e02951d7e126951b0ec3d2a30a5c SHA1: d71b2a5ef9be9e47b0bfeb2049b6411b1c33af1f MD5sum: d8c5233ea02c74c2450220bc434ec2fa Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the R package. Package: shogun-ruby-modular Source: shogun Version: 1.1.0-6~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9935 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libglpk0 (>= 4.30), libhdf5-7, libjson0 (>= 0.10), liblzma5 (>= 5.1.1alpha+20110809), liblzo2-2, libruby1.9.1 (>= 1.9.2.0), libshogun11 (= 1.1.0-6~nd70+1), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4) Homepage: http://www.shogun-toolbox.org Priority: optional Section: science Filename: pool/main/s/shogun/shogun-ruby-modular_1.1.0-6~nd70+1_i386.deb Size: 1878032 SHA256: 01faccb19ae22776ac59e369e8f8b29b2eb03e78294a2213fa44991360a2b020 SHA1: 2a97dc00483ba3b0e0522f452cf22cedf3a821e5 MD5sum: c18f04c77508a07b2058c29e13732422 Description: Large Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the modular ruby package employing swig. Package: sigviewer Version: 0.5.1+svn556-3~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 936 Depends: neurodebian-popularity-contest, libbiosig1, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.6) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-3~nd70+1_i386.deb Size: 420294 SHA256: 4d3f2ae26704777e34a0e38902d31099643a2be77d5c8ab09d50f616a5241723 SHA1: 373ffbc324ba8859a045aef39734c92e08f2d511 MD5sum: fc5cef1b5336007a2abadd57ef0bbaf8 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of 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 . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: singularity-container Version: 2.6.1-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2500 Depends: neurodebian-popularity-contest, python, squashfs-tools, ca-certificates, libarchive12, libc6 (>= 2.11) Recommends: e2fsprogs Homepage: http://www.sylabs.io Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.6.1-2~nd70+1_i386.deb Size: 774186 SHA256: 8e72c41fa2963ebc24229ae06fddc44e1753256ff459aaa3ed0fdf5b596a22d8 SHA1: 5c9da98d70b776afbf8615ba0042993b7c5a1fc6 MD5sum: 776828274efd94a27f249863f7a40156 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18626 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~nd70+1_all.deb Size: 10751106 SHA256: 4b0892096fb3e6c5ba1254a3c3a218a92ae151e1a37fb8fc29dadbac8b624a6d SHA1: 0397da1f5bbd5171f4ef11c705679bd2a2915530 MD5sum: 283cc17b8f9c34af894c68533fe70a57 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73046 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd70+1_all.deb Size: 52177460 SHA256: 51fc6055c99b93fcf82446d3357a9b8143dee566714de2921103a58a61eef981 SHA1: 11a2d79617c8c0883acdfc4e3689baf240bcdb79 MD5sum: e3fb3e6df0f60a562696f6ad2a91b292 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~nd70+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9273 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd70+1_all.deb Size: 8991102 SHA256: e203c8227771f56005d1e04f7fbec1a7bfc58c5ba9dde1da5aa8bc32f434f9c2 SHA1: a984401fdd20fa64f68b76ec1fc06d73e6ed6b4c MD5sum: 3c6e980cbe8ec3bc7f268fcb98d177bf 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: spyder Version: 2.2.5+dfsg-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 113 Depends: neurodebian-popularity-contest, python, python-spyderlib (= 2.2.5+dfsg-1~nd70+1) Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: devel Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd70+1_all.deb Size: 56614 SHA256: fe5146cc4279f0846d8b9c0815bdbbda5bdda7ad8a664d81933772b465298ec4 SHA1: 61ba32cf4dbeb6bcc5e708e917e344a913401bd4 MD5sum: 52db6267791f2eee2221b83ac91a1e29 Description: python IDE for scientists Spyder (previously known as Pydee) is a free open-source Python development environment providing MATLAB-like features in a simple and light-weighted software Package: spykeviewer Version: 0.4.4-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2011 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.4-1~nd70+1_all.deb Size: 1344274 SHA256: f113a77bcf0c3e0b0adffe628a5cc3cfd8fee3909a27ca4cbac8f4f839dc3cbd SHA1: f698246fd9c102be479559472d55af52f810513e MD5sum: 061cfffc25feb42cc402a44da792cdac 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~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 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~nd70+1_all.deb Size: 28600 SHA256: d06a1ee5b6de6404f66db07820f084ca9699bfcef21015bb34c9cd64e1900e74 SHA1: 6515b207f33e7ef2ea59d0db40bb2b35d39355b8 MD5sum: 365f3a53daff4820e153393bb90a269c 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: 2.6, 2.7 Package: stimfit Version: 0.15.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2916 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3 | libatlas3-base, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1), zlib1g (>= 1:1.1.4), python (>= 2.6.6-7~), python-numpy (>= 1:1.6.1), python-numpy-abi9, python2.7, libsuitesparse-dev, zlib1g-dev, python-wxgtk3.0 | python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.15.4-1~nd70+1_i386.deb Size: 1128518 SHA256: 51ffd2ecce7ac8f449ca586baf189d5a897b0191148b64efee78fe14b48b3658 SHA1: d9ffde06bca2bca5ec675a7d7a905e190871bfe6 MD5sum: 9ab2842e14447b1d54d4c459af8dcd51 Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.15.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20197 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.15.4-1~nd70+1_i386.deb Size: 7528898 SHA256: d3012f6aef3b81b3151082208ef47050acdab875130a4b0589498843541d701f SHA1: 8bc824b5d770de831e6546b367f91aab87d6682a MD5sum: 5a848d96a62338177745dba310c00e1a 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: svgtune Version: 0.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-1~nd70+1_all.deb Size: 6828 SHA256: 664347bc9decb736aec4f14819a9eef0c8afedf8aae82d45087ff30facae72af SHA1: c2ca191c7b3cd09c05d737e60ed14c298dd3190e MD5sum: ac63ca302b7db2272aced98a86d44a08 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: tar Version: 1.29b-1.1~nd70+1 Architecture: i386 Essential: yes Maintainer: NeuroDebian Maintainers Installed-Size: 2981 Pre-Depends: libacl1 (>= 2.2.51-8), libc6 (>= 2.8), libselinux1 (>= 1.32) Suggests: bzip2, ncompress, xz-utils, tar-scripts Conflicts: cpio (<= 2.4.2-38) Breaks: dpkg-dev (<< 1.14.26) Replaces: cpio (<< 2.4.2-39) Multi-Arch: foreign Priority: required Section: utils Filename: pool/main/t/tar/tar_1.29b-1.1~nd70+1_i386.deb Size: 1201162 SHA256: ea6a6d6df9da3052033cc755535c73fbf8274236202b78037a4431d73b186705 SHA1: 3e44dd0b318bf1ef238e88ec21019b4f2bf36e58 MD5sum: 97961bcd462746f0e7499f096018b8ef Description: GNU version of the tar archiving utility Tar is a program for packaging a set of files as a single archive in tar format. The function it performs is conceptually similar to cpio, and to things like PKZIP in the DOS world. It is heavily used by the Debian package management system, and is useful for performing system backups and exchanging sets of files with others. Package: tar-scripts Source: tar Version: 1.29b-1.1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest Conflicts: dump, openafs-client Multi-Arch: foreign Priority: optional Section: utils Filename: pool/main/t/tar/tar-scripts_1.29b-1.1~nd70+1_i386.deb Size: 22328 SHA256: 6275218d213d782b790df2ab5c1e521f52d8411c42900dd490e7fb90a9a6a194 SHA1: 7ddb2c1ec5aee1ea999daed305d8dd43a24875ce MD5sum: 03d7f40c944cbd8c817f8c9b3d3b4399 Description: optional scripts for GNU version of the tar archiving utility This package provides the backup, restore, backup.sh, and dump-remind scripts that are mentioned in the tar documentation. Package: tcl-vtk Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17913 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd70+1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libx11-6, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc Replaces: vtk, vtk-tcl Homepage: http://www.vtk.org/ Priority: optional Section: interpreters Filename: pool/main/v/vtk/tcl-vtk_5.8.0-7+b0~nd70+1_i386.deb Size: 5575448 SHA256: db6fc0818630854c57cf93dc16f9f04174a8146603d7b852e94766239d31a23e SHA1: 50dbeb7114b117248c70470d0637409d90b4732b MD5sum: 6644fea58558302edd2bd120c6a7732e Description: Tcl bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries and executable that enable one to use VTK from Tcl/Tk scripts. You will need Tcl/Tk and vtk installed to use this. Package: testkraut Version: 0.0.1-1~nd70+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~nd70+1_all.deb Size: 100034 SHA256: 569f799af355429d7939adc34742caadb6f3eb108bb1a32b35cc5cabdb8336ca SHA1: e4a40dab2d773f92b8a810ba078d96d218775dcb MD5sum: 1a32c11b522abfa6f8b658c890f2cbe4 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: 2.6, 2.7 Package: tigervnc-common Source: tigervnc Version: 1.2.0+X1.12.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgnutls26 (>= 2.12.17-0), libice6 (>= 1:1.0.0), libjpeg8 (>= 8c), libpam0g (>= 0.99.7.1), libsm6, libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6 (>= 2:1.4.99.1), libxext6, zlib1g (>= 1:1.1.4) Conflicts: tigervnc-server (<< 1.1.90), tigervnc-viewer (<< 1.1.90) Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-common_1.2.0+X1.12.4-1~nd70+1_i386.deb Size: 80342 SHA256: ae13fb5ae47b03f1a5ba38c25bcc5674bb89c73a469a0c9472e2095e0a6828a8 SHA1: 43c290b569a2e7e3d3c5c445d597d67178b83cd3 MD5sum: ae8c226e817175733dbe1e1da45ebcdd Description: Virtual network computing; Common software needed by clients and servers VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It is implemented in a client/server model. This package provides the common software for both client and server. Package: tigervnc-scraping-server Source: tigervnc Version: 1.2.0+X1.12.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 580 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libc6 (>= 2.11), libgcc1 (>= 1:4.1.1), libgnutls26 (>= 2.12.17-0), libice6 (>= 1:1.0.0), libjpeg8 (>= 8c), libpam0g (>= 0.99.7.1), libsm6, libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxext6, libxtst6, zlib1g (>= 1:1.1.4) Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-scraping-server_1.2.0+X1.12.4-1~nd70+1_i386.deb Size: 229136 SHA256: f14e54f4d29882dff5efe9b4de1e8c0e1477f881d1194ccf5acbfc9fe5ac19d9 SHA1: e5de45d70367e23fe8bb1489adf5952ee1dbd7d6 MD5sum: 7fab58d11b929387a892607ca9d7561b Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . This package provides a vncserver which uses screen scraping of an already running X server to provide its VNC desktop. The VNC desktop can be viewed by any vncviewer even on other operating systems. . Note: If you only want to scrap your local X11 server, you should consider the tigervnc-xorg-extension package. This package provides the vnc extension for your local X11 server. The usage of this extension is more efficient than a scraping vnc server. Package: tigervnc-standalone-server Source: tigervnc Version: 1.2.0+X1.12.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2635 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libaudit0 (>= 1.7.13), libc6 (>= 2.11), libgcc1 (>= 1:4.1.1), libgcrypt11 (>= 1.4.5), libgnutls26 (>= 2.12.17-0), libjpeg8 (>= 8c), libpam0g (>= 0.99.7.1), libpixman-1-0 (>= 0.21.6), libselinux1 (>= 2.0.82), libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxau6, libxdmcp6, libxfont1 (>= 1:1.4.2), zlib1g (>= 1:1.1.4), perl Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-standalone-server_1.2.0+X1.12.4-1~nd70+1_i386.deb Size: 1167920 SHA256: 7b79c6f51557612c554c6dcb7289aaf57fdb80c501b2de057105d34889beb7e7 SHA1: a5bd862821fafd6f8a36001e1f684ed96b214bc8 MD5sum: e32441d6bd7711411a4136f101ea757c Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . This package provides a standalone vncserver to which X clients can connect. The server generates a display that can be viewed with a vncviewer. . Note: This server does not need a display. You need a vncviewer to see something. This viewer may also be on a computer running other operating systems. Package: tigervnc-viewer Source: tigervnc Version: 1.2.0+X1.12.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1104 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), tigervnc-common, libc6 (>= 2.11), libfontconfig1 (>= 2.9.0), libgcc1 (>= 1:4.1.1), libgnutls26 (>= 2.12.17-0), libice6 (>= 1:1.0.0), libjpeg8 (>= 8c), libpam0g (>= 0.99.7.1), libsm6, libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxcursor1 (>> 1.1.2), libxext6, libxfixes3, libxft2 (>> 2.1.1), libxinerama1, zlib1g (>= 1:1.1.4) Provides: vnc-viewer Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-viewer_1.2.0+X1.12.4-1~nd70+1_i386.deb Size: 506614 SHA256: 7a8a5a9bce1b6849900f08c2d2367a0f9b231e4b85ab5207629e270e7d323755 SHA1: 4c00cc41f63ec2ce00e57894e6cf7c15b812293a MD5sum: d9fc92b1b0cfb4b24fe21886933fa88c Description: Virtual network computing client software for X VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It is implemented in a client/server model. This package provides a vncclient for X, with this you can connect to a vncserver somewhere in the network and display its content in a window. There are vncservers available for other operating systems. Package: tigervnc-xorg-extension Source: tigervnc Version: 1.2.0+X1.12.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 787 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libaudit0 (>= 1.7.13), libc6 (>= 2.11), libgcc1 (>= 1:4.1.1), libgnutls26 (>= 2.12.17-0), libjpeg8 (>= 8c), libpam0g (>= 0.99.7.1), libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), zlib1g (>= 1:1.1.4) Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server, vnc-xorg-extension Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-xorg-extension_1.2.0+X1.12.4-1~nd70+1_i386.deb Size: 289736 SHA256: 9cd0f86c17862f44b1e02f67c1bc7dbaf1eb3a2e546abb641d085a90ace2099b SHA1: b0eecce9003acc408b5502526fb476724bf34e9e MD5sum: 3c706b4a0128e78fce5d015935d644fb Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It contains an X server connector so clients can connect to your local X desktop directly. Package: ubuntu-keyring Version: 2010.+09.30~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd70+1_all.deb Size: 11794 SHA256: c326d77f59c53ce386ed48a4f622087920af9c2d0a9b826e734680500b0cd3a0 SHA1: a46c68a0539f105919576423f0daeb6709e6a10a MD5sum: 8bed9b239d848186981a2e04eec03bb1 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: uftp Version: 4.9.3-1+nd1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 542 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libssl1.0.0 (>= 1.0.1), debconf (>= 0.5) | debconf-2.0 Homepage: http://uftp-multicast.sourceforge.net/ Priority: optional Section: net Filename: pool/main/u/uftp/uftp_4.9.3-1+nd1~nd70+1_i386.deb Size: 245992 SHA256: 3e8acf717825b49218d240a6804301455c622df26d1c921dcf8d6ef9aadda298 SHA1: 8d7cbfd7d12775ea436dc56ba625a126393650aa MD5sum: 688d17616e438e9fbafec7405fa88f64 Description: Encrypted multicast file transfer program Utility for secure, reliable, and efficient file transfer to multiple receivers simultaneously. This is useful for distributing large files to a large number of receivers, and is especially useful for data distribution over a satellite link where the inherent delay makes any TCP based communication highly inefficient. Package: utopia-documents Version: 2.4.4-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19190 Depends: neurodebian-popularity-contest, libboost-python1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.11), libexpat1 (>= 2.0.1), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.7 (>= 1.7.0), libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libpcre3 (>= 8.10), libpcrecpp0 (>= 7.7), libpython2.7 (>= 2.7), libqglviewer-qt4-2 (>= 2.3.4), 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), libqt4-xmlpatterns (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4 (>= 2.1.0~2011week13), libraptor1 (>= 1.4.21-3), libsm6, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libx11-6, libxext6, zlib1g (>= 1:1.1.4), python (>= 2.6.6-7~), 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~nd70+1_i386.deb Size: 7739126 SHA256: a7720abc6e5d777419a0c22a7fa0dc79f5408489faea07bf04a08ed195168264 SHA1: 4b9edebbab1153f561c90785b7067255ee29dcfc MD5sum: d346b6bd966f35673e6d6a8ef424491e 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 42939 Depends: neurodebian-popularity-contest, utopia-documents (= 2.4.4-1~nd70+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_2.4.4-1~nd70+1_i386.deb Size: 42032042 SHA256: ae7d166f96d632739a11fb38e95c38c33de4ee4ad54e5bae14c4170991cad5eb SHA1: 0ec10807774c4139e787e1b4da59a4a3af9bad73 MD5sum: ed1c8e8e7c63c740cf66c7e33a77b09f 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: via-bin Source: via Version: 2.0.4-2~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 500 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia2, libx11-6, libxext6, libxmu6, libxt6 Recommends: libvia-doc Conflicts: via, via-utils Replaces: via-utils Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/v/via/via-bin_2.0.4-2~nd70+1_i386.deb Size: 169608 SHA256: 6f0f72c3f1a29e2eacab8761769bb352224352c8696a1f7193218587f96149db SHA1: ba36ad1b6eb3b45c96ab51db724f0292e60c79e2 MD5sum: 675c7b8e6fe2c1336d76bc5dac7c21bc Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: vowpal-wabbit Version: 7.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 45 Depends: neurodebian-popularity-contest, libboost-program-options1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libvw0 (= 7.3-1~nd70+1), zlib1g (>= 1:1.1.4) Suggests: vowpal-wabbit-doc Homepage: http://hunch.net/~vw/ Priority: optional Section: science Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit_7.3-1~nd70+1_i386.deb Size: 20898 SHA256: 1257728006c82df996bb4fd559efe2313f279bb7d82480b2c5ebad781f3f3fe2 SHA1: 8359e1106004dc1f96980556883dbca12f156a45 MD5sum: cdd350f9ea1fa8c7a0569c137cdce54e Description: fast and scalable online machine learning algorithm Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing Package: vowpal-wabbit-dbg Source: vowpal-wabbit Version: 7.3-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5608 Depends: neurodebian-popularity-contest, vowpal-wabbit (= 7.3-1~nd70+1) Homepage: http://hunch.net/~vw/ Priority: extra Section: debug Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-dbg_7.3-1~nd70+1_i386.deb Size: 2167392 SHA256: ab759d4b5d1c2995dc31c3510c1100668b454b79f3929afda3dfdef2e03fe318 SHA1: 5d1dc9c5d60ac4330022a714949cbb526738f31a MD5sum: 55a2c8a07723760486ae6a43e715a2be Description: fast and scalable online machine learning algorithm - debug files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains debug symbols for the binaries shipped by vowpal-wabbit packages. Package: vowpal-wabbit-doc Source: vowpal-wabbit Version: 7.3-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70918 Depends: neurodebian-popularity-contest Recommends: vowpal-wabbit Homepage: http://hunch.net/~vw/ Priority: optional Section: doc Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-doc_7.3-1~nd70+1_all.deb Size: 50202380 SHA256: 213cdcb76214686a0a8983ea5fc9000f30097ad7ece36f32986f81828614bbfd SHA1: 82dace7aad70a98fdf52f35495b021f2ce9caea5 MD5sum: 5cd618999611d5d61901a70a6057e23c Description: fast and scalable online machine learning algorithm - documentation Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains examples (tests) for vowpal-wabbit. Package: voxbo Version: 1.8.5~svn1246-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9696 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti, matlab-spm8 Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1246-1~nd70+1_i386.deb Size: 3704676 SHA256: e287d12a4f8562cc6ed2f8e64d64938cfa33a64e2a0edaf34fd1a52d7da63e78 SHA1: f361d60af81addd6abc74b53da16da063985c7e3 MD5sum: 5f54ecfba6b9c661369ce81d661a53db Description: processing, statistical analysis, and display of brain imaging data This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others. Package: vrpn Version: 07.30+dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 327 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd70+1), libvrpnserver0 (= 07.30+dfsg-1~nd70+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd70+1_i386.deb Size: 111150 SHA256: d7b89bc0906c4a5ce0388808e2eddbca9bf1a84f0576ba2e2e6713782562dbdf SHA1: 8a2654c34b0b6e266bf03916f3cda75a844bcb46 MD5sum: 8c6a69010853c891c6da4b1bc99c8b60 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~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4203 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd70+1), libvrpnserver0 (= 07.30+dfsg-1~nd70+1), vrpn (= 07.30+dfsg-1~nd70+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd70+1_i386.deb Size: 1635436 SHA256: a788357d1644ac712d488a6e6c3879efd17f77a4591817dce2991d30df15b8f1 SHA1: 22985accf28c8f2ed701dfaaf7083384ff82c2d5 MD5sum: e1c58e3802bf7e285b688af4b098a7b4 Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-doc Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 342007 Depends: neurodebian-popularity-contest, doc-base Suggests: libvtk5-dev, vtk-examples, vtkdata Homepage: http://www.vtk.org/ Priority: optional Section: doc Filename: pool/main/v/vtk/vtk-doc_5.8.0-7+b0~nd70+1_all.deb Size: 66709864 SHA256: 1a71117b4f7574428e9da98482fb0c2cb41581e0ca6d2e931ea639a5da51263c SHA1: 74a40de489c5a44161b4aa468547d356da0bf911 MD5sum: 4c9a59935cca888f4c608d56f7eb3213 Description: VTK class reference documentation The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains exhaustive HTML documentation for the all the documented VTK C++ classes. The documentation was generated using doxygen and some excellent perl scripts from Sebastien Barre et. al. Please read the README.docs in /usr/share/doc/vtk-doc/ for details. The documentation is available under /usr/share/doc/vtk/html. Package: vtk-examples Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2521 Depends: neurodebian-popularity-contest Suggests: libvtk5-dev, tcl-vtk, python-vtk, vtk-doc, python, tclsh, libqt4-dev Homepage: http://www.vtk.org/ Priority: optional Section: graphics Filename: pool/main/v/vtk/vtk-examples_5.8.0-7+b0~nd70+1_all.deb Size: 578898 SHA256: d070189a36ffd5bed00de02b3c794d0fa8f8bb2765fbc36f0f99c1634cda5ac7 SHA1: 132096d02c71c2f969d9baff0842e4afcdbb501c MD5sum: c018d4c1cace1b218dec239a1cf5e39e Description: C++, Tcl and Python example programs/scripts for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains examples from the VTK source. To compile the C++ examples you will need to install the vtk-dev package as well. Some of them require the libqt4-dev package. . The Python and Tcl examples can be run with the corresponding packages (python-vtk, tcl-vtk). Package: xmhtml1 Source: xmhtml Version: 1.1.7-17~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 473 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libc6 (>= 2.7), libjpeg8 (>= 8c), libpng12-0 (>= 1.2.13-4), libxpm4 Priority: optional Section: libs Filename: pool/main/x/xmhtml/xmhtml1_1.1.7-17~nd70+1_i386.deb Size: 249314 SHA256: e41759a2b9cce7cceb13753d1b270ce73534e52630e33c70d06ddb2b86ca01c8 SHA1: 0d9e8ded6b3c931b81d133ff0decba994d6b0a03 MD5sum: a6d6383ede5c3b85ed68c4dca377ad83 Description: A Motif widget for display HTML 3.2 XmHTML is a high performance Motif Widget capable of displaying HTML 3.2 confirming text. Graphics support, lesstif compatibility and extensive documentation are amongst its many features. . This package provides the runtime shared library. The xmhtml-dev package provides the header files, and the static library. Package: xmhtml1-dev Source: xmhtml Version: 1.1.7-17~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 830 Depends: neurodebian-popularity-contest, xmhtml1, lesstif2-dev | libmotif-dev, libc6-dev Conflicts: xmhtml-dev Provides: xmhtml-dev Priority: optional Section: devel Filename: pool/main/x/xmhtml/xmhtml1-dev_1.1.7-17~nd70+1_i386.deb Size: 341378 SHA256: 865d7001778b4af7b01c703e55529bb636bb386353e4aced800d36facfb58b88 SHA1: 76755ed34a06b8e663f40d48cb488906d14b8a96 MD5sum: d8e32052d4db5a715aa6f020ea86430f Description: A Motif widget for display HTML 3.2 XmHTML is a high performance Motif Widget capable of displaying HTML 3.2 confirming text. Graphics support, lesstif compatibility and extensive documentation are amongst its many features. . This is the development kit, containing static libraries and header files necessary to build programs that use xmhtml. The runtime library is provided by the xmhtml package. Package: xppaut Version: 6.11b+1.dfsg-1~nd70+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5804 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libx11-6 Homepage: http://www.math.pitt.edu/~bard/xpp/xpp.html Priority: optional Section: science Filename: pool/main/x/xppaut/xppaut_6.11b+1.dfsg-1~nd70+1_i386.deb Size: 4142704 SHA256: 66687a822868b877cc2db25953618d498b4dbc157014881a3ef84b07215abdba SHA1: 061882bed8bcbcd4b6d8ac42209d1fc37ef5a331 MD5sum: f8a0b357dbb31ae1b6483b034b59c8d9 Description: Phase Plane Plus Auto: Solves many kinds of equations XPPAUT is a tool for solving * differential equations, * difference equations, * delay equations, * functional equations, * boundary value problems, and * stochastic equations. . The code brings together a number of useful algorithms and is extremely portable. All the graphics and interface are written completely in Xlib which explains the somewhat idiosyncratic and primitive widgets interface. Package: youtube-dl Version: 2021.12.17-1~nd110+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5937 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3:any Recommends: aria2 | wget | curl, ca-certificates, ffmpeg, mpv | mplayer, python3-pyxattr, rtmpdump, python3-pycryptodome Suggests: libfribidi-bin | bidiv, phantomjs Homepage: https://ytdl-org.github.io/youtube-dl/ Priority: optional Section: web Filename: pool/main/y/youtube-dl/youtube-dl_2021.12.17-1~nd110+1_all.deb Size: 1128692 SHA256: 75859d2f34a475fc0f199cd6d2b73e18c29cda44406530964890dcb790008eca SHA1: 09f85f2abc32eb5e9c2ccd6bfd1354ea332b6489 MD5sum: 6d04814be91bd9f85a7d3793ff2a2fb3 Description: downloader of videos from YouTube and other sites youtube-dl is a small command-line program to download videos from YouTube.com and other sites that don't provide direct links to the videos served. . youtube-dl allows the user, among other things, to choose a specific video quality to download (if available) or let the program automatically determine the best (or worst) quality video to grab. It supports downloading entire playlists and all videos from a given user. . Currently supported sites (or features of sites) are: . 1tv, 20min, 220.ro, 23video, 24video, 3qsdn, 3sat, 4tube, 56.com, 5min, 6play, 7plus, 8tracks, 91porn, 9c9media, 9gag, 9now.com.au, abc.net.au, abc.net.au:iview, abcnews, abcnews:video, abcotvs, abcotvs:clips, AcademicEarth:Course, acast, acast:channel, ADN, AdobeConnect, adobetv, adobetv:channel, adobetv:embed, adobetv:show, adobetv:video, AdultSwim, aenetworks, aenetworks:collection, aenetworks:show, afreecatv, AirMozilla, AliExpressLive, AlJazeera, Allocine, AlphaPorno, Amara, AMCNetworks, AmericasTestKitchen, AmericasTestKitchenSeason, anderetijden, AnimeOnDemand, Anvato, aol.com, APA, Aparat, AppleConnect, AppleDaily, ApplePodcasts, appletrailers, appletrailers:section, archive.org, ArcPublishing, ARD, ARD:mediathek, ARDBetaMediathek, Arkena, arte.sky.it, ArteTV, ArteTVEmbed, ArteTVPlaylist, AsianCrush, AsianCrushPlaylist, AtresPlayer, ATTTechChannel, ATVAt, AudiMedia, AudioBoom, audiomack, audiomack:album, AWAAN, awaan:live, awaan:season, awaan:video, AZMedien, BaiduVideo, Bandcamp, Bandcamp:album, Bandcamp:weekly, bangumi.bilibili.com, bbc, bbc.co.uk, bbc.co.uk:article, bbc.co.uk:iplayer:playlist, bbc.co.uk:playlist, BBVTV, Beatport, Beeg, BehindKink, Bellator, BellMedia, Bet, bfi:player, bfmtv, bfmtv:article, bfmtv:live, BibelTV, Bigflix, Bild, BiliBili, BilibiliAudio, BilibiliAudioAlbum, BiliBiliPlayer, BioBioChileTV, Biography, BIQLE, BitChute, BitChuteChannel, BleacherReport, BleacherReportCMS, blinkx, Bloomberg, BokeCC, BongaCams, BostonGlobe, Box, Bpb, BR, BravoTV, Break, brightcove:legacy, brightcove:new, BRMediathek, bt:article, bt:vestlendingen, BusinessInsider, BuzzFeed, BYUtv, Camdemy, CamdemyFolder, CamModels, CamTube, CamWithHer, canalc2.tv, Canalplus, Canvas, CanvasEen, CarambaTV, CarambaTVPage, CartoonNetwork, cbc.ca, cbc.ca:olympics, cbc.ca:player, cbc.ca:watch, cbc.ca:watch:video, CBS, CBSInteractive, CBSLocal, CBSLocalArticle, cbsnews, cbsnews:embed, cbsnews:livevideo, CBSSports, CCMA, 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youku, youku:show, YouNowChannel, YouNowLive, YouNowMoment, YouPorn, YourPorn, YourUpload, youtube, youtube:favorites, youtube:history, youtube:playlist, youtube:recommended, youtube:search, youtube:search:date, youtube:subscriptions, youtube:tab, youtube:truncated_id, youtube:truncated_url, youtube:watchlater, YoutubeYtBe, YoutubeYtUser, Zapiks, Zattoo, ZattooLive, ZDF, ZDFChannel, zingmp3, Zype