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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1596 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_amd64.deb Size: 711014 SHA256: bbc1101b36fee0cd4e8823d48a4988b9bd5b67bc56c93e9b954c4c093025dc15 SHA1: 0e3d3bb3eecde836ad2769e5a49fc835a1aaad19 MD5sum: d1162a2c69724b8894cb1922acbd3131 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: 2.0.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 130050 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libinsighttoolkit4.5, libstdc++6 (>= 4.6), libvtk5.8 Recommends: environment-modules Suggests: fsl, gridengine-client, r-base-core Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_2.0.0-1~nd70+1_amd64.deb Size: 35134876 SHA256: 51058e4856668785a04a6d98877701c60f8c0589b5f72be55f6777347a0ac415 SHA1: cea0dbd5a34eb463eedef938f576f4adaf1ea40e MD5sum: 501b5fa309b5e98e56449e51d11bd5e0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 661 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_amd64.deb Size: 280862 SHA256: ede889a8d73ead0cb58a3acf4d41d4c6801dc62d7e4003c1a6ba41d586e1c5ac SHA1: 691229b07b2438d11df1eedf9c90cf178c6ea00d MD5sum: 3bf49074d6f4bee801f9150815466c2c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3316 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_amd64.deb Size: 1658468 SHA256: 4e0fbc7737cf0865e178008f922e405c88daf6b8234e8721d7ef9ad3297aafd0 SHA1: 27b17346abeeac0714ead00ff9f15cf72138b7a7 MD5sum: 62d0c45ba9bdcfc1c3498f050fcaf3d4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5567 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_amd64.deb Size: 5289764 SHA256: 0fa584fe17336b8cc462e86389975d0e488cc8f2055c724296a507c8d1b64727 SHA1: 758bc4a58242df38835dcc3bec2f7f689aa90d65 MD5sum: 6bdec99946dea97a41a1b0b8bb531d64 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18488 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 7376026 SHA256: 18a7e2e54edf249436ed4f63dd73b3ca2642abf97e3f0a9581486abf65c8e32c SHA1: 23be5cb2697e9529f5b34e2e492dd578ba623d47 MD5sum: f484324687f5fde85147cfb3e892d3ca 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1015 Depends: neurodebian-popularity-contest, libc6 (>= 2.3) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd70+1_amd64.deb Size: 367120 SHA256: b7e1d2931afa67175fb579af48064f7d89d7a662668216828f7e380274d11b3a SHA1: 38a8b8874ead9d504d8c9e669aed30d8aedc9ffe MD5sum: 1f53a578695fd2318a7ce3104a189504 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 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_amd64.deb Size: 66046 SHA256: 6943e3e514829289c63c84f6112178c4bf02a24b7b6a31c688839b83aa659a59 SHA1: 904415be370d6ab952e17e040fadd0ef13a611e0 MD5sum: f11926de39d36d36c044fb12e6eb2da0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 25860 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk2 (>= 3.6.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), 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_amd64.deb Size: 7120598 SHA256: fd28a069a8959128cc6fdd73c62e574e36d82fb108a75fb2c58da83a6f1b4ed2 SHA1: b028bdc44d10ff7c50a1ff5ba8d9edb89a7482ab MD5sum: 9ed4800fc4420c787502fb6239fe9a1f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 335 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_amd64.deb Size: 132542 SHA256: 562846639b74b8bce1463ad154b6fcba590ee4a1986df53e6eaddd1bd5495cc2 SHA1: 5787966b5b2ebd6b24ec1fba60e231a07161d554 MD5sum: 193e8daaecadb78e6ddc8d16d9c1456c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 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_amd64.deb Size: 25050 SHA256: 3c49996eb4013724473a25b1be3eb6fea4686dcc16d91fe96e269b2e0601c533 SHA1: 6ac125c2551a0da3c1d54ed4282395d39c4910bf MD5sum: e7019258c29e82932e73662b99f3dc10 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 54627 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_amd64.deb Size: 33550992 SHA256: 14c46371d2a7890a2892e4a98517b817d74131bcf1ee7ec8708a08365fda9eef SHA1: f50b8325ab40d096541727e92b7679e26d0e4f31 MD5sum: 654dcab2cafedd204a6175015d95dab3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 135229 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_amd64.deb Size: 133278650 SHA256: c643b7a85751920a23415de3d7d8d0ce20eeca3d481f759cff80776b935311e5 SHA1: 3b931f463e3d67ee68971ec8c5a86ffddf11cfde MD5sum: 6165ebe2808cbbf2a238a6657fbdeefb 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4143 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), 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_amd64.deb Size: 1385724 SHA256: 3e3d109bc2270fb3aaa50af892e1758c0a833bc2b4142041d24b58f8ec47bb9f SHA1: 2f24ce46104eb364890a38d7b3fb230dfaeb2eac MD5sum: 1cb17a03918c8b97568dc66fb129be01 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 956 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_amd64.deb Size: 223124 SHA256: 966931cea9c2772f2f274e8f28f56862ea3bb2ce7e75b925db29948b5a327135 SHA1: 7823084ce78245027b30988d842a5c2059714e33 MD5sum: 73c8560240dd6698aceb86886f1abe28 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 240 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_amd64.deb Size: 108522 SHA256: 4dc9b2f245fe4248b7731ebe92373830aa4267a48febe10143f4796c10f8b64d SHA1: a9f4f7e90954c88a8770c94d9a197ace214b90ec MD5sum: 622de032380b9e8d92d3c4966dfbb884 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 47854 SHA256: 834ad1dd20d8b12c483e3e6abf0c21a05985bc74575b068ba1d17dcd7392967e SHA1: 1fb9fbf9c85b92721515bc835966e4411466044c MD5sum: 15ea946e8d25cb946d78d24ab573601a 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 510 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_amd64.deb Size: 162808 SHA256: e0f6581849e048ed945b75b2694e777bce205d4f6426cc4c9a6d75bbbff2f3d1 SHA1: e6b96305126f19de17397bb944f8c030d144caec MD5sum: 1a7797365f8b4565e3e3cf6a4a11b30d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2564 Depends: neurodebian-popularity-contest, libc6 (>= 2.10), 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_amd64.deb Size: 1088460 SHA256: feec01b1f8546ff7163191c69f3b5c7e9b63c1f27a2a25f8ee8709495a3a2f98 SHA1: 205cd3332860ec62831b88d9aebfe290023623ab MD5sum: b473835c8962495830c8410aef7434f7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24768 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_amd64.deb Size: 6954840 SHA256: e10673428d66eed72ee862729358551bc1eed1a29d4816ee7c8c05283fcd862d SHA1: 6d3af25d82abc6db4ea9ed5338191ace0d68b84c MD5sum: 7d4c31423de4ab05f2e034a9a86d70bc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 55 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_amd64.deb Size: 29430 SHA256: 988d46cb01ef63b5f373dd756b9e0c550cd90cd55aeec1b4f48c8ef4e09338b5 SHA1: e6f070ab8993ab02d714936df3c8d4f99361e541 MD5sum: 4adcfc104be6d115e60f64aa39e2689b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 83 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd70+1), libc6 (>= 2.3.4), 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_amd64.deb Size: 28728 SHA256: 836e4c8f55206d8ba1f4440c05a7adbdf7582513bdc8561caac85ef475a7b618 SHA1: 3ac001b19c6df3cf304066cbd952a89cf90fd1fd MD5sum: f3264511bd8d6984c73c23c15014229e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 13090 SHA256: 0cd9b3391951f0b54841cc3f4cadf3acd9069f94518f9e9629f75d63340cc37b SHA1: f0450b1a88c93694bd1d23ce2bbb25a8d4a6ebd1 MD5sum: 55e8a7fe33d248c3d17c4d9332f1ffab 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 193 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_amd64.deb Size: 104780 SHA256: 5bb82cd1529f210ae302c4c9312b861a330b5372da585c968c6ed1c14ab1616a SHA1: 96de820425a08fd5fccee12c2bff0ab9ef6485f9 MD5sum: 0dc587ed118bd0d6d12d633e0c8f79c5 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: fis-gtm-6.0-003 Source: fis-gtm Version: 6.0-003-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24436 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libelf1 (>= 0.131), libgcrypt11 (>= 1.4.5), libgpg-error0 (>= 1.10), libgpgme11 (>= 1.2.0), libncurses5 (>= 5.5-5~), libtinfo5, libicu-dev Provides: gtm, mumps Homepage: http://sourceforge.net/projects/fis-gtm Priority: optional Section: database Filename: pool/main/f/fis-gtm/fis-gtm-6.0-003_6.0-003-2~nd70+1_amd64.deb Size: 9886796 SHA256: 80eab41f1452d5185d63e98a373da6adbbe04d47450b6bd4fe979ae6d92b3ab3 SHA1: ca13df9ca5ce8d14d924a039af9ae110bae1e27c MD5sum: f3bfdbd0c43029e9076b200867216f28 Description: package for 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. 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 125 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_amd64.deb Size: 54718 SHA256: 97635f1de1cbc5294f77d8c452f47d4a8acdf8273e8c40c14d7b60fc3a040186 SHA1: fd08f278f6b4b33e4299fe4f641c6d913599c562 MD5sum: e81c4530d02b2f0951d9255b8a5aabbd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 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_amd64.deb Size: 53092 SHA256: 30ed6aacc20b927b7074a2d8b153e2864c06d492e09c543b326073ec99cd8c48 SHA1: cf715c892d54fad1dd1e7fb1931b205182f47710 MD5sum: 97da4024f3080dd2ef891c5fe2670278 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 192 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_amd64.deb Size: 93772 SHA256: 9866fd8e420269aa3f99e970491144190a9f21e9b7ec3ea6a32b58062f496aa6 SHA1: 25a5cf319417ae213b3802495b63cec696bac1e9 MD5sum: 101a975a331b7805340bca4d186a14b7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2814 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_amd64.deb Size: 1258606 SHA256: 85c9b642d88822ee5a45dcb2ea46dce63c6425f51c477765c8409fa5e890983a SHA1: caf926af8aa47e975732629850882a1621820651 MD5sum: faf3dd0f37d9e003292283f47e91d260 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: amd64 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_amd64.deb Size: 9158 SHA256: ce1ecf1a3f1b181277fee1291a856c17bd772c2e9a6f6c7502625572af6336ae SHA1: 0cc9199b7515011cf6a62b7a19939a0533ffcee6 MD5sum: a2666c3baed2a6fdb13bc4b35d6d16c9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6632 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 2386376 SHA256: efa181325dd3454b10e42137c12c733a3574ed8c9cfe10d815b6e5b3f2ea045e SHA1: 5577f285a50c37a50329cedf43065c1dfa1c1b8d MD5sum: 36099902e710ebff96918011825d433f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 181 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 (>= 2.2.5), 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_amd64.deb Size: 55060 SHA256: 355f4069983473e95ee8ea106a75b681d8f6834ac6525f6ffc5a82348c0bae25 SHA1: f9c76ca93b63b84af5f9564c672ffa917f990fce MD5sum: 537eacc7f40107f5427640ef53cd7ef2 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: 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: amd64 Maintainer: Richard Hartmann Installed-Size: 166312 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_amd64.deb Size: 53000596 SHA256: 8080805f2216a629460f3b65242f5562fd0f1ac34403ca0713bb0a1e132ea172 SHA1: 01eba33bc328a2698a427d7006259343f31b4a5a MD5sum: b572f29657b3bba8053a3ec047ec2ed5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 426 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd70+1), libc6 (>= 2.2.5), 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_amd64.deb Size: 135510 SHA256: 0d75203ae8729dbdbc8fe4863cc2f4df1800c6ccb93a7b34da45d70d3caf1feb SHA1: 7c75495dff3565257df62d2449a9210083f6f861 MD5sum: 58c11432c32f4f0d68b579ffee66d604 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 34 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_amd64.deb Size: 16028 SHA256: 7bf2bc7be070c5dbfc75002d462cfe5cd7cc3329679f443e79fb8997f7334311 SHA1: b1684c3941e49f8f9b00fae467061d2ca7e3ea52 MD5sum: 1eac266e1b50f2168bf1189e6ee6a6b9 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: 8.4.9~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 12976 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.9~dfsg.1-2~nd70+1), perl, libc6 (>= 2.11), libcgroup1 (>= 0.37.1), 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) Recommends: dmtcp, ecryptfs-utils Suggests: docker, coop-computing-tools Breaks: condor (<< 8.0.5~) Replaces: condor (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: science Filename: pool/main/c/condor/htcondor_8.4.9~dfsg.1-2~nd70+1_amd64.deb Size: 5372232 SHA256: 85538c60cdc7f40f883e6ab513696d790a2afbba0cf796cad1e6b207df41dc75 SHA1: 723aef7c3a364ca24a16db1d0073151b449a6da5 MD5sum: 88f5fdbc2f0dcf82e82dc79c4edec196 Description: distributed workload management system Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package can set up an appropriate initial configuration at install time for a machine intended either as a member of an existing HTCondor pool or as a "Personal" (single machine) HTCondor pool. Package: htcondor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 34929 Depends: neurodebian-popularity-contest, htcondor (= 8.4.9~dfsg.1-2~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_8.4.9~dfsg.1-2~nd70+1_amd64.deb Size: 33198068 SHA256: ff81182914dc284ff7c8519bc62e17306412a4bcde82533a12939d0c7c233f1f SHA1: 0fdd145f14d5cb6f11b6ea87118bf0de4d6cbc57 MD5sum: 6e2cd1d44299e0cf4c4bbeb8c28f5f1c Description: distributed workload management system - debugging symbols Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for HTCondor. Package: htcondor-dev Source: condor Version: 8.4.9~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1667 Depends: neurodebian-popularity-contest Breaks: condor-dev (<< 8.0.5~) Replaces: condor-dev (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/htcondor-dev_8.4.9~dfsg.1-2~nd70+1_amd64.deb Size: 441934 SHA256: 129bd217e79dd4cad104a0c328703af20244d8d45f63c02cf45acb094535b1c3 SHA1: 7cd141212464c4115d27a21c0fdcc1d6b01985bf MD5sum: f11bfc08cb084a0a610ede68b46327b5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 941 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 (>= 2.2.5), 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_amd64.deb Size: 271212 SHA256: 4017f4a3e56c998b5f276c39ed371cd04b8140907540be37d606ef40aea7376f SHA1: 5c685ea0a27a05eb1a29f22bfecece60e9ca6a2d MD5sum: 8c989e2f0ed79484796e7667374cfcd8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 23078 SHA256: 408ce54522f5db716c99edea2089993436feb23cef17c2dfa7766beea8b76a68 SHA1: 0287982a5f922663215618f48730f7b209f7f7c9 MD5sum: 93df9b567b8a475c135145bc332a5656 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1695 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_amd64.deb Size: 422380 SHA256: aef1eb5a41e4ee486a9299ab566df10bfbb4b8e105cc5bf931091194c33ea77d SHA1: d24ebb95e2c6d2c86f088accab35cab648209cb2 MD5sum: 6f73a32edb13f3083a0dd90e97608171 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 911 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_amd64.deb Size: 337456 SHA256: 047d9d2883828923bf3a1c57d6f04fa796752d2be157886e57c2f9858ba0a6cf SHA1: cea0a7232d2ccf7a9b32645236b711250329ff3d MD5sum: 1a9337d7441395e1ccc1ce5fa6ed3172 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 377 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_amd64.deb Size: 118416 SHA256: b17f570139350e1c638a90ffd2c2fdd7b50a6e4b2285060672e8cec5f81dd445 SHA1: cf572084e1b5b54cabab76dc6a7e0d0d0bdc06e3 MD5sum: 6b75825de98abbce97ff7c6b9fee2718 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: amd64 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_amd64.deb Size: 17398 SHA256: 9b70596ab471f2ab23d987d531483f1af36055bc5d8d4772a5545aa8081811c7 SHA1: e324f022fe2b3482fbf00beddb40146569f9b644 MD5sum: 4a13cc06d0cde6bc9aed2b5c4c837380 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 78 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_amd64.deb Size: 38540 SHA256: 0bcf895f197ed19172cc3998452ef5d7c1b2fea61d68f385557d957a70e09047 SHA1: 3d877f31553b67cbac17086cb5ddc48aef394ad8 MD5sum: 8fefbb087322d3ca99c0d7bd5957c707 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: 8.4.9~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1411 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.9~dfsg.1-2~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_8.4.9~dfsg.1-2~nd70+1_amd64.deb Size: 354724 SHA256: 3fb5658027a6506b257a0ba1237a4816c738ae4774a8120c19d978de3ab6700a SHA1: 4903bfeb58e8927d4c0ed3e7a7879e65e3b7aa1c MD5sum: c47d2c586402ce061fc933f8bb233274 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 928 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 285798 SHA256: c484f6ebc857703bf4786426027e1408badab2990a0050cf378e8c145bcba2dc SHA1: c90f3b0ed35f5a878828ed35b9c812261d64990a MD5sum: 5537d74f0b479018a57f681fc8f33e4f 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: 8.4.9~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 627 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_8.4.9~dfsg.1-2~nd70+1_amd64.deb Size: 245418 SHA256: 482e61c3d394000990f4109a11ab4d9af102aa1fea2ffc83f4481b306eaeae5a SHA1: e52bfb3ecdacdf00d81aad95700e2847189dc422 MD5sum: 9dac601aae7f38720836d3c76fdea11f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 321 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_amd64.deb Size: 104632 SHA256: 3f82e5a6da76255a44ef9ccc250a362e5d62ca06effa487cfcc951f04a45de8f SHA1: 6ac588c955f689ad77b73c11ecf2dc94639209ab MD5sum: c9565b934e40eb3947696d3642af2ec4 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: amd64 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_amd64.deb Size: 28434 SHA256: 7c3ea76b6b1cb287601c98346470f9606777203d80d0f703a9d701397133f60c SHA1: 90dba560906627292fed3d14708ccbd01bb54e7c MD5sum: 26edea5972500a6bfa682dcba5b933a1 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: amd64 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_amd64.deb Size: 7116 SHA256: 1e11c37aa39b18b267ec0a22fc1558345abc35d68987d3d8eaffdbb1731577fd SHA1: edba98ee173c4443bad08c28fd68b11e79916dc6 MD5sum: 4539e55d0bc18e29412b313ac19ff803 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.2.5) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.5-1~nd70+1_amd64.deb Size: 7178 SHA256: b1b684b8e5a00c74daf03b22562de8f62b848351dfdee21b6b570076d6aa35fe SHA1: 14cb91c8f0ed5205f37622adb930c108da3afb05 MD5sum: 3a98a1ec607005792cb722662ffbc0ef 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 118 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_amd64.deb Size: 104628 SHA256: d2edb1b51d9d9e5b9bbfcc56fe7845c0b1a327c671d14db0d2d6ddf368ffb70f SHA1: c65328fe944b42fa12ed7c557661e58a5426fcac MD5sum: 94e348446180cd4f67d5032cf537c229 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 200 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_amd64.deb Size: 59088 SHA256: c2d84e8ce6d060d1f82a12dbec51ca4abbe1e3d5e511cd6fc2746c29b1a684cf SHA1: 045b6f940d027c5e89028b6677c841364688dbcd MD5sum: 978633a4eb5b6c3345c2e74088e4379b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 75 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_amd64.deb Size: 37868 SHA256: a869d253ff12e232e85020270bb21f60e9ea58b6b05d11eaa7db40ca6d22cd12 SHA1: c94ebb3ea5b115fadf63263102d75e5a4c2db636 MD5sum: 663430c42328fa34a3cc4f43ffbde146 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: amd64 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_amd64.deb Size: 43592 SHA256: b9ed91474f944d36ce4c32a19c86395a334bbcb53810d2e8bf27e345d4d91a75 SHA1: 1d54cad3a594b00e71c63d0bc3b504877c64eb1b MD5sum: 2625bc1927e69418f5178569a2ed05a8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 66 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_amd64.deb Size: 35678 SHA256: 4de278f86722f70c73e28e6de17b0994340367a5af09c8bfd369bd1c3c7d6c4d SHA1: 1011317660c481167f8fc3f2cd5f664e4e742c29 MD5sum: 11c462aea8bba5f7f3966e2bba5a6d04 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 73 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_amd64.deb Size: 64094 SHA256: a7a9aa3d793255265cbc76f50946f235c12ceec4f5aada9d9035e4fd760d2aac SHA1: 3a32c6290c276c60a4507509fdbde3db1de72c8b MD5sum: e1abd9cd8085b59a3294625b7845a4b9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29 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_amd64.deb Size: 18998 SHA256: 0c6768e4e88205c8ac7bd3d32a571ab88ed0a2991131163134693e9ab0df048e SHA1: 173c8ae845418e377c6a14a4757024908c9da8e4 MD5sum: 99ff79c80af866929fe2461bf488ded8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24 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_amd64.deb Size: 14990 SHA256: 3ca056758eb752f400ce3e498b075b32b5560aeecb4bd8a6b5203287191c6106 SHA1: a9d8cf91b6055ff7ff7e44cd5a233b22ef7f1024 MD5sum: f11364b55608db2d0ce50e9a2d684d84 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 76 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_amd64.deb Size: 33438 SHA256: b2847b4ffec34d3a152113d7b94b95e963adfe51ea8ec0bf2a6ef4093b69b0d2 SHA1: defa9fd481f8f7082f3c761be3787f5ac322a100 MD5sum: be6a39e8861765ddd1d58aa781c961b1 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: amd64 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_amd64.deb Size: 22434 SHA256: f7637b0e52661b8441133d6925c47def9eca334fe94b794a2d91bef9684e48ad SHA1: 2c9709328f5dfa1c55dd362c332c7638d3e87731 MD5sum: 5c9256c9af42dfdbf9d8c991795fbf68 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.3.2) 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_amd64.deb Size: 45012 SHA256: 57ed4a80b199995c051f7ec75e4bd13a053b445714cc86cbbd46f94919bbf01d SHA1: c49e563b9ce3a5036db6733d17c5294187a37389 MD5sum: b2f1601746465bc19b1cb601dfde021b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 167 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_amd64.deb Size: 141626 SHA256: e468d27bac7ec9ce64199276604e9db4e26fb476f9b6a79d8332936abb941c5e SHA1: 60e5088b5a1919d66432776737a1958ad4d83efd MD5sum: e9bec57f87b66369c7b1cb71afd6ad26 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: amd64 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_amd64.deb Size: 509864 SHA256: 9d12cf00824b926884b6259eea04aad3c85b603603b490a96d0ff4ce45064756 SHA1: fbce8e2f0c2bcb9306b10abf8d53c2fffbc36fca MD5sum: 28d181ca81e4c367057b63a98f8761d4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7668 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_amd64.deb Size: 1318766 SHA256: 5c1150a35074c5e04a55ff76d1d3ca294301e724d9e041e9fb5b86d9211d6ced SHA1: 3056594064153bb5469e27728ea740da25096cd6 MD5sum: 4b530dc6d2b071aa41239a72e0cee722 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4625 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_amd64.deb Size: 1101074 SHA256: bccd5585424f3f555842a785001a1d4cb81481bc327ba9c8eb8a415d6800263a SHA1: f0a8f731d1f7a3e374f741e651d998a4f27d3444 MD5sum: b56b0a15f23b98cab71767390e76ea16 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5075 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_amd64.deb Size: 1090392 SHA256: 01dcc472fbef67f2c3531a2b1775983177f924a395d64745618b08a6d4ee87e2 SHA1: 6c4e56b9fdda6d3e18665939575ccfe4dd088a4b MD5sum: e4edd53e5a463caed9185425e3f26ddc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 288 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_amd64.deb Size: 85458 SHA256: fc13598b5208aef5f5da878ef45ebe12260a9ab22542d40dcadd52269b859c8f SHA1: b9777599491248dbd93a45241bb57030a5b2dbe8 MD5sum: c6760f47694fc5beff797caee3102fa4 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: amd64 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_amd64.deb Size: 9190 SHA256: 1fe6967728972c096f243dbed895cfa3fa291e2609fef8ec3059357b01125fa9 SHA1: 7bda5bfec6231d0eb34aa14a6aef7a31714d584c MD5sum: 46266a9cb718cdc6d697a2172cebac6c 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: amd64 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_amd64.deb Size: 21608 SHA256: d76b88438e53a6d85e01b95cd35b0cfa434d489b2806f25f0c8218f747469709 SHA1: 3317c66b47b8703d22f069f20870bf31f99d83df MD5sum: 765ad75902ecd1da5262f3de93f26e72 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 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_amd64.deb Size: 37326 SHA256: 9b9b4ab0e3b082ae8cad872a1f1b64d9dc7080bcebde303f77c8b21f7e4c55e5 SHA1: b98c27ea41b699387dc41b17d8cbbc39d1d4034f MD5sum: 16d2de34d4596452ab503d083fdeefc8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 158 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_amd64.deb Size: 50168 SHA256: a9c3045f7fb23e028c39fc2ea9fc0f1e385e0dc40310eb801d574ca779282034 SHA1: b328cdd298bcec490c5b329905315915a32c41c9 MD5sum: 05d67b47cddbc617180aa5578c5d22c8 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: amd64 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_amd64.deb Size: 19770 SHA256: 49e0f5a48d6a13bb15ea6429e7830b1b027b9487d5de5f77a29ef7218fc6b5da SHA1: ad0c3299900360cae38db590fe3b6b90dbb4d033 MD5sum: 0445434c686809a61771fae14c37878e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 802 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 215642 SHA256: 469da38ea2fe770668a4da33af5377aaa0754a41da1cc305753a3324e35c2c65 SHA1: 714853b4df5b9cab988ccb2db1bc0b586e5dfd01 MD5sum: 555bcb37c448b89f1f7fcf1da7412188 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2169 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_amd64.deb Size: 533706 SHA256: 4744ae089d8c0517e9a30e06f321171223e329d195a4e855375e1374fba34bda SHA1: 76fc35326e58936043e6c29c7d6edc18b14d07a6 MD5sum: c76109515596cf0059c53cde25ff1bb7 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: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 650 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 183544 SHA256: 0d876aaa23812e4f9deef0c811a80da7c48aff1da4ad32bd892469e44a1957dc SHA1: bbf9a44448d0de7a762013201a56586c5c75cadf MD5sum: 53aa6d5ea36c16562c1a57cdb8842f44 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 149 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_amd64.deb Size: 41050 SHA256: b42b58d0bf3125e0d092b13b6e8895959d3ca758a776ad68e1f1f75d191010b6 SHA1: 6601359f829eb6211ad83999be815b2f82e69da4 MD5sum: a01ac1e09bcc416e96959da36bf6e78a 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: amd64 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_amd64.deb Size: 153184 SHA256: d858c48eabe2b6c73291897479415378a515d3fcd5fe3d3a5910f761bbe84531 SHA1: 7b47290310c401a1d5ccd2a06668234a0958905b MD5sum: 89cd0a5eea2cfda2152f3113c76b6f8f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 573 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 164558 SHA256: 512798738909e8061ec2ac8ed282074f2ff2eef5d37fcd34bb8a479eb006e326 SHA1: f670d8f8e974dd751c91476af5ad07e1e72e98bd MD5sum: b2a2202b632dac1665b39deed186d23d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 122 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_amd64.deb Size: 33016 SHA256: 1546075ee0ac306518286d26e1b622a641e4e2944ba0949aab231f60bdcb20e1 SHA1: c796caf0a2f82518f7c2e959bd213b5ba595914d MD5sum: 74c5afad0329fed0c7c08649da17fa57 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: amd64 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_amd64.deb Size: 8798 SHA256: d8b0d591b7f0cac49ae8bd93c8f5a7ca7849dacae294f05737462dc914d2a015 SHA1: 444dfdfad03400ec28214b4dd4b46e6cd726ae60 MD5sum: 0829a802b32c527758902532e8e24c5e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 430 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_amd64.deb Size: 107196 SHA256: 5ba953545f4fa95cfbee7f10b55c410cffdda7fe7ad43b0fb97e1b351a36f80e SHA1: 485a5e2b72459b2bacfae9226b6caec6fc648c9c MD5sum: 7c372782e6fe46e4c143d684fce927d5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 183 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_amd64.deb Size: 67814 SHA256: ab81ea157fffbefef5cb799c3a938a55b51c5f2e75395f01a31450fcde17a41f SHA1: a7a6681e23a8661612f5e5df70748acfd3a0cfc2 MD5sum: 31ee5c5a2265b5f877b7ffc98fb234a5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 109 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_amd64.deb Size: 37898 SHA256: 867d57435db0b8617981622a9a735684ae9175922840c4e82b8f1147a1af2745 SHA1: da71a15cfdcc493d4c16b5b7cd5b59bbc6d61800 MD5sum: 140b7dae43e8cf564b38f4672713594b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 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_amd64.deb Size: 27156 SHA256: 225001bb0130fcbe8b43f77a17f0df8ef27cc895ad872876180922adf9bb25a8 SHA1: d27dae4a21554b64a60c43bcf0549bebbba4952b MD5sum: 58bcedee78c4552965c4b2d9d7778a82 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27 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_amd64.deb Size: 12584 SHA256: 2b66bab61346348e647972dd954bf585ec46336ac38056f21a1ad04b7106a0e1 SHA1: efd0018bbce18fc6fc835d503c3aebd5ad6f9a0d MD5sum: c674eb5510cb078d31f7c9dac578dea8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 214 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_amd64.deb Size: 45488 SHA256: 68eb1230d768fd66378b7cf474ecc6d27c2e53f3dd2fd7e72684bb9eb27d73f7 SHA1: 30c807ff24c6a963fa78c5705b999b898ad641a2 MD5sum: 0a9aabd964bc0b2d4ba6b142a37473bf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 18996 SHA256: ff66fd48c04b00670f263d5665f38a48abff7746fdecd4198a7ecf1d41fe5250 SHA1: c15b6001d1f4841b65dddc3073eaff902e2a5ed9 MD5sum: 8234d3926e3b325e0e6bddc639c6079a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 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_amd64.deb Size: 26896 SHA256: c155f382dde1108480ade88b500c3c07ab3369a3353b527edf6ed8d2e7a3bfaf SHA1: 2b48673890d9a74ee307b0cf14de0d8f871635a3 MD5sum: 188fdd5c766cbb4a3f769d3308c12aa8 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: 4.5.0-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 26927 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5 (= 4.5.0-3~nd70+1), libjpeg8 (>= 8c), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtiff4 (>> 3.9.5-3~), zlib1g (>= 1:1.1.4), libgdcm2-dev, libdcmtk2-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_4.5.0-3~nd70+1_amd64.deb Size: 5456748 SHA256: eb41be39f2ce918738d622b1543913aa1bae8cfbd676e4e59e589634a7e155ba SHA1: 1c8277069a3e2a77c5aa04dd6d1fed36e7250889 MD5sum: b562c046a4e98e0c55fb16ee8845784b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22235 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_amd64.deb Size: 7285294 SHA256: 9bb45e9cad5b6b8689ad5d4f081079321a62d7109dd0c6335ea25db4705136ac SHA1: a1e39e2e995bded3b3f1ecedd5cb18e8ba0f2104 MD5sum: 9632194c6a8271910e8e0daee2833fbe 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: libinsighttoolkit4.5 Source: insighttoolkit4 Version: 4.5.0-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22179 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libgcc1 (>= 1:4.1.1), libgdcm2.2, libjpeg8 (>= 8c), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtiff4 (>> 3.9.5-3~), zlib1g (>= 1:1.2.3.3) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.5_4.5.0-3~nd70+1_amd64.deb Size: 7176938 SHA256: e7d982b3fe0d27c1de31d394dbcaeac007f1ad4801b682a3bee18665f0baa2eb SHA1: 344f827288050f43686682bac31178dc83267777 MD5sum: 6950bbacffd57ea5f99ae557f4531c49 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 495 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_amd64.deb Size: 135150 SHA256: 043c5d8e54c50c2876bf02977b121fc34eaaa25e720a302d7f366eab7feb7aa0 SHA1: 607c81ee412b5e180d1d189474dea5ebdf994e7a MD5sum: 2d08ad46d7b4036e2ddbc1027fce8d4d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 246 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_amd64.deb Size: 103096 SHA256: 8fae6fef66a0363c8c4348eafa6cf13b7d16f72141bb43d80d80bcf71f3f90b0 SHA1: ccb6b675840a86b198722ac2c5a523a78c742a2c MD5sum: 0a2999c095f7bd3271872b9310dcf085 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 101 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_amd64.deb Size: 37386 SHA256: ba34a3f5c5fdb2fd856837f4a21b3a9fbe9cbbd0bc1308b9798a6dcbfeb8f4fb SHA1: d0b013a49858d56cfec2d108dc181cb122343f30 MD5sum: 6368a5234d630d24a4c1a7d20848dfe0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 60 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_amd64.deb Size: 28938 SHA256: 54b77ba727f96f4393fe6e5267c271530dac52ce50edf0a20a9c2f601b740911 SHA1: 51289462739b8e8c44bca45cf95013a93f7402b8 MD5sum: 1cd238c9c314d4075842d269ce0a42cd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 301 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_amd64.deb Size: 78916 SHA256: 5e7d8b34ee875950b86db2e3cbd2bce9954a54d7ca27f87cfe4f72c76408dd8a SHA1: f4c7f2add605806166d9fd72c1049362f0d4986e MD5sum: 3c4930c6d8512a284fd899ada34d43db 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 255 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_amd64.deb Size: 190190 SHA256: 94fabf06a59fccebc2393af51b00b535a22b6911d5dabbde4d807b0f5da9e045 SHA1: 8202e1460e43761586715f8cdb74b57dd7280685 MD5sum: c01c9ad2e377e8280799db669f92bdc5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 119 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_amd64.deb Size: 51612 SHA256: e4a8e5a773aca6d9ff954c178c2af12493382ce390e39ea920a494acc5784072 SHA1: c264c869a27c757026a7bb4eca4037a788e7d28e MD5sum: 362c9dd2c59fe2f2193541b91c215387 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9875 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 (>= 2.2.5), 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_amd64.deb Size: 2019594 SHA256: cdcafe66dd15c461a2729edeb8c576d48e2c7851ef89cfab489fd1ddfced9393 SHA1: b1f67caecec61424ed12e4ec992f7d1c03bb97f1 MD5sum: 43729e2dbee8c7de1dba835c87c60324 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5602 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 (>= 2.2.5), 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_amd64.deb Size: 1459852 SHA256: 8c2acccca750c8f3eaf4fe0d731df4a4fdd413adfd3f1474f6dec1daba0f5de4 SHA1: b2ee68c5d832ecc73abc72e937c703518f23ee4d MD5sum: 4951b4b7f40ae7256669a41dedde5026 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1414 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 (>= 2.2.5), 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_amd64.deb Size: 371354 SHA256: bf0e86c60f5afb37972c9288c23f8bce8d840764fa8dac36955751a4a6516128 SHA1: 45780c7dc372670244e5190d46bf8bfcc9c5161f MD5sum: 7a94ddb3a274e1d32dfe1ca95fe9d563 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 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 (>= 2.2.5), 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_amd64.deb Size: 48828 SHA256: c67b545cc531d7bda63c31b639d8e4d6489de01d0372cf8dfd45d22f31920933 SHA1: 6888db247f5fd474e1fb39f24f81c8c1e6c94ef1 MD5sum: c12584164ff4e2cf63435f53322009a3 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: amd64 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_amd64.deb Size: 2392 SHA256: ae18b5e17e9b254156d3ffb73fdc17c8abe7e9da8d32a5408930a6c7dc7037a9 SHA1: 352b39d8b8b6a630b1dea50de1ec6d89bf41eb07 MD5sum: 30b0c24b2f9a2c1ac9b8557a5ab47712 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 145 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_amd64.deb Size: 54376 SHA256: 25aa09e49b93c8e306d3cf6fe7a3e2fa376cb1a39304b1944b3129b7eee5f14d SHA1: 9bec70ba1a28eb6562c376f097085683f527fd28 MD5sum: 5cee97a95228cbc6b03adf60abe5be4f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 333 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_amd64.deb Size: 122690 SHA256: 76d45f284f3fd61530546a5cb9202c5043d150312bfc6542246b5850a9bedd03 SHA1: 7ddee15e9c74c06b3dcee67f03af9c4801a491e7 MD5sum: 1a04d1cab0226f858266d1b58d10baae 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27157 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_amd64.deb Size: 4120244 SHA256: fe6491ec0e793e627958182242a2a30558a53c38eef8a44d9aa465b8b4e36188 SHA1: 8364118fc3f37161f72ba44730e02b8789bec0c2 MD5sum: c23158e6478a6dda27cf133cc69a6708 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 66016 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_amd64.deb Size: 58870808 SHA256: 5d9c6a87ba67adb17da2f8ce64fb5d2f8ccc4bba98e83dc3be5825a547a50107 SHA1: 7d7727f7ec52b06f31da67068c5b3f73e0e9e71a MD5sum: 960c2c97ee10ea48e6bf4d5905ebb834 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: amd64 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_amd64.deb Size: 177490 SHA256: ed9b5a6c3ba7be1a158c749cc92132f3f04a351b79406f765bea873222687b9a SHA1: 658ba1255ed9b6f9a76fd5acdc0dd5c690f6042c MD5sum: 8df313fc3f3fa090da64715b2135a4f2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 449 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_amd64.deb Size: 128252 SHA256: d5321b988d7d17a9a46b3b13da9399d9cbb70deffa4a30f59b49203a146405a7 SHA1: 3aea893d43f85d11da539979d37b32d418f00e02 MD5sum: f17266baa97e0e91c0183cafb9cecfed 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 57 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_amd64.deb Size: 22914 SHA256: 91fbec0f26dc51ba9a11c1c03c41d281651fb3ce870eee5be29bb26eeb18ee84 SHA1: 43e30fb98acf4b50d43a166b57b5f64cb3497312 MD5sum: df0c4e6c285cc1cfe8664e2d9643f351 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 77 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_amd64.deb Size: 64980 SHA256: 71e86e591c088b48bcde31e72d8138052ff1f6e678b3588990aaa40c0d9649c2 SHA1: 4dd0d7c2b4592368450ebf2d97c9eeff1b93f6a8 MD5sum: c0d66b4f737115c5424f5618effef4fe 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: amd64 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_amd64.deb Size: 5570 SHA256: 3e6a6093b56abd7f811c905b83c99d29c9ddff9b1e9c3d1a241f98cdf2f4d6e0 SHA1: 2608f9ee849370a6fc1e296c25c6a342721d39db MD5sum: d38ba8c402370b532a21ce89496b2add 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 110 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_amd64.deb Size: 45304 SHA256: cd44cdbb087c1c2b1461cbbfb63427d76b73d8b8dd270bbbb25ff55d95380e5a SHA1: 2f6323c122533988a850a78cc9e09495516dbc76 MD5sum: 64abe111633f6316aa32de5f03019d2c 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 581 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_amd64.deb Size: 171594 SHA256: 7b377a7b28c93315bdc89b0d3c443e610e3a8821ab13c07cc8390c4aba72950f SHA1: 7d1f5bb536fd98618baa1e54c72aa962e155d38d MD5sum: 75e221550ed77551c78f08be3c51842f 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 307 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_amd64.deb Size: 124582 SHA256: 6b3a25c92f9cef6894bcbc0d299d62be66c71f28994aec1b592b5d36e58e80b0 SHA1: 92c5af35f11fe5ab1dc3cde4432f5bfa35825daa MD5sum: fb8efc6c745b32e15e98a6cae926b9d7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 594 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_amd64.deb Size: 209886 SHA256: f0ed5a289cdd8e800c4f46f2bdacb3653dbfc1be3cd96d8ed19eb719dae37250 SHA1: c44b106896a3372c5e76234bfd457e940c513f33 MD5sum: 62d33aea72e052a7d155d1a0e978dcee 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 134 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd70+1), libc6 (>= 2.2.5), 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_amd64.deb Size: 50480 SHA256: 81df46469626eb13fa5d633f6d7cf08cb793c0a28db1a681bb97cc62364e2834 SHA1: d42d61f8c595a73afdc2d13f4444e7999ad7558f MD5sum: 74ac73b6ca7cf7cca12b04aca9b5947a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 435 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_amd64.deb Size: 189974 SHA256: e7e651eee22ed7a218aca33e070d04bf318706d19c5d4a360e98b8171d294917 SHA1: 27895cf54d4ebef28a265660d175b91f1a41de1a MD5sum: 199ed3be8601103a5515d700fb4d4737 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: 1.8.8-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 23080 Depends: neurodebian-popularity-contest Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.8-1~nd70+1_amd64.deb Size: 4511652 SHA256: ef807fc500bf9606046dc1561b635b07490330186f63b07a399d336af0a730ed SHA1: 092222cac5c7644285c8a4dd749f572358ba6a5d MD5sum: b234902d0dda586b4acaf8cfce57c056 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: amd64 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_amd64.deb Size: 42574 SHA256: edb2c179742df10e47c5529cd89af0948271294629a0a4763ae834bf0c18ed50 SHA1: 0cc9c3de65126a1ecf2b43174a5dd9aa98d07f61 MD5sum: 1faf21b27a88956f37f2dca7a422a096 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1779 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 266080 SHA256: 8a691f73fca1e801ed17863649a177dd9f481ffe8dbb6534de298cd71ae925e4 SHA1: fb4d437654dd0c7e4f275af9de3d247c96092dae MD5sum: e6b4db0cbaa8df1103508dd63bab2fdf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7677 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, 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_amd64.deb Size: 2011530 SHA256: 81fe81a084fec7bb56fcc48c436e4e891a0c16ed2d1164e62fbc7a976999bd91 SHA1: 4f56a5881c6e131f5bd7a24e37732608d8307597 MD5sum: f5eaa9fe5b4bd989143a46cee5420cff 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: amd64 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_amd64.deb Size: 339176 SHA256: 8d55c134a9124ff8bdf287425a9ab7bc3739333fbdcb29f94e2892362ae92285 SHA1: 673bba2bbd53aac744195273d134f21467b464bf MD5sum: 9ef36e508b012cc2ab6b58628eeac371 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: amd64 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_amd64.deb Size: 19256 SHA256: 3031f72882419f0bba7e947a18525a58e373c2cacd64d83bf533001ed56ccccb SHA1: aa7ad2cd23740b63672281760f9df6570ca94d3c MD5sum: 4a3edf0f9052c8a97ab281abe3a3c893 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 307 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_amd64.deb Size: 131490 SHA256: 1f6d9b7f3ff7ae51773fa6bbd9c63a43086d74b7cae2667ecfb1921086fb7670 SHA1: 7de84ef3113d4fb68ae3d766615b1ba221478b24 MD5sum: 96a22cf6352ad6f9462e533c73a82224 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 7792 SHA256: fd0540e8e09f8ec8b4f042032b107a65f506c52a9ec0e982c92be0f9affd3b66 SHA1: 6bf5ae5b92a7138626e6484e649f6d8357435f90 MD5sum: 2d86a22ab20cb9cb160e320a13e0daf9 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: amd64 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_amd64.deb Size: 12600 SHA256: a12d14b8b6725556fe36db24d90cb0ca61525ad21dd14c0c5235e575b478d849 SHA1: 1461872afc86c1462cbe64684cffb3dd8d7e6813 MD5sum: bcc5f3b28fbffcc5450b5fc0cd43d365 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5) 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_amd64.deb Size: 31184 SHA256: 5cb21d5d22780c438cb371f0287a238a330dd2cf54591b6559ae2f8b3213a192 SHA1: 9aa1d3347cd23c923b78a5b95354f0ff4b8dc6bc MD5sum: 6909e1084963448af461cd757243a098 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 41 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_amd64.deb Size: 36504 SHA256: e734a37b8c13f0b21fde39054b56bbbe3e12d46a3e4038b5cbcf268b8abdac4b SHA1: f571aa39a5b5bb7258f3827e4c4de0cd4a1b7032 MD5sum: ce9f939e354e6927194126c8e97c56ce 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16571 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_amd64.deb Size: 2758284 SHA256: a7278b487e1a7f8be2c14b93575e4af06c59e48e171d6b39af8bb3dfc47d7fb0 SHA1: ca0eef589807b01c0399b4fde7bd38711f1ab89a MD5sum: 198b464ae98962a69da45ffe9918e6d6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5456 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.3.2), 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_amd64.deb Size: 1579418 SHA256: e312c308fedd2feade89316fa5221d7adf3370374bf5de523a988cd2b4b8b727 SHA1: 61bf9084866c2334fb40db46adaa023721d58e36 MD5sum: 2a22419cd27daa66f15efc778e600cd9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 111 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_amd64.deb Size: 54792 SHA256: 5c1a87e62f4ad0b0f7f25b50f1d6ae72265761448952335b3a969eba93f51548 SHA1: b8d2c15e31a223ca72bae239644fc4435253d293 MD5sum: 170a2a8f0d5e6b8877874269299eed95 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 298 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_amd64.deb Size: 112634 SHA256: f6ff1ef5139f27685a24806c7f3c8fcac54f40fb7dbafc86932b96e27cf3f45d SHA1: ecb6143a805bd5657c23ca97e14db411dae54b36 MD5sum: 1dddcfcc4762d432d3763fdb68de5d6a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 245 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_amd64.deb Size: 79158 SHA256: ff66ae6ba5d5efb7432fbe9083c26a969d102954eede736181f28ae4ca56eeb6 SHA1: 99657e66e2923ba4cb9888e0c499b2616a401dcb MD5sum: f61f2c5147fce3c00a495e137f9fd83f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 969 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_amd64.deb Size: 212220 SHA256: 44b0d7f45533514a58d18da7477f8147320d23d1ca2e2da513ca0638c84372f0 SHA1: 279054de6615f664af82030520218d6bfd1d2d22 MD5sum: be7834dfbe616b25919944ea6968072e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 568 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_amd64.deb Size: 172346 SHA256: 9006b22186b7f0e8cbc4e3914bd7bcb674379c3b8eaa01b69066eae7749a8415 SHA1: 69879a36111156fa87c5ff68e17d904d9487bd71 MD5sum: d2fc837ccadee5f7581304f29ad60a77 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: amd64 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_amd64.deb Size: 112336 SHA256: b76980c9c821e27eef4459f2c25f0e38673054b6a32713c559150500138414ce SHA1: 345109c639a93c47c5b850df249f7ac7cd6a47aa MD5sum: e04b6b33210f57653e93675b3a19e814 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 99 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_amd64.deb Size: 43890 SHA256: 1d22c181987b1f01f26384371eabe56e1bef0f57a632a65ddbbf9888a34fe0bc SHA1: 90cc62aad7bb4225106dd18dfc151003a256ad35 MD5sum: e5b6faa0aafbb1cdecfb41323fcd3598 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 100 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_amd64.deb Size: 89120 SHA256: 643f03c5083c8242f271e5f37a1a7986020b181a6b4c2024c7107d58833123b0 SHA1: 40c44d9741da5de735c552e3ebe060aca91013f8 MD5sum: c8d7b93809d6974f8266ac1412a62fdb 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: amd64 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_amd64.deb Size: 218312 SHA256: e2c64f9ab32628f52da98f7e959436435b8eeb050e6d7aba718c2f1fdf9ea038 SHA1: e212814878ef7949899e99aa05e51b5c93fe0b46 MD5sum: 4ba1b79a9a3682478198d778ea0ef38e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 585 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_amd64.deb Size: 232324 SHA256: 207a26dc84e865944ad5ede80d98f46629f66d1a2f4d2d5aa69fb8609fcaed49 SHA1: 262e5f1720d08bdf3bdb4ed7c4b3370e8a2c4d50 MD5sum: 7069f631935755d5e71f4e2693aee38c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1422 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_amd64.deb Size: 492400 SHA256: 158b3511b781eaf2b92acbff2451b966dea1824c104776a34027bedcd5c5ea3a SHA1: 098fa7e6edc42190c8170ccb7fa3c5e07d06fb7d MD5sum: a679028df66cf8f8fcd5be66573d0696 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.2.5), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.8 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd70+1_amd64.deb Size: 45272 SHA256: 3513796292700a425a2b8362c427e77a897770be3df11dfee591f5443793eaf7 SHA1: 4437ca8ff320cfa4efd5a533bee3f6d8bb03141c MD5sum: a24bb9c5c88e221bac269801a305c63c Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1730 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libstdc++6 (>= 4.6), libvtk5.8, zlib1g (>= 1:1.2.3.3) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd70+1_amd64.deb Size: 582432 SHA256: adc3dece73e45fda60858eaa72a71bf2a1fd3f4d20d1c044a7338ea8c7061b90 SHA1: f11b0b78018282e50767f7c33c5b3cd041348f7e MD5sum: 8a4171ca45bc7268be8127d9d0c8cb30 Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 530 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd70+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd70+1_amd64.deb Size: 107146 SHA256: 2a1f09abc0c71f4eebf249f497599a7bffc6dcd72b4b9010618ce5a045f9914e SHA1: cc0da88b668f1082038c8e99172f2d7c43f84275 MD5sum: 69626ba916417ecbd25edabd54597fe8 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: libvtk-java Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10911 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_amd64.deb Size: 4911660 SHA256: 68229a9bf87e3a1b9799f6ca833ed4bc50e6bff78f0b5459f2d5f37adaa965d4 SHA1: 63c1b0a65daaa2df22b45079c1a88bca460e4b78 MD5sum: d8c8e0aa2f5e0c6e630eca91a5dec181 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12852 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_amd64.deb Size: 2565214 SHA256: 13c1ba8002c22cd09b24bbff4334db11310c4fe26eb8ce46c7c85eb1ae90bdf8 SHA1: 83441de1304fc5cb4136fd128b1f601274a215eb MD5sum: 2581309d3c9ac507f18bed2d8075bd29 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 549 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 109450 SHA256: f8a5d96cd72c4689d152150c988da0788fbf7a5f8f03642744d33b6a51b97cf5 SHA1: d4274d37e0fda0b58d5f54600cd1a248d2f8a7b6 MD5sum: 2918cf3fce1921511fbcac4acc8173f9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47808 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_amd64.deb Size: 15257918 SHA256: ed0323761444227f6664e788787b82249dc87fe12f4b55d6785bdc8fb259e472 SHA1: 71433fdf990dc407df7b0f4acdbcf6eeb3263897 MD5sum: 67a046cfe213ed96361d228646b5cdd0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1360 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 484074 SHA256: 422d8109b5f7b7b0af999c02a9568d0e03070c42e4202466d109bc76cee92c8a SHA1: 9d54d7d16173da33685bbb978b2bc229d343b656 MD5sum: 282bad631a4e495636f5ad980f6ca789 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2576 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_amd64.deb Size: 579548 SHA256: fe872441d40d78d1efc213bdae5878c94f5681d3ab4aa808e19df6b51c3b6551 SHA1: 14b80f94f069544748294e560b005538dfebb24e MD5sum: b4046e97014c4cd91cc15e2e6d5d0160 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 759 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_amd64.deb Size: 315352 SHA256: e8ca90b1c59b172f8d62097b46bc22b9f510724e549a5d4b9465861485cfaba5 SHA1: 1564b9cb49e01bc927b074cdc0b234a4e847f007 MD5sum: 3dd895590baa88ca97268f43a7146892 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: amd64 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_amd64.deb Size: 27776 SHA256: 12fa076aecf2cefc865ef21c27bfcd3701f6dcf432c82a8cc68507a08e3b73f6 SHA1: 9f6c4dd3b896bb19869a371c2c09adbcf1dad4bf MD5sum: f40cbfdc1f04fb44b430421e0af72b12 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 79 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_amd64.deb Size: 42544 SHA256: bfc34faa9f7af89d20e60b8e371a2e1c6a7ee0a5725f232141f7d65d0cc1a553 SHA1: 27bac77b653abc13c477dff836950cca4f152fe8 MD5sum: 9f08c8270d74247e9d090ca341ee2adc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 71 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_amd64.deb Size: 61922 SHA256: 9012007e5d7c465db911773f7fb8b4e465c884576555f0132ea94a3bdbcd5e25 SHA1: 4b9f9ff0afd69fd137d51301d1cebd5b74c3c443 MD5sum: 3d5eb6cd54918ea7762bed10926da8d2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 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_amd64.deb Size: 50542 SHA256: ab159ede543e2db2b003e88ee3a423e81e3f1a32c4e0a5b0fea26ab11624cedf SHA1: 2617ec2a0b548082813d4ac1ec0784f5f2394e18 MD5sum: 33c5d7fb35de0a9100eb2120979c24f2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9273 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_amd64.deb Size: 1593278 SHA256: 985ccacc596ccb1330934c862e32ad10c1ab02d9e1dcfcf5e7de6a4026aaf31b SHA1: c78d3fdff23badc95fc80d049625b1bf1c91fc33 MD5sum: 55b2940005cdeda9181af8fb09ed29ac 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 28088 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_amd64.deb Size: 25359208 SHA256: 3152942c7732c96322b929e3e9d1b74e010f878fa3c29127334b290dc68ef1e2 SHA1: a933a75afa4ecdd04009cd5ba367b3fbd8022728 MD5sum: db2ed21a40e445c41b8372b4beea323a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 183 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_amd64.deb Size: 82930 SHA256: ec9be005dbd4d98cac3c3e939e289162614dbe8465afc41bd16b8748963b1729 SHA1: 5fe721e3a699ac35a40dbc7ddd0e8832bc106741 MD5sum: 909607d9a649464b574af67ffcbf94e0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 205 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_amd64.deb Size: 178442 SHA256: 8c7327cb97ef033cd6daf733c9cb3435ff9704ca8588ab876c2924b81a31fc45 SHA1: 3973e2ed2f13d3d2b9acbb37b84fe4ae6f702565 MD5sum: b8c6ef04dee9fc98c5b76a2c8a99e149 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: 1.8.8-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 7300 Depends: neurodebian-popularity-contest, libatlas3-base, libblitz0ldbl, libc6 (>= 2.11), 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 (>= 4:4.6.1), 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_1.8.8-1~nd70+1_amd64.deb Size: 2443072 SHA256: 65702ff050aacc56d8b5bf6591438c4e4d630134ebaf41407f87c19458d05dac SHA1: ce867c3610bf1c378991056c77ecfac1a5ad06d5 MD5sum: 46b1b27cadb0b8e0379041e7c685b795 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 3250 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_amd64.deb Size: 1036142 SHA256: 3f57663e055a26edfaa65f540cc349759e078adb9031d0a4fad3504cdd7c5305 SHA1: fadeef5b38e98c512164a2d15e3f89a598b2e554 MD5sum: f7c8a401adf1502cf74c51f90d3aa9b4 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 19845 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), 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_amd64.deb Size: 6484294 SHA256: 93c748056dd9f32975ede8d70aea3c646b729ab66ae3d76b37195ed116de1297 SHA1: 280f8bf4589e559ad0a87b0b8681dd4d64809639 MD5sum: 031c24867fc06561293de5ac9776122c 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 9551 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.2.5), 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_amd64.deb Size: 3034238 SHA256: 39074d96be443c0071f2771f1ad016d22dd91a26e0779aee3cdb27d366bb6d92 SHA1: b6994ac9033ca33d727b3d4f1ed02c25dcf2efa4 MD5sum: 3071a5fba2f2dc60ad15c15e9ae3b27d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 275 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_amd64.deb Size: 218988 SHA256: c715af214c6837df83c0b9eb2558f57a8992e3c11a658e53836baaae9b34296c SHA1: 44f72ae8fa0c5bfbccc01f24fe5d3085415689b2 MD5sum: 3ed7bbc623b0fe797f1f990df999a281 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 115 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_amd64.deb Size: 45322 SHA256: 25b8e0493f571545fc9cdf02f071d15ac7f0fe626ead8ae77551ba516ee306ea SHA1: 619b86820164bbc68705cb471f5c9303a98e43bb MD5sum: 066f500a66c705ac58b874dcdc2c56e3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 32572 SHA256: f68bd1fcc5e4e779561c20660cc338e04f026506808d3ae62974ccfd618a47b5 SHA1: d60a6a8decfc11b40c92cdc6c3d5e3c7911fc731 MD5sum: 5af7dbdfba9b2ae310f175dc8db1261b 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 176 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-2~nd70+1_amd64.deb Size: 63860 SHA256: 0532b78e95b7617406c9991f7a339ab0e14e9c1d6a9318609fde10ded93bbfcc SHA1: 5aa49ecca93da50260eb9dee7b9ac890ec6e3013 MD5sum: 949e5db1c1985e85bc72f6aed277ce77 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2360 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, 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_amd64.deb Size: 528346 SHA256: b05adf2c9a1d40bf950c9943007c3c4d599e6e0bbe33fc8b7e7272f0231b6321 SHA1: 136b0af0bd1c477446786eb3020296a2fd8d12cd MD5sum: 45cbe09f0360c4f559f6772aca930f29 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38596 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_amd64.deb Size: 9691342 SHA256: a1a3a3a63f9ebf7f48d4722f23def910dc25759a235f250360a7d4c6696d049d SHA1: 1b4f93b7cdc7e7a26b6c55aa0ff0864748a17570 MD5sum: 7749520e9b1bf82bef4e86f72f9b2a59 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 953 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_amd64.deb Size: 637662 SHA256: 63d5e22f24a493acda9dbed7422b3ba9e0ef4c06d276a36a415cae3f940c4419 SHA1: 6cf8f45897780ef602b8b88b40d245a8951de3de MD5sum: 07a7e07d785096a4615d894bd5a506bd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 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_amd64.deb Size: 24796 SHA256: 1e1a100b74842433a333fcfac346b160b81e80b88e4b965958e428e4bfd9a7ed SHA1: 61247dec7a9c683a4dfa6f547c4d05c01b826b6e MD5sum: 23cb46c3ee611edfeb6bea38a58e8444 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 293 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_amd64.deb Size: 122574 SHA256: e0a171f30504237fcd1dd96a87ad19db327264a180cc5d656d51954bb18f3b78 SHA1: a2116add360c1b38634f378faffa4c8b6d4e7025 MD5sum: 792d9caa7f43dcf8e8b52bd59616ae32 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 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_amd64.deb Size: 31618 SHA256: 4b78a0f603190f600d44306094239e6533ec3c78fad948a8f42f58f511b01f7e SHA1: b3493f59d0506c9aab36f137844d84f71a14762d MD5sum: 9f22a9f052e10c81cce1aa23cc4b3c66 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2863 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_amd64.deb Size: 933340 SHA256: bf95d9d4b572e49f1b1a6f9f889b158ebad8fc820ea3ccb9cf28023f059ac0cb SHA1: 9d5c41fca8fdfbe8f48aa24bdd8f5ddc4e62c3d3 MD5sum: a19b802e1f042511b1cbfed77d2828e3 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: 1.8.8-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 3912 Depends: neurodebian-popularity-contest, libatlas3-base, libblitz0ldbl, libc6 (>= 2.4), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libnifti2, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, mitools (= 1.8.8-1~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_1.8.8-1~nd70+1_amd64.deb Size: 1494074 SHA256: b21dce17314380a0da508a655fe6a6499bb9a9fbbde6414a3e65429ba86fc057 SHA1: 1922576c835dfb496dd03e24c0c03db9c469c88b MD5sum: e9815a71913250cb86376f441f12c750 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 637 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 197344 SHA256: c09fab2d3cefd845d022b5a8d13fe3adeb087133a9e39c2cb7c1d10babad7ff0 SHA1: 665303acb9e0a173b4286b8326eeb5f6395f7136 MD5sum: 32f370fe5c7f4c3cd0f823ca0f99da65 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1205 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_amd64.deb Size: 447952 SHA256: 7bb74eef7ae4ad1230b11b7bb4ac5cef5e5127f1d4de8271eb5cc1e070710096 SHA1: 21e444958d84d29880355f971c2bf0ae609c3017 MD5sum: 285d647cb96b4a366e8f8a9c514ac0fb 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: amd64 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_amd64.deb Size: 100674 SHA256: fadf4332d3b6faef5d7642e1badbae0e6ce1b6525b794f006f08f6459339e96b SHA1: 1fffeb81109d43bfbffee2228c75357a92d3abde MD5sum: af83e6ed54ee2191fb2b54808a6b6af0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2229 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_amd64.deb Size: 638288 SHA256: 42738ee9281785e614122f66d7b611292264fac53bb8300bc3c8cf62979726f2 SHA1: bb5689098455a366380f9bfc482f20ff639dd9ac MD5sum: 0c5ae2f984ccd4c9ed50796cb34c61e4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5663 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_amd64.deb Size: 1663650 SHA256: ede595c32587f73c53b6a31f0c96726678e9ebe8c738e0d5b9b6d49203136ef7 SHA1: 45db90bb059f137ca063d059fd2f163189adb5c7 MD5sum: 8ef62059722ec22c84bf35314e146861 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 23316 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, 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_amd64.deb Size: 6919680 SHA256: ed6b3272a055e79b5d251656139af39577b5ba8ee5ffbb9feecf0a0cdc5d5a1e SHA1: 5256b2515dee273bc03fd74e8923ed937ec81729 MD5sum: 863a4cc2856deb4e6eb18d58877c95e9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2207 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, 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_amd64.deb Size: 966582 SHA256: 78974e6aec09285d03502e81718537ff0da34e190b1b3659a74667c895204e4a SHA1: 7a48b39d208617ac8a2ec808cdf86a8f376fdf13 MD5sum: 46f822419b1695b0ea9654fde1dad855 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1553 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_amd64.deb Size: 583422 SHA256: 1343a289e7fdf7ff4df8ba1662f83e9c5a7c6d4f8d0d203bdc75c9a333f76f6d SHA1: 0b2a8df2c7a73f1bb49f457e6b2161e182721c4d MD5sum: 93bb75d5b7aae2f1036ad10ef0b87dcf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2726 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_amd64.deb Size: 870624 SHA256: 08fbb59a679408db11aed4624b15c8730ce4efdc7128b9e5dea4453bdaa8da9c SHA1: 9c0546b3e06d9df16b39934b073bbc777df177a7 MD5sum: 066dc9e058f974540e56fa3e90c3a2a5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 156 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 66542 SHA256: ced8b384b3efca4e9caf802329fe613fe29ea08d6035e2bb211e30b35f585fa4 SHA1: a11b6f75627ca010d8bcae87d3d314e8e86fe4bf MD5sum: 181570cf10998e269b7bc2fca7e017cb 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 207 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 (>= 2.2.5), 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_amd64.deb Size: 55970 SHA256: 3eb2577110e210a1f85468f926bcef0408c1fa99e608adfefcb6b585a2786587 SHA1: 4ddc695e15d62db4d0c00ba27c5b0ee734a5ac7f MD5sum: 0e4c88bb95af52e6a0560dfd2b9f5428 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 249 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 (>= 2.2.5), 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_amd64.deb Size: 95922 SHA256: d71134f96e4ce240a5a547af41c69ed5b621f90e30c670833255b57f3a4a7d17 SHA1: 43491ae5e0e436252cbe6638d9b1c6c9d860f52f MD5sum: d3ca3eb38666c9097fa1c94cc9dd27b3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5270 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.3), 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_amd64.deb Size: 1990756 SHA256: 4e372022b91570f44a60d187c037b63d06588b0cbe8c0eb6855ee2ad816e5cd4 SHA1: 4663b6416f0233f97ddbe640c100c9d713d5bf94 MD5sum: 779cf6942f8c83f4e3b6253c060fc1c4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 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_amd64.deb Size: 46968 SHA256: 73c89455b7454875f09d57d39db41111d6f2cd8f7aedf7cfa6656d0e155045cb SHA1: d406ed741c50c3fb0f768c824c5472c1d1a644ef MD5sum: de80b2e34aa24101dc21f9a0c879cc4c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 246 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.6.6-7~), python (<< 2.8), libc6 (>= 2.2.5) 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_amd64.deb Size: 67622 SHA256: 3aadd379883dac918c58727ada6ecf7f168bb8aa1632f0803a527063e909831e SHA1: 6a1992a54c082e81944b2f813c28dd3bcda1053e MD5sum: 0130d988a79b44c5f866bc466cc423bf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11805 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 (>= 2.2.5), 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_amd64.deb Size: 2456274 SHA256: 68944d6d3f77b7bd01128a055e9dee329e7aa3d449caebfb458bc2043811879e SHA1: 2b64501a36ba03af8a5946f3a93746233f45a216 MD5sum: eaa08181943340e25bedbc39e53f68be 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2449 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libopenmpi1.3, 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_amd64.deb Size: 806014 SHA256: 9f8f486fe2519e3251059fa93c727e99bf8ad3e3997019b0b9282ac6066ee39d SHA1: 1c287d94be14afe5409b5b9af69d95786aaab1c3 MD5sum: e41afd45af2caefe508fb9d5c368a0b7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10056 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_amd64.deb Size: 2409694 SHA256: b211af78cea408a1c990f4357dbd43e22f9081642670a53ae2b8cdbe395b51dd SHA1: 695b4c1893102e6eb8131c09520ce9f50b1a09c2 MD5sum: e64e1ca9cd8e115c8a86895dd744b86c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 316 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_amd64.deb Size: 125744 SHA256: db83141852de671f1286191c052027ad42c229c57ed00c4558a4e22450a8d4cd SHA1: 3bf25549dc54726c079c088d963f2d7df2ae9177 MD5sum: eb582f07ab482ed0180b159c78daec73 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 193 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0) 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_amd64.deb Size: 72850 SHA256: 7ce7fe100b0fe479eeea64791a083f8aaa1d22742ff1e3bdcd7187c2746bd4f2 SHA1: b54c74f54e8b986dd7652e9eb3008d4fdcb40d5d MD5sum: 723c80e0cb3e08805a5014a09ebf9799 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 57116 SHA256: bdbcc98c71ae430b908546fa9599a0ad09e9a7fe97165908bdea608d27df9df6 SHA1: 55fc2238bc8de9ee8c3f6162c69204bed76419bc MD5sum: ed76182d038b5de403daebde5779c82f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 20254 SHA256: b2d421240b3cd5f8142a7565d9316643158977528ad14d2d436c1d4c7274eeda SHA1: 20692a168ed98daa38196f7d2dcf383ebbcfe865 MD5sum: f7704f38d6ed95c5f351d20c67faa509 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1480 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 375728 SHA256: 7a4ac791f54109e24feabe3d4afc0be1d6dc52e7d1c78541d41bb515cca6a6f0 SHA1: 488170931671b03655c6e5db5a53e9fc9409ebd3 MD5sum: bc525d5d55673a048e1bcfb70e30c514 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: 0.4.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4966 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), 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_0.4.1-1~nd70+1_amd64.deb Size: 2081656 SHA256: c6c581aeb2ea0b7c3b34092aa03fb10288ce16fc968d56c394e3d6d3cf668700 SHA1: d307fbd9984f09a31c4ec0334e21d35ddc7a0848 MD5sum: 80e5a89271029d05d1e081f119eb0f70 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: 0.4.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7080 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-dbg (>= 2.6), python-dbg (<< 2.8), python-nipy-lib (= 0.4.1-1~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_0.4.1-1~nd70+1_amd64.deb Size: 2263954 SHA256: e4be4729376d73e1e42fb3968b8051e38e2169d40ba84d020fb4738510f9dd28 SHA1: 0de213ef05ba357de6aa5a36e105b6907d50f9f4 MD5sum: 1ebe6cc267efeb84ab372402890b22d9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 521 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_amd64.deb Size: 173342 SHA256: c1cf37be5debc6636e0ba857282db5a7ea42c7fa379b9191bca51eaccf2133f3 SHA1: 5b349073398ac836f15e974c3e5a1d344de6e308 MD5sum: 6c64afbbcb3c960648974615112d6888 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 752 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.6.6-3), python (<< 2.8), libc6 (>= 2.3.4), 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_amd64.deb Size: 289634 SHA256: 213d2f44a3e99a8e6c5bc2803cd5e30509e653f345790c512e0e55bb4b0575f5 SHA1: 1aafaebab9de19c898203a2ea6807a99272e7ac5 MD5sum: 9bafa5ff2dd3c9478b3796ac0aa3f539 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 586 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python-dbg (>= 2.6), python-dbg (<< 2.8), libc6 (>= 2.3.4), 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_amd64.deb Size: 255138 SHA256: 77d69a7138860f5fb4b94a990ce10fdf8dec4740a3eb306f48da869675fbb469 SHA1: 7db773b5e6252979410e72ae95167fc0a7a86ca5 MD5sum: dc2019cc52540abc797cb4389c7a3aa7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 652 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 166148 SHA256: 807f97c09c018dcd54c1965c2bc176468f0d2f18c9c7a574481d12c4333796f1 SHA1: ace23af7d56c818dd85677ea140858ceddc05acc MD5sum: f91e2544ae3fe175e90491435ebe54f2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5034 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_amd64.deb Size: 1869416 SHA256: d7bf94dd0855ecd8a9fcd811f1c4d7ff07ecca37d2b0a639dc1779429ef671ba SHA1: fdab601bce15dbacc0558223c0ab971d55609df7 MD5sum: d14ba88f4b8f6f7e9b8984b2300e1f8e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 570 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_amd64.deb Size: 153000 SHA256: f6dcdc902c42af9ce9b4db6b844442c189591d8c36905f1427d4e0fd32da52ac SHA1: c9fe386aa90fd611bc613732d857e810010c6ce1 MD5sum: db15b89d9a0e037d16cc1fa4acb460b1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2050 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 (>= 2.3.2), 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_amd64.deb Size: 612946 SHA256: 14623a42dc2d3479c582bfad00a23e11054cbedc3903ef1e08eb24d10e91d891 SHA1: f115b9fc55e7c8bb3386feef8a312e1b74889e0c MD5sum: fb7b66cbb35e6c4d2cb5bb615d959f45 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2936 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 (>= 2.2.5), 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_amd64.deb Size: 975936 SHA256: 8cdbd6cec2d277bd676701bbfd51a807b6ab6704627402e5ad5f877fea5c9caf SHA1: 2426834b305c11825f726e1d3de2adad075251a1 MD5sum: d3c5d619042795537fdc18db9eda75d7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16037 Depends: neurodebian-popularity-contest, python (>= 2.6.6-7~), libc6 (>= 2.2.5), 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_amd64.deb Size: 6452412 SHA256: d98343b41c185e877baf53e09506fbc8f8268c97559e8fdaade283b7d8025c26 SHA1: dece81414907ba2552ff81dc60bbe2dbd8f043e9 MD5sum: 22021d59dd81283136dc077b0d5304f0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2456 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 690242 SHA256: a022c8575548aa7a9c33b971c2bea24fa24c495b3163922565e917278d4362ed SHA1: d6ffaffae5443e84d90207f0b89e643276c86143 MD5sum: e4c1525ece15a0887f723bbb0019470e 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: 0.8.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4722 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Recommends: python-skimage Provides: python2.6-skimage-lib, python2.7-skimage-lib Homepage: http://scikits-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.8.2-1~nd70+1_amd64.deb Size: 1741838 SHA256: 9160149a42f97ed09f68d047e50f039d2629957d945e47132fb71897d1e65047 SHA1: b675b9715e011fff045172b441d1300dde034b78 MD5sum: 9415455b45d00f140347fea21f8acd33 Description: Optimized low-level algorithms for scikits-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. Python-Version: 2.6, 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8718 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), 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_amd64.deb Size: 3495380 SHA256: 77b93ea958434e04115a81f7d7a1926bd3e2983fa5a0846dd3f5ef29f01c0d84 SHA1: 84da3d0cae251c5a539d4ff2034cfd50c4c391fc MD5sum: 915e2aacfb18e6db6f5fb73620235fed 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.2.5) 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_amd64.deb Size: 93126 SHA256: a515154af3ff3c0ad3fa2a5a6d75d440c6733f89b2d62a544c8deb6cf66b74d5 SHA1: 3ded0a3788b5afb706007bb814f6f71bd1fc05de MD5sum: da65ee9546425b792e308cd09c2b36ef 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1532 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_amd64.deb Size: 631500 SHA256: de36d9f388703086a2be07eb683c295f8facfef17cf845f50143b427f3b2001f SHA1: 149c8c94fd090eb985172c5f9ff7d303cf6bc7b5 MD5sum: 94af4389d37e4c00e56cbae2473aba2a 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: amd64 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_amd64.deb Size: 223278 SHA256: 9062ef84ccd1c826e50113258d5a09ab715beb06e7e2300fb9db501d5c98b824 SHA1: 26ef56d367e2c3cd3faf2346df6e6d57e8231eb6 MD5sum: 362566030893f1c38e209b2abd9ad48b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1811 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_amd64.deb Size: 689474 SHA256: 443b332f8e4a13ff95dcff817a97cc4a5ad28fc0e5a62aa4156558d05a318d99 SHA1: e2bdccb2af8b7b69aa2d0dc7e4c529c8988b519c MD5sum: 7ab7660bdbcd3f93fcb96efb7626d050 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29686 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_amd64.deb Size: 7300084 SHA256: 79cccf123b81910b7404da2470228da7f730901303fce6e8f1df9d8142398e79 SHA1: 670e7945161349fb336d6eeb74a71065dbaa92d2 MD5sum: 2c6b5f97194d746ffe6b6df8abf74895 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-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 347 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.8, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd70+1_amd64.deb Size: 89892 SHA256: 837556e851d725d0c0326d13ad829d0158fc7f6162aacb7962f3f0d62bdd7c6d SHA1: 1fbf7323bbb6f5d98fae643b8f848b58403d1ba8 MD5sum: 24848b4b8dae5734a03e1908fd1a1b62 Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python-w3lib Version: 1.11.0-1~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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 423 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_amd64.deb Size: 135890 SHA256: 15167347dea5799e30bf991316e6bdb5f4a670a3c82be15c2e60c9d75f7fdbd7 SHA1: c28021009479d583b02107bd3aeea1171a22709d MD5sum: 3d7f7820c55367c46d2858966d0a731c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1241 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libopenmpi1.3, 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_amd64.deb Size: 408772 SHA256: c4412a3f163e864fc684d4901a20e8d9ee16f5ae1269f0a2a20750c74c5fff45 SHA1: 42e023485751e15c564a02a8c7362e8428180248 MD5sum: 5324b849697fe1ce27a683af92a5c15e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5013 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_amd64.deb Size: 1203222 SHA256: 1b08783a7e74fed6d3b01bd6cafdb1b543b433be8f3f7648dffa060ff45979bd SHA1: c0e4e8b22d14eeba477561508e31c6be56408e18 MD5sum: ed9f33667011fdb90ebf81cff868ffb5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 180 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_amd64.deb Size: 68494 SHA256: b6ffb10bd87c574185355368018826825af8331494f3e8252eb1157b67963040 SHA1: 62a77362564bb001f260771853f55ea3716af4b2 MD5sum: 6c03f7290a350d5d08d34c319f7d4d12 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 432 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.6.1), python3-numpy-abi9, python3 (<< 3.3), python3 (>= 3.2.3-3~), libc6 (>= 2.3.4), 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_amd64.deb Size: 165052 SHA256: d39b96f20cecb80bad1bf06a0b31623570555a994e585c19bfd613daa05dd447 SHA1: 36d24deee649548f55a2d2c4bb86abbed4258614 MD5sum: 3bc02a886feba703e5011d534d7fe7d6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 314 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.6.1), python3-numpy-abi9, python3-dbg (<< 3.3), python3-dbg (>= 3.2), libc6 (>= 2.3.4), 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_amd64.deb Size: 134976 SHA256: c9f7aa5d0f36559734868bb53e0909fe751205abcfb8667506277b041d9fccb7 SHA1: 3df39101f19fc22e693373fcf8db38989faead21 MD5sum: 076eef8a07c43940c743189d76db6a67 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4978 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_amd64.deb Size: 1850406 SHA256: d6a67996ede18cd87e063361484352685cee8c50894bdb4d06f39ff2310b87d4 SHA1: edca5884d55caf3f5beb7af1d5c033b116b043a6 MD5sum: a73875529d11dd96976d8ce53267f04b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 248 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_amd64.deb Size: 70068 SHA256: dec9088393f5777a9227e9ac6ea2c64e75b7b5a2a6bb0629789795768bf8afc4 SHA1: cb790357f963df2276c5c4d6b396995db1526be8 MD5sum: 0513c80305432c57b1a2ec242d178ab6 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-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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3075 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), 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_amd64.deb Size: 651280 SHA256: 915fdb1fdb0fd8a153cb82faa8458290d6679a8bf468ba75a44a3627b3172ce6 SHA1: 1a5f409753438c80716e93088f3dd8d6581955b3 MD5sum: e3c022901750de20a6a94e98a55431a7 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: amd64 Maintainer: Debian Go Packaging Team Installed-Size: 19633 Depends: libc6 (>= 2.3.2) 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_amd64.deb Size: 4810068 SHA256: b62160db730a2285a36444f0eb30a9f4c6a67957e03fff27de9cc3f8a7ecd689 SHA1: 68368135f21e5fa81d2904f9391054208697d5b3 MD5sum: f58523511ec0a1334697803e366f753e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 293 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_amd64.deb Size: 178652 SHA256: 71beb753e52dc4268a8cb1360128f9681ab4ac6b778303e42d069d9dcc393ee4 SHA1: a2f4e3bc0fa94c32886eac2b76ebd673217c6b0d MD5sum: 1a5b16e71b674ed5c6fb4b1bfc643231 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 143 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 45708 SHA256: 99e614a2f65d6b8db989989349e05b04a7cb6f4ef3dc08ea24ccce6f29f4644b SHA1: a1acfde2d2d54d9ba11824e222de4e769565102e MD5sum: 7857dcf2000949af764ca9e68c7bcc9e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7355 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 1512808 SHA256: 92802ee1447e9c260a7f77bc230e5aee023e72116cf0ebed656a9fa8e878ae97 SHA1: b70fd8e43f8dcff15e08a18730d68434580f7608 MD5sum: 3392c27ad6895e3bb25258a901845b83 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 72645 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_amd64.deb Size: 16120910 SHA256: 19a2e3a2a01f472d99226761eadeee7f0590b0d87ccea1178e1c42196e7c1e09 SHA1: 1a803d0f28f806e131670da91633c1ae9fc38075 MD5sum: 757deabee3fe99b4c69b0de93680717c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 61254 SHA256: b3dc6f206322cb919513ad828846d34fc623478bf505f7af0e6de1afad1c313b SHA1: 9d5e39a6f9e3d104d13eea20481345775156f99c MD5sum: 15644852e4cb04ee9b119de1ec567231 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7574 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 2247632 SHA256: ac5f4180ff5657214665e003533eb11923dd90ec0a631b15eb532eae8de1ad8b SHA1: c7da3ec3d6947e9d88dcaad075055948b87d45f6 MD5sum: 22a2d1c24fe1100268930ef759db2928 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11227 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 2614016 SHA256: 6438b82eae5c423aca41f2fa03df2472bedc3eac92290071dd1c47acde91565d SHA1: a1728276cb4624e1514879c2cf5a98381527c8d5 MD5sum: 3d992952901b9fb93d31c6bcc9cef9ba 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 26343 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 5923306 SHA256: 7d316f9cec1676fda6f0df9864e44078052df9755481d040bfdcf43535c7c5ff SHA1: aa44f7118f66b7baac0e0747e3a93b7cee09fb44 MD5sum: dc82087d5a260cb68e405261ce9c7468 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 66208 SHA256: 6caf382be4e16049d9cef7483afa01729d1b646a656fd2554ed6aa0d595a9138 SHA1: 4f107dd0b29b8a5057b6009429421b644d960a64 MD5sum: 4a1dfdedd327b095c24fb3911997ff3a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 260 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 65462 SHA256: 59962bed7a822cd2aed8ce5405cb2a679b35230c14a25deb54ed1a3686931ae5 SHA1: 13f03c6874369d5a42daa5914444ade604959dfa MD5sum: 64a9036ac53c3914593c1fe35acaca7a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8969 Depends: neurodebian-popularity-contest, libarpack2 (>= 2.1), libatlas3-base, libc6 (>= 2.2.5), 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_amd64.deb Size: 1971980 SHA256: 9b844b1f15b54779af1c14764dad3ee0799b456ec6347aa9494fd636cfd18d9a SHA1: 172a04c97937f5690926c314630ade366641a9f5 MD5sum: 3315adbba945a37febe4ee8d693633e5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, libbiosig1, libc6 (>= 2.2.5), 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_amd64.deb Size: 413102 SHA256: 3e22cc839cb6fb3070a8493fcf129311937d09a25e4e24493ffd4c2dc4df5fcf SHA1: 499e1e6872d48cfe75f850558c0226f09653890a MD5sum: 752b37ada98f78d26acf4e4da0c31c45 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: 2.2-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 991 Depends: neurodebian-popularity-contest, libc6 (>= 2.9), python Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.2-2~nd70+1_amd64.deb Size: 228604 SHA256: ad6bf1d0943119ca4093f8e0cc378723773880cb10b6ce7d5279eee877a1f8e8 SHA1: 306e6aa7619768f23c48449a36e592d8aacddd5f MD5sum: 963278b753a4e69eff1c49369e0dfbd7 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: solar-eclipse Version: 8.1.1+git0-g8f32b4b-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11357 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.6), libnifti2, libquadmath0 (>= 4.6), libstdc++6 (>= 4.4.0), tcl8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Recommends: python Homepage: http://solar-eclipse-genetics.org/ Priority: optional Section: science Filename: pool/main/s/solar-eclipse/solar-eclipse_8.1.1+git0-g8f32b4b-1~nd70+1_amd64.deb Size: 4589640 SHA256: 26e49d56245ee26a99ec8c0855e1b66896fad97aa8fbbce2f5d6ca1aa9eb0300 SHA1: d185092208f8180c72ec50b489fd2bf470aed857 MD5sum: 87a2a5071fadc21cf6bc06ee9e937f3c Description: genetic variance components analysis software SOLAR-Eclipse is an extensive, flexible software package for genetic variance components analysis, including linkage analysis, quantitative genetic analysis, SNP association analysis (QTN and QTLD), and covariate screening. Operations are included for calculation of marker-specific or multipoint identity-by-descent (IBD) matrices in pedigrees of arbitrary size and complexity, and for linkage analysis of multiple quantitative traits and/or discrete traits which may involve multiple loci (oligogenic analysis), dominance effects, household effects, and interactions. Additional features include functionality for mega and meta-genetic analyses where data from diverse cohorts can be pooled to improve statistical significance. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3118 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_amd64.deb Size: 1133386 SHA256: ba5cedf7945b5028e7d566842da269659f4ccee333bc1f8dc2d08292e1848cf3 SHA1: 84c08e41124b76941c241dbfe4bf4ae3ecd7e327 MD5sum: 45d323758885c4591eb13be5708275e0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 30157 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_amd64.deb Size: 8434540 SHA256: 521477176a9b77b6714931110b54858d698baefcaeda823bacf1d0ce645e2972 SHA1: 401c8d7fe75b54cba2d440cbe8f77343f002bb06 MD5sum: 5dcf8164cf9c1e57aa9cf9088cc4e3be 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: tcl-vtk Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16157 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_amd64.deb Size: 5322644 SHA256: 2f787363443fa6563ed9ad98b9e2e570a354106c758c5652b4ebf23aca8e4fec SHA1: eec67a1fadd025ba3069f8bf73fb323f5c466bd0 MD5sum: 93c1f13de7e12e1be1c105180edbd3d5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 258 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_amd64.deb Size: 82548 SHA256: 505ea20351136af2e78ca5874b7ba7f71dede7c08fafd7e5d7ad1a6673f63783 SHA1: 3230862b1e04a912b263cca1ba9c63d93e9b45b0 MD5sum: c4df729b6bfa12d296a3fa039eb7158d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 590 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_amd64.deb Size: 224032 SHA256: cfe13eebecb61f5f73e90295940e05d8d2966810d7369ca3c400cf4551582952 SHA1: 16fd139d1f61395765c1e4f326dccf21f2c96923 MD5sum: 1bad73138d9c24c66d856e1e3d3a4978 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2608 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_amd64.deb Size: 1176434 SHA256: 6de0a44cda867df8c32be1727d5a65fbee5a3e9fb78809f62ff6d154ee133f36 SHA1: 493c21441192a995fb574f4dadea412c576cbf05 MD5sum: 5ae8af197561408f96fccc8c46a2fcb6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1121 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_amd64.deb Size: 514712 SHA256: c5945488c72556a475075d4751dab111fda3e416665b10340b934efa7ad82b5c SHA1: fb36d4fe2cf5d5e588faae88b362e64c076b3203 MD5sum: 0df0484e1129d68d970638c051c62534 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 792 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_amd64.deb Size: 288610 SHA256: 39f2cdd1912dc038a5f42b85ffb59417d4743e20dcba876f4505e59492352526 SHA1: 3c5e8d96beea3d24bfd14b5c84bf4ec9a38635a2 MD5sum: a1ff87dc29126eba83bd5e1faec862bc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 551 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_amd64.deb Size: 258104 SHA256: bbc6e3f0525d4d4d448d4048c71f30a963866b372a2806d0bc2f3acaee2eae95 SHA1: 97f5af344eab7dd8a54c8cc0718d44653fbdc74e MD5sum: d69637d03d1716e3628fc7076f3ae978 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20444 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_amd64.deb Size: 7719578 SHA256: d1eb4869ae2b3435092c9c78129bbb32c549ce786cab4c66e4c667b5c1d45f32 SHA1: 2932c6ae1bccd8fe641d689b82873f9c992eadca MD5sum: 1dafeba9328f6a27c9d37899c9a56cd4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 45865 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_amd64.deb Size: 44673208 SHA256: a1978aab840c3e04857de1be88bff16a86736a2b680b5dbe30d3399eb1a442d0 SHA1: 301bc995bca9ab04c981435dafd47edb5343ec55 MD5sum: e157e9c90ae3eb5629ee9dc246eb702d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 628 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_amd64.deb Size: 180770 SHA256: 24267304fa1bc850db435571d21e5a6377fc6a46fc2ab6651aea60829f51f6a1 SHA1: 4d805d92442f6d4bc1596aacd2565e1eb4171e5d MD5sum: b11732d6d0c3028be0668f041559164a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 55 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_amd64.deb Size: 21624 SHA256: 5f1ebcf9be12eef3a11164a1b3fd16198df12dda9ba13a44d336ead6bf0b12d9 SHA1: 82a77e652ce32a14e7114a39da53b067526cffeb MD5sum: 567113cc3694cb703c2950b4311d6063 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8202 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_amd64.deb Size: 2397190 SHA256: bf5371fe2768e3aacf073a7dd646ac7ca47ee6b1a9d24266c746870b11dd0164 SHA1: afd0fefc8389a3f9d074c79fa55a7394eeb54b5a MD5sum: a8a91f30c844b1e08233bf16866ef67f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10232 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), 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_amd64.deb Size: 3755282 SHA256: 6bdf208f5be29c38d1a289781dc115bd8ced8ccca4666749bee93844550f6005 SHA1: 72dec9297a356f210fdea023341c40156a40fa0c MD5sum: da38303fc1cedf6c540fa94536d1a418 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 386 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_amd64.deb Size: 113446 SHA256: 30c10d6d3bb885fc839c049206fd74a92891b53e3a1dec479b4cd1beaeab96e3 SHA1: 9a7b23fc31f9c78fe54ea0dfcfe6e62f899cd5a5 MD5sum: 41c5739a785c4f86691d9bb9f130cafd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5779 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_amd64.deb Size: 1811102 SHA256: 12728df36d1115de7ad9b7937afa94a364869f221a24422d6b7a36af30513149 SHA1: 927f5bc1061857f298fccd6eac170612468f3be9 MD5sum: 9a06cfd29e23ff071f489c5253cd7552 Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 195 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libvtk-dicom0.5, libvtk5.8 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd70+1_amd64.deb Size: 79094 SHA256: fc4bc3af3483d69e0bc83370e23472feb60959dc9aa5a36f710bf6f0bc87bd72 SHA1: 2df7c09615b26ef6f3c6b6f01a1991436cdcd29f MD5sum: 549e627a8ecfab1c91e20baf70c9ac10 Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 528 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_amd64.deb Size: 256342 SHA256: 3ec43406d65e048e526712069eb321c6ffb44f9ed828b3648d9d0e7cb5bdcbbc SHA1: add62d428312df8cbfb9fbbc287535e6d70ebd27 MD5sum: 25c341b0b6a71c758df0050d3376436b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 985 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_amd64.deb Size: 345494 SHA256: fe8bf3f19ee02df02bdfedba5e22a5ae424ae89495ec24491a5f19d3e0cd843a SHA1: fc34586925edb9638c175287d3e9a856dd1ab4a6 MD5sum: d34d4ffca25f74e83a4bd4ee1d6f11db 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5809 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_amd64.deb Size: 4187354 SHA256: 5fc94705f843f8719cc00b08626bfe7800b55fd64b26d944313e5a09984da942 SHA1: 2b7c0b88eab5942584ce1c79755424e71b8363fb MD5sum: f5b23e13b63b29d071c016e1176a554c 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, CCTV, CDA, CeskaTelevize, CeskaTelevizePorady, channel9, CharlieRose, Chaturbate, Chilloutzone, chirbit, chirbit:profile, cielotv.it, Cinchcast, Cinemax, CiscoLiveSearch, CiscoLiveSession, CJSW, cliphunter, Clippit, ClipRs, Clipsyndicate, CloserToTruth, CloudflareStream, Cloudy, Clubic, Clyp, cmt.com, CNBC, CNBCVideo, CNN, CNNArticle, CNNBlogs, ComedyCentral, ComedyCentralTV, CommonMistakes, CondeNast, CONtv, Corus, Coub, Cracked, Crackle, CrooksAndLiars, crunchyroll, crunchyroll:playlist, CSpan, CtsNews, CTV, CTVNews, cu.ntv.co.jp, Culturebox, CultureUnplugged, curiositystream, curiositystream:collection, CWTV, DailyMail, dailymotion, dailymotion:playlist, dailymotion:user, daum.net, daum.net:clip, daum.net:playlist, daum.net:user, DBTV, DctpTv, DeezerPlaylist, defense.gouv.fr, democracynow, DHM, Digg, DigitallySpeaking, Digiteka, Discovery, DiscoveryGo, DiscoveryGoPlaylist, DiscoveryNetworksDe, DiscoveryVR, Disney, dlive:stream, dlive:vod, Dotsub, DouyuShow, DouyuTV, DPlay, DRBonanza, Dropbox, DrTuber, drtv, drtv:live, DTube, Dumpert, dvtv, dw, dw:article, EaglePlatform, EbaumsWorld, EchoMsk, egghead:course, egghead:lesson, ehftv, eHow, EinsUndEinsTV, Einthusan, eitb.tv, EllenTube, EllenTubePlaylist, EllenTubeVideo, ElPais, Embedly, EMPFlix, Engadget, Eporner, EroProfile, Escapist, ESPN, ESPNArticle, EsriVideo, Europa, EWETV, ExpoTV, Expressen, ExtremeTube, EyedoTV, facebook, FacebookPluginsVideo, faz.net, fc2, fc2:embed, Fczenit, filmon, filmon:channel, Filmweb, FiveThirtyEight, FiveTV, Flickr, Folketinget, FootyRoom, Formula1, FOX, FOX9, FOX9News, Foxgay, foxnews, foxnews:article, FoxSports, france2.fr:generation-what, FranceCulture, FranceInter, FranceTV, FranceTVEmbed, francetvinfo.fr, FranceTVJeunesse, FranceTVSite, Freesound, freespeech.org, FreshLive, FrontendMasters, FrontendMastersCourse, FrontendMastersLesson, FujiTVFODPlus7, Funimation, Funk, Fusion, Fux, Gaia, GameInformer, GameSpot, GameStar, Gaskrank, Gazeta, GDCVault, generic, Gfycat, GiantBomb, Giga, GlattvisionTV, Glide, Globo, GloboArticle, Go, GodTube, Golem, google:podcasts, google:podcasts:feed, GoogleDrive, Goshgay, GPUTechConf, Groupon, hbo, HearThisAt, Heise, HellPorno, Helsinki, HentaiStigma, hetklokhuis, hgtv.com:show, HiDive, HistoricFilms, history:player, history:topic, hitbox, hitbox:live, HitRecord, hketv, HornBunny, HotNewHipHop, hotstar, hotstar:playlist, Howcast, HowStuffWorks, HRTi, HRTiPlaylist, Huajiao, HuffPost, Hungama, HungamaSong, Hypem, ign.com, IGNArticle, IGNVideo, IHeartRadio, iheartradio:podcast, imdb, imdb:list, Imgur, imgur:album, imgur:gallery, Ina, Inc, IndavideoEmbed, InfoQ, Instagram, instagram:tag, instagram:user, Internazionale, InternetVideoArchive, IPrima, iqiyi, Ir90Tv, ITTF, ITV, ITVBTCC, ivi, ivi:compilation, ivideon, Iwara, Izlesene, Jamendo, JamendoAlbum, JeuxVideo, Joj, Jove, JWPlatform, Kakao, Kaltura, Kankan, Karaoketv, KarriereVideos, Katsomo, KeezMovies, Ketnet, khanacademy, khanacademy:unit, KickStarter, KinjaEmbed, KinoPoisk, KonserthusetPlay, KrasView, Ku6, KUSI, kuwo:album, kuwo:category, kuwo:chart, kuwo:mv, kuwo:singer, kuwo:song, la7.it, laola1tv, laola1tv:embed, lbry, lbry:channel, LCI, Lcp, LcpPlay, Le, Lecture2Go, Lecturio, LecturioCourse, LecturioDeCourse, LEGO, Lemonde, Lenta, LePlaylist, LetvCloud, Libsyn, life, life:embed, limelight, limelight:channel, limelight:channel_list, LineTV, linkedin:learning, linkedin:learning:course, LinuxAcademy, LiTV, LiveJournal, LiveLeak, LiveLeakEmbed, livestream, livestream:original, livestream:shortener, LnkGo, loc, LocalNews8, LoveHomePorn, lrt.lt, lynda, lynda:course, m6, mailru, mailru:music, mailru:music:search, MallTV, mangomolo:live, mangomolo:video, ManyVids, Markiza, MarkizaPage, massengeschmack.tv, MatchTV, MDR, MedalTV, media.ccc.de, media.ccc.de:lists, Medialaan, Mediaset, Mediasite, MediasiteCatalog, MediasiteNamedCatalog, Medici, megaphone.fm, Meipai, MelonVOD, META, metacafe, Metacritic, mewatch, Mgoon, MGTV, MiaoPai, minds, minds:channel, minds:group, MinistryGrid, Minoto, miomio.tv, MiTele, mixcloud, mixcloud:playlist, mixcloud:user, MLB, Mms, Mnet, MNetTV, MoeVideo, Mofosex, MofosexEmbed, Mojvideo, Morningstar, Motherless, MotherlessGroup, Motorsport, MovieClips, MovieFap, Moviezine, MovingImage, MSN, mtg, mtv, mtv.de, mtv:video, mtvjapan, mtvservices:embedded, MTVUutisetArticle, MuenchenTV, mva, mva:course, Mwave, MwaveMeetGreet, MyChannels, MySpace, MySpace:album, MySpass, Myvi, MyVidster, MyviEmbed, MyVisionTV, n-tv.de, natgeo:video, NationalGeographicTV, Naver, NBA, nba:watch, nba:watch:collection, NBAChannel, NBAEmbed, NBAWatchEmbed, NBC, NBCNews, nbcolympics, nbcolympics:stream, NBCSports, NBCSportsStream, NBCSportsVPlayer, ndr, ndr:embed, ndr:embed:base, NDTV, NerdCubedFeed, netease:album, netease:djradio, netease:mv, netease:playlist, netease:program, netease:singer, netease:song, NetPlus, Netzkino, Newgrounds, NewgroundsPlaylist, Newstube, NextMedia, NextMediaActionNews, NextTV, Nexx, NexxEmbed, nfl.com (CURRENTLY BROKEN), nfl.com:article (CURRENTLY BROKEN), NhkVod, NhkVodProgram, nhl.com, nick.com, nick.de, nickelodeon:br, nickelodeonru, nicknight, niconico, NiconicoPlaylist, Nintendo, njoy, njoy:embed, NJPWWorld, NobelPrize, NonkTube, Noovo, Normalboots, NosVideo, Nova, NovaEmbed, nowness, nowness:playlist, nowness:series, Noz, npo, npo.nl:live, npo.nl:radio, npo.nl:radio:fragment, Npr, NRK, NRKPlaylist, NRKRadioPodkast, NRKSkole, NRKTV, NRKTVDirekte, NRKTVEpisode, NRKTVEpisodes, NRKTVSeason, NRKTVSeries, NRLTV, ntv.ru, Nuvid, NYTimes, NYTimesArticle, NYTimesCooking, NZZ, ocw.mit.edu, OdaTV, Odnoklassniki, OktoberfestTV, OnDemandKorea, onet.pl, onet.tv, onet.tv:channel, OnetMVP, OnionStudios, Ooyala, OoyalaExternal, OraTV, orf:burgenland, orf:fm4, orf:fm4:story, orf:iptv, orf:kaernten, orf:noe, orf:oberoesterreich, orf:oe1, orf:oe3, orf:salzburg, orf:steiermark, orf:tirol, orf:tvthek, orf:vorarlberg, orf:wien, OsnatelTV, OutsideTV, PacktPub, PacktPubCourse, pandora.tv, ParamountNetwork, parliamentlive.tv, Patreon, pbs, PearVideo, PeerTube, People, PerformGroup, periscope, periscope:user, PhilharmonieDeParis, phoenix.de, Photobucket, Picarto, PicartoVod, Piksel, Pinkbike, Pinterest, PinterestCollection, Pladform, Platzi, PlatziCourse, play.fm, player.sky.it, PlayPlusTV, PlaysTV, Playtvak, Playvid, Playwire, pluralsight, pluralsight:course, podomatic, Pokemon, PolskieRadio, PolskieRadioCategory, Popcorntimes, PopcornTV, PornCom, PornerBros, PornHd, PornHub, PornHubPagedVideoList, PornHubUser, PornHubUserVideosUpload, Pornotube, PornoVoisines, PornoXO, PornTube, PressTV, prosiebensat1, puhutv, puhutv:serie, Puls4, Pyvideo, qqmusic, qqmusic:album, qqmusic:playlist, qqmusic:singer, qqmusic:toplist, QuantumTV, Qub, Quickline, QuicklineLive, R7, R7Article, radio.de, radiobremen, radiocanada, radiocanada:audiovideo, radiofrance, RadioJavan, Rai, RaiPlay, RaiPlayLive, RaiPlayPlaylist, RayWenderlich, RayWenderlichCourse, RBMARadio, RDS, RedBull, RedBullEmbed, RedBullTV, RedBullTVRrnContent, Reddit, RedditR, RedTube, RegioTV, RENTV, RENTVArticle, Restudy, Reuters, ReverbNation, RICE, RMCDecouverte, RockstarGames, RoosterTeeth, RottenTomatoes, Roxwel, Rozhlas, RTBF, rte, rte:radio, rtl.nl, rtl2, rtl2:you, rtl2:you:series, Rtmp, RTP, RTS, rtve.es:alacarta, rtve.es:infantil, rtve.es:live, rtve.es:television, RTVNH, RTVS, RUHD, RumbleEmbed, rutube, rutube:channel, rutube:embed, rutube:movie, rutube:person, rutube:playlist, RUTV, Ruutu, Ruv, safari, safari:api, safari:course, SAKTV, SaltTV, Sapo, savefrom.net, SBS, schooltv, screen.yahoo:search, Screencast, ScreencastOMatic, ScrippsNetworks, scrippsnetworks:watch, SCTE, SCTECourse, Seeker, SenateISVP, SendtoNews, Servus, Sexu, SeznamZpravy, SeznamZpravyArticle, Shahid, ShahidShow, Shared, ShowRoomLive, Sina, sky.it, sky:news, sky:sports, sky:sports:news, skyacademy.it, SkylineWebcams, skynewsarabia:article, skynewsarabia:video, Slideshare, SlidesLive, Slutload, Snotr, Sohu, SonyLIV, soundcloud, soundcloud:playlist, soundcloud:search, soundcloud:set, soundcloud:trackstation, soundcloud:user, SoundcloudEmbed, soundgasm, soundgasm:profile, southpark.cc.com, southpark.cc.com:español, southpark.de, southpark.nl, southparkstudios.dk, SpankBang, SpankBangPlaylist, Spankwire, Spiegel, sport.francetvinfo.fr, Sport5, SportBox, SportDeutschland, spotify, spotify:show, Spreaker, SpreakerPage, SpreakerShow, SpreakerShowPage, SpringboardPlatform, Sprout, sr:mediathek, SRGSSR, SRGSSRPlay, stanfordoc, Steam, Stitcher, StitcherShow, Streamable, streamcloud.eu, StreamCZ, StreetVoice, StretchInternet, stv:player, SunPorno, sverigesradio:episode, sverigesradio:publication, SVT, SVTPage, SVTPlay, SVTSeries, SWRMediathek, Syfy, SztvHu, t-online.de, Tagesschau, tagesschau:player, Tass, TBS, TDSLifeway, Teachable, TeachableCourse, teachertube, teachertube:user:collection, TeachingChannel, Teamcoco, TeamTreeHouse, TechTalks, techtv.mit.edu, ted, Tele13, Tele5, TeleBruxelles, Telecinco, Telegraaf, TeleMB, TeleQuebec, TeleQuebecEmission, TeleQuebecLive, TeleQuebecSquat, TeleQuebecVideo, TeleTask, Telewebion, TennisTV, TenPlay, TestURL, TF1, TFO, TheIntercept, ThePlatform, ThePlatformFeed, TheScene, TheStar, TheSun, TheWeatherChannel, ThisAmericanLife, ThisAV, ThisOldHouse, TikTok, TikTokUser (CURRENTLY BROKEN), tinypic, TMZ, TMZArticle, TNAFlix, TNAFlixNetworkEmbed, toggle, ToonGoggles, tou.tv, Toypics, ToypicsUser, TrailerAddict (CURRENTLY BROKEN), Trilulilu, Trovo, TrovoVod, TruNews, TruTV, Tube8, TubiTv, Tumblr, tunein:clip, tunein:program, tunein:shortener, tunein:station, tunein:topic, TunePk, Turbo, tv.dfb.de, TV2, tv2.hu, TV2Article, TV2DK, TV2DKBornholmPlay, TV4, TV5MondePlus, tv5unis, tv5unis:video, tv8.it, TVA, TVANouvelles, TVANouvellesArticle, TVC, TVCArticle, TVer, tvigle, tvland.com, TVN24, TVNet, TVNoe, TVNow, TVNowAnnual, TVNowNew, TVNowSeason, TVNowShow, tvp, tvp:embed, tvp:series, TVPlayer, TVPlayHome, Tweakers, TwitCasting, twitch:clips, 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