Package: aghermann Version: 1.0.4-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1592 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp8, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.6), libunique-3.0-0 (>= 2.90.1), libvte-2.90-9 (>= 1:0.27.2) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.4-1~nd14.04+1_amd64.deb Size: 530764 SHA256: 2839d619882d83d4dadb934392fa6e0b5da687a5d51eb27aa790bd097f118064 SHA1: 8496629d65379e4d52704f5c70b82b4a8811f0d1 MD5sum: 06cd3312c46b1c15fd3a5276df200409 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: 2.1.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 166393 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libinsighttoolkit4.7, libstdc++6 (>= 4.6) Recommends: environment-modules Suggests: fsl, gridengine-client, r-base-core Conflicts: gpe-conf Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_2.1.0-2~nd14.04+1_amd64.deb Size: 23464000 SHA256: b738612c511b271294acf029840be923e7d854ad51645a2568d850e634e9e08f SHA1: d513216b6b15fa5b6e0b14aa79d6a734938e04e9 MD5sum: 82cb36ad087eda967fff6015bfcdee70 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). . This package provides environment-modules configuration. Use 'module load ants' to make all cmdline tools available in your shell. Package: bats Version: 0.4.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest Homepage: https://github.com/sstephenson/bats Priority: optional Section: shells Filename: pool/main/b/bats/bats_0.4.0-1~nd14.04+1_all.deb Size: 14380 SHA256: fddb023e52a6515b50557af46c086354d4096c16874c9cd9f375586299d472de SHA1: 618cbfadea7eb8069c32c0b3075a3033adb283be MD5sum: f13ced8df8376670cb14d9be8d8e7798 Description: bash automated testing system Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. Bats is most useful when testing software written in Bash, but you can use it to test any UNIX program. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 658 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_1.4.1-2~nd14.04+1_amd64.deb Size: 237906 SHA256: 405f5c292224f6a25595d99a0ba24857ef26b6a96b6a2223db1ed7013c8dc0ab SHA1: 23f615ee1ecf630c12347b9e04be37dfd1f24f47 MD5sum: e8c12de4fac25eadcbc976e275109805 Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: btrbk Version: 0.23.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 295 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv Homepage: http://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.23.2-1~nd14.04+1_all.deb Size: 67496 SHA256: ed91d74bdb196eaadba2f91eaabc12295d88a189d5518f0b4b74be07b9b6e370 SHA1: 0b2dfcf634cb795aa39f20b1c6cb97e23c6ee664 MD5sum: 679e519b169e6c4bac49b3c1a148a3c8 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3321 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~nd14.04+1_amd64.deb Size: 483874 SHA256: 053c74d29848de83a393709dbb6275a22ae91e7cf8262cc520544e2602db9098 SHA1: 881bdc84e3bd23463db1e6d5b59dc0a8277debeb MD5sum: ba0371a9d0e2bce39947b746ddfff3df 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5709 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd14.04+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd14.04+1_amd64.deb Size: 4657730 SHA256: 43a1175ff8752135bc6b2cc169c452e986677885083df939def204f8e277241c SHA1: e27ebea792a5b4fa3c832a3d7013debdee3ab74e MD5sum: ed0829b4e88fd92140da4183524e08b1 Description: Checksumming Copy on Write Filesystem utilities (debug) Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains the debugging symbols. Package: cde Version: 0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1022 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1_amd64.deb Size: 144680 SHA256: f8a857091f8f96b6e353bc6ee61846d5a94a6591c4366545284c574e0e3ffe6b SHA1: ef8e513155605f8c04c1500f5e5d70f05e67836f MD5sum: 8fa54dc077b3b3e90548a1a58db6a0c3 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cmtk Version: 3.2.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24503 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libmxml1, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_3.2.2-1~nd14.04+1_amd64.deb Size: 3631742 SHA256: a991f829e3a68725b5ffb4e30ffa0349089260be722f7821e6c73eebc1dc701b SHA1: aba14b25b9aa6921c8841188c1b64950842dfa23 MD5sum: 65a4a934d4230bbebb982cca380c7c9c Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cnrun-tools Source: cnrun Version: 2.0.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.4.0) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.3-1~nd14.04+1_amd64.deb Size: 17284 SHA256: 6620a9d9fa7a89c82692875b11478ff5b9f6d973a1748ec40ee722e9738c684a SHA1: 40a3b529eef4e184e70af243a35fd33936c53f0c MD5sum: 966e324f1eb7a42f95e29f7d4a1da9fa 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.2~dfsg.1-1~nd14.04+1_all.deb Size: 15720 SHA256: d7733566674c51836cd7ea782fa4ca1bc31f2c8df9d5718e0832d712ed12ce70 SHA1: 53efcf6b6b6f3986a2d16921648f5a03c715375b MD5sum: 355bab86f15980da222a09ecdfb9383a 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.2~dfsg.1-1~nd14.04+1_all.deb Size: 15740 SHA256: 6211739c90133636c75c560b06c9aeccd64f6dbe3524d9700790b2085777a343 SHA1: 874bf64b4a01b97369a7cc520d2cd6f8e63f806a MD5sum: 3717e70c257abdde6f9e16a207f3d9f4 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.2~dfsg.1-1~nd14.04+1_all.deb Size: 15750 SHA256: 4dd0ffafbe5cbd99976cfbb706b28ddb220fdbaa06dd238426addd1ceeb54711 SHA1: 85669aae0740478750b4396f493153f83dae633a MD5sum: 77063b8041e125c458683c9b85f1bf57 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.2~dfsg.1-1~nd14.04+1_all.deb Size: 15744 SHA256: 46720ddc9795c239c6c8130dbaea3ed0b82e8b07b75eed827d5e6306a963bf8a SHA1: 5f3b5cd5d64fc1cb5c859c49b0206b7a126a1e75 MD5sum: 0f52c3c43be3249c687f7d0c86587f28 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: 1.2.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51204 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.4), libosmesa6 (>= 6.5.2-1) | libgl1-mesa-glide3, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.7.0~beta1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.4) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.2.2-1~nd14.04+1_amd64.deb Size: 25146036 SHA256: a8a4db294e03dcef02835ed389e62c133cdf7b3c42b44234b0feabca6f8c2eb4 SHA1: c452818c09175b1a3f1860212aadab6fcfae03ba MD5sum: a2d683785a14de7f001da554471811fd 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: 1.2.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 139336 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.2.2-1~nd14.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.2.2-1~nd14.04+1_amd64.deb Size: 136778278 SHA256: 0e75ce168599227be26a1e21c411356187ad1f763130800cdc263f395e36c81a SHA1: 3efc5ff2c974fce13ad809dfd48304c48463d344 MD5sum: e8d832d4686570ac34ec28c68c4d482b Description: brain visualization, analysis and discovery tool -- debug symbols Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. . This package contains debug symbols for the binaries. Package: datalad Version: 0.2.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.2.3-1~nd14.04+1), python Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.2.3-1~nd14.04+1_all.deb Size: 27936 SHA256: 8b254d2c0827ab0b2c66681428b82dd74a7418db7967a940da8c6c72b49415dc SHA1: 69738ba5593b795f00157dc7f9c110b767708026 MD5sum: 2dd55f215db940a94a4e9803e7226c71 Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming for neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare or update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of datasets (search, install, uninstall, upgrade etc) . This package provides the command line tool. Install without Recommends if you need only core functionality. . DISCLAIMER: DataLad is Work-In-Progress and this package is not yet for regular user consumption. Primarily intended for demonstrations and development. Package: dcm2niix Version: 0.20160606.1+git22-gf6471c0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_0.20160606.1+git22-gf6471c0-1~nd14.04+1_amd64.deb Size: 90428 SHA256: 366cf800b0d995b758996fc04ae35244a8610e884401581a6b6893c6e3d0b770 SHA1: 4b778e4ba5f25449543b6d5999d7d918a1c6aaaa MD5sum: 7ef9e65f1eccb24b75dbd69d88741015 Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 37574 SHA256: 48dde4d86cc614b77aa5a2d1290f6a04dacdf59c1f77451f8c5d5b13532abfbb SHA1: 25a49d3bd47422f2a9c9bc46a5d17de84ce5525e MD5sum: 6a68f3fbd055bcb6c949ff86e93a9c03 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: dh-systemd Source: init-system-helpers Version: 1.18~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, perl, debhelper Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/dh-systemd_1.18~nd13.10+1+nd14.04+1_all.deb Size: 13814 SHA256: d174181f267afbaf3c6c7d6108b65eca78861aa6d3c71288a03db9b5cafd5a13 SHA1: 15700758d679f3bda80f55b5f435edad45d1b39e MD5sum: 4ed20ea08d8c497a1a3e9b7ce46fe4c8 Description: debhelper add-on to handle systemd unit files dh-systemd provides a debhelper sequence addon named 'systemd' and the dh_systemd_enable/dh_systemd_start commands. . The dh_systemd_enable command adds the appropriate code to the postinst, prerm and postrm maint scripts to properly enable/disable systemd service files. The dh_systemd_start command deals with start/stop/restart on upgrades for systemd-only service files. Package: dicomnifti Version: 2.32.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 514 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.6) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.32.1-1~nd14.04+1_amd64.deb Size: 95646 SHA256: a0faecbd1cd8ce2829c36033a89e482cb37b5951395174cc03dd980027f13d0e SHA1: 974e826d147fcf090f756122c99938b28c6f4965 MD5sum: 0be470f6d6d61b42ba8b5d2c43807762 Description: converts DICOM files into the NIfTI format The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer. . dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files. Package: dmtcp Version: 2.3.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2520 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_2.3.1-6~nd14.04+1_amd64.deb Size: 633372 SHA256: 3595f57c349b565907ff07de81fc6baebc049a7ae3000b18eea1f21c75617f59 SHA1: fe9fb79ad98515cbf16a3b353ea6a7db81043381 MD5sum: d36e7d4cf8d373e4a47d0dd462edfe57 Description: Checkpoint/Restart functionality for Linux processes DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains DMTCP binaries. Package: dmtcp-dbg Source: dmtcp Version: 2.3.1-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24027 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_2.3.1-6~nd14.04+1_amd64.deb Size: 4207898 SHA256: 4d3c64cb9a85b297b51a75f35030ecb871cfc774ef67cd89b8b3df7daeb4bbef SHA1: a94860fa591411023309edfe00b19989124b763b MD5sum: 5229bcb10442f308559de77e60f9d6d6 Description: Debug package for dmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 7062228 SHA256: aa1e0c88dbb25feff7d4a79637ce14e2bd7fccf5b2e73f675ba5b88baebdcb3b SHA1: e5d9d261fdfa5d96e1fe0b8e6ce4b67948bb54c4 MD5sum: 0bf506b1eed312f76a0e48cb663cb40a Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.9.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1212 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python, 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_0.9.5-1~nd14.04+1_all.deb Size: 254112 SHA256: 798684a41fb1e5741f1c66eaa6bd7b18078ddbc6d857220c948f75a111c7b59b SHA1: 1fcc5938df9a473095bb2735082deb2a073973ed MD5sum: 45b9946091042c375994295d9e9615db Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: freeipmi Version: 1.4.9-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd14.04+1_all.deb Size: 1172 SHA256: ddbc7d7bbb61097f230807cfc6c0a77d391bf1d4a6e31410718041006b827f32 SHA1: d2a247bce06f052b9d54033f81738a20cb1b9077 MD5sum: 2951d4e9077337872d5db574dfbd131f 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 126 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd14.04+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.9-1~nd14.04+1_amd64.deb Size: 44788 SHA256: 9f9184242e9298760c07be377b7a986684adc81e97323060c648e365d3398495 SHA1: 4133a03fa034dfac7ca7a786cc5b72db50362604 MD5sum: 148fc92697b09a06e9505202a171d51f 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 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~nd14.04+1_all.deb Size: 189106 SHA256: 705f1b5454ee66c6fb40ef496ffe68656c0b7524dd0e51b1ce2b3dc2a8e7762e SHA1: af7f15103d39b2d03ef557295a8d218997ef76a2 MD5sum: 223c7b78bf96ba503d34c6129041813f 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd14.04+1_amd64.deb Size: 37450 SHA256: b7bc7d8557901c926aecda4a1d649d08764e93df48471d77bb3b012bb12dcd4f SHA1: 40102c4b037345bb496948210fe9611206ba8c28 MD5sum: af50e84c9f81453aabea82f11f6ac475 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 192 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd14.04+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.9-1~nd14.04+1_amd64.deb Size: 78678 SHA256: 33251143ea06acadf9fe3af8154c46a5e6bae05dd2362da46f6b9e59dae49283 SHA1: 7daf9e47a6e905d6897bd233bf83135910ad7483 MD5sum: a7f340776bf3d37bc54b36ec123d35b0 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2798 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.9-1~nd14.04+1), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd14.04+1) Suggests: freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-tools_1.4.9-1~nd14.04+1_amd64.deb Size: 590662 SHA256: af2159dc89293748fc96b8981c98faec1cda9742a719abb2cedb592a00949b6f SHA1: 9d4dd8723fb16d3f6a1b98eb3992cd317f3dd6f3 MD5sum: 6830535b881a872cf14d5a0d10de3177 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~nd14.04+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~nd14.04+1_amd64.deb Size: 8634 SHA256: c1002af0ca650e34521b408b549336720eb192063913577777b262603ec6e7f0 SHA1: 10584cebddaf0b1bf3629f26195850d24da38bca MD5sum: a34cf06b7d45091ab2e11684cce22b1d 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 108 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-nibabel, python, python-numpy, python:any (<< 2.8), python-pkg-resources, python-scipy, python-matplotlib, 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~nd14.04+1_all.deb Size: 13908 SHA256: bd401b3672c86e560a1927b583637a89617ab68c7e7785458566f6aac708be7b SHA1: 3b05c5b556d57b3764ca8a2c8d52363aeacb801f MD5sum: b8a48a2a910611bd834f22e8f1974fac Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: fslview Version: 4.0.1-7~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 6583 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-7~nd14.04+1_amd64.deb Size: 1318356 SHA256: afb47d7aa37ef6002ff96e77e1c8ffaadb022c774fa6b28ab5b23ba2bbe1dc0d SHA1: 8bfa7f921902da2c420246ea9b17900c7ee37bcd MD5sum: 62965b63b65169bedf22654db76433a0 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: 4.0.1-7~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 2898 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-7~nd14.04+1_all.deb Size: 2228538 SHA256: 090d2faad68a2d0bd98956f35958dc9aeb5163f534d3ba4368817f656c06d70f SHA1: cbc2784174659eb5743bb2c7c8f5ab1d658004d7 MD5sum: 5d36ffd8a0146a965379b234953844e1 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1739 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.3.2-1~nd14.04+1_all.deb Size: 1669830 SHA256: fd31d1e902264566bf7e32785bbd20cebbbd92513ced28e1e233c02bf12f29e6 SHA1: e86d7094c16c125f0b1e01c73b63c6d6d5606d00 MD5sum: 24dd2e76ba03e082e4dedd8a99e9fc61 Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: gccxml Version: 0.9.0+git20140716-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12861 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), g++ Homepage: http://www.gccxml.org/ Priority: optional Section: devel Filename: pool/main/g/gccxml/gccxml_0.9.0+git20140716-2~nd14.04+1_amd64.deb Size: 3325384 SHA256: 9af97f1c81de640a9333e44240d75697cd0a7656c80942de3f4f8f7a018ee800 SHA1: 8131af7bfb493eea0f3b2a265155cc87805acafc MD5sum: 82b955e4b4a5b8d7d55967a20f373b30 Description: XML output extension to GCC There is one open-source C++ parser, the C++ front-end to GCC, which is currently able to deal with the language in its entirety. The purpose of the GCC-XML extension is to generate an XML description of a C++ program from GCC's internal representation. Since XML is easy to parse, other development tools will be able to work with C++ programs without the burden of a complicated C++ parser. Package: git-annex-standalone Source: git-annex Version: 6.20160728+gitg9a2fe62-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 409381 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: graphviz, bup, tahoe-lafs, libnss-mdns Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20160728+gitg9a2fe62-1~ndall+1_amd64.deb Size: 29330580 SHA256: ee6f231596dea7c9aab446c5d3d4d5952cfa6081ea2448fa0bdf5756fa8bf9f3 SHA1: 52d51f0e76b54efc50b4bda09762ba15c9844a76 MD5sum: fa784d0d12a63e73fe97f198a775aeeb Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: git-annex-standalone-dbgsym Source: git-annex Version: 6.20160126+gitg65f4442-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 45 Depends: git-annex-standalone (= 6.20160126+gitg65f4442-1~ndall+1) Homepage: http://git-annex.branchable.com/ Priority: extra Section: debug Filename: pool/main/g/git-annex/git-annex-standalone-dbgsym_6.20160126+gitg65f4442-1~ndall+1_amd64.deb Size: 9076 SHA256: df13c8d6accff21cae1128fda8e3626634b54097765c744bda4d814a294a4754 SHA1: bf65febb9152d0ab4b069d9ef9ca4b44fc3ea7fa MD5sum: dc4d8ce99c459c96dd4f4a6d010e02ca Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 75d11a3ee55319e6cebcf33286de8df9a39bcaea 75d11a3ee55319e6cebcf33286de8df9a39bcaea Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libx11-6 Replaces: libglew1.6 (<< 1.7) Homepage: http://glew.sourceforge.net Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 93038 SHA256: 65b460894e0cf44263960f17ea4e04cfa28127aeaf01b324b6af2b1ee66f1435 SHA1: a57c2afe4059f7a47a35f7a5f209582fbdaf24d7 MD5sum: 2ad2377bec59c31a820fe47a55e6cb08 Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the utilities which can be used to query the supported OpenGL extensions. Package: gmsl Version: 1.1.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd14.04+1_all.deb Size: 13800 SHA256: 4127230a0b3a6b132f2e98087b496cddbabf8efd64fb0573ac384d4ec292ddab SHA1: 16ab5cc30564be2024ea5ea282213fc38a320743 MD5sum: 75f0db3af8b2efad55c4794e50b84412 Description: extra functions to extend functionality of GNU Makefiles The GNU Make Standard Library (GMSL) is a collection of functions implemented using native GNU Make functionality that provide list and string manipulation, integer arithmetic, associative arrays, stacks, and debugging facilities. . Note that despite the name of this project, this library is NOT standard and is NOT written or distributed by the GNU project. Package: heudiconv Version: 0.1-1~nd14.04+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~nd14.04+1_all.deb Size: 10218 SHA256: 43684321833fd0cc620b87b9edf3e20f1071e00fbfb1c9d9115a5938f4df236e SHA1: a5a75c8ce1c59b56fc4a82892e034ef636ee2532 MD5sum: 3155ae84167a24442e1810d0d49f75dd 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 13003 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.2~dfsg.1-1~nd14.04+1), perl, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 2), libglobus-common0 (>= 14), libglobus-ftp-client2 (>= 7), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 6), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 9), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 9), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgsoap4, libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.8), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libvomsapi1, 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_8.4.2~dfsg.1-1~nd14.04+1_amd64.deb Size: 3713452 SHA256: 1e54fb3aea060bb015f82aca9e7e03ec3e58d5fc810492882d7fa5ced7cdfd36 SHA1: dfd7b5e291f7686ccef1433551ebfb2480e98b9e MD5sum: 478b9c82c1bd856fa92dee782614c8bc 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 38121 Depends: neurodebian-popularity-contest, htcondor (= 8.4.2~dfsg.1-1~nd14.04+1) Breaks: condor-dbg (<< 8.0.5~) Replaces: condor-dbg (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: debug Filename: pool/main/c/condor/htcondor-dbg_8.4.2~dfsg.1-1~nd14.04+1_amd64.deb Size: 36000936 SHA256: 90809aedb5cb13e8a91867a88f143cf6ca549c2355288e807639183eadfd5313 SHA1: a1a90a0b869da7ce7db62b0af369d53c3c8bdc44 MD5sum: 363a847f0e52c51ed5aca90f3287b1e3 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1670 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_8.4.2~dfsg.1-1~nd14.04+1_amd64.deb Size: 305482 SHA256: 85066c38c073505290c51ff9aaafdc13e94a74c008eab14711d42a5dad7055a0 SHA1: 9bd9b29ab33098f5a1598a01ed00a8117cb7ea87 MD5sum: 2960508af618a5d045324ab4a16c6985 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: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5917 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_8.4.2~dfsg.1-1~nd14.04+1_all.deb Size: 1067822 SHA256: 6d774f6adf7fa696f2bf430fc2c7bd2f547a1e905e32390df9d17611ba626b37 SHA1: 6f58cf5718e706683eef5bfe3f7480522f9ba71c MD5sum: 015a3b775dff163b996768b66d213b33 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 466 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~nd14.04+1_all.deb Size: 175686 SHA256: 93a2cfe442cded96df94ade891d2c9892a0b09d43b4fd86073a479f8ca4ba0b8 SHA1: 18a29af861ececa34319234d1929b3aeb2ff77b4 MD5sum: 34273046bb09d48c5331dd6c982e85f3 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~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 9150 SHA256: 6221480f9dac530be0388cb543cb7222a71f2eeb5a05e3b7684189951be779a9 SHA1: d6e2bc39ee2ea2858d5aa50a8b825dcc1a9766ef MD5sum: 42c1f57576c0b1537c531816653e0f04 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: init-system-helpers Version: 1.18~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, perl Breaks: systemd (<< 44-12) Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/init-system-helpers_1.18~nd13.10+1+nd14.04+1_all.deb Size: 13450 SHA256: 9b738273e06fa645d7746ddcfc18257e82b1aa81991b60f4940c8336ca7c276b SHA1: a69ef0da8cacfe37a1898934c6feb74737e63597 MD5sum: c519d25c91c535528c645290c7201987 Description: helper tools for all init systems This package contains helper tools that are necessary for switching between the various init systems that Debian contains (e.g. sysvinit, upstart, systemd). An example is deb-systemd-helper, a script that enables systemd unit files without depending on a running systemd. . While this package is maintained by pkg-systemd-maintainers, it is NOT specific to systemd at all. Maintainers of other init systems are welcome to include their helpers in this package. Package: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2836 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_4.7.0-1~nd14.04+1_all.deb Size: 2498446 SHA256: ce5b7ee80d764522163321fea16c74d1159642fcb4a74a28f5c51fc9438552ab SHA1: a8a9342033fbc34ed40d182ecfbe1991bc1c9c31 MD5sum: 0abb2152be3c1e64724f0cabcb7be373 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: insighttoolkit4-python Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 844791 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfftw3-double3, libfftw3-single3, libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.6) Conflicts: insighttoolkit-python Replaces: insighttoolkit-python Homepage: http://www.itk.org/ Priority: optional Section: python Filename: pool/main/i/insighttoolkit4/insighttoolkit4-python_4.7.0-1~nd14.04+1_amd64.deb Size: 70486006 SHA256: d01b08707e1a6ebcda9bdd832fae35e134d82af3f8e9fb61fa94880a519c9a40 SHA1: 83b7f2b2d4e73a7affa80bf5a3cffa1c629beabb MD5sum: 5b10b989530b92d62e3e016ab3c50fe9 Description: Image processing toolkit for registration and segmentation - Python bindings 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 Python bindings. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd14.04+1_all.deb Size: 5018 SHA256: 30af8e92d10d414bf87e8c4699a93b2a65aede0538a750d23b741b6c31b1d0f9 SHA1: 026b10c125ea9fb70fd9f19f71d809cf33d4c274 MD5sum: 5fc45130f6fa18505f9de5ab7ee5b221 Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 445 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd14.04+1), libboost-program-options1.54.0, libc6 (>= 2.14), libfftw3-single3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd14.04+1_amd64.deb Size: 123416 SHA256: 680b60b67a081444ac07f6beff38147def498568990a36eb0e659d809b13d07f SHA1: bce3b2b927452c83e3ef7316a6239a249b8232e6 MD5sum: 72290fe783ced0e78a130dfa44085bf2 Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1703 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd14.04+1_amd64.deb Size: 296770 SHA256: 4edb67730409a3128a932e074a40e91b0808d3549a9fde264ea92fbd09ae27c5 SHA1: f2711b34e52a6a4a5e98d3bcb2629bf0bf49c1af MD5sum: 12335bc7b530bf60caab32b1ea9cf7b4 Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig1 Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 904 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-2~nd14.04+1_amd64.deb Size: 276178 SHA256: f21301ecefd541222195af522e1234d9d87569f384809cdb572b2a66e9f92df5 SHA1: 1743333d42fe247a4455111b60985d1e9b5c0417 MD5sum: d38533148d22986ef4b965e8bf1a0f26 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig1-dbg Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 373 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd14.04+1_amd64.deb Size: 75684 SHA256: 8602bbcf5212915f4539ccafef3693d1ab50deefe8323c729780a20814bc9ccb SHA1: 20ee7ecf4fe70e4d4ad9f61ed3ec1d48bf0dd3f1 MD5sum: 96cf527eb495a03a3e8821dd4bea4dfa Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libclassad-dev Source: condor Version: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1377 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.2~dfsg.1-1~nd14.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_8.4.2~dfsg.1-1~nd14.04+1_amd64.deb Size: 235238 SHA256: aaa8eded4a5e5156971a27ebd634c4cd6824fa0fb71e85a7e0757e2317de0a60 SHA1: 09082f7bbcfbe6b03b8e8e26126aa21c5d836a35 MD5sum: 20902a00cbeab41ab9e9fcbcb15e03c0 Description: HTCondor classads expression language - development library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the static library and header files. Package: libclassad7 Source: condor Version: 8.4.2~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 598 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libpcre3, libstdc++6 (>= 4.8) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.2~dfsg.1-1~nd14.04+1_amd64.deb Size: 191820 SHA256: e27fa01f6f2452579a7267c3507b2185f758956be26e5371fa86527199869e1f SHA1: ee826769c80972647024a26ad3dcc1d25cc13f51 MD5sum: d05a1f0b177630f9fcb7d5c6d37f745b Description: HTCondor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libcnrun2 Source: cnrun Version: 2.0.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 297 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.6), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.0.3-1~nd14.04+1_amd64.deb Size: 76782 SHA256: b44a154d97d55ba5cf8a1e1ba7d2e8ee5fb765c9c7827d06f037c741c6a021c8 SHA1: fda74e2e54b09323250fc978f49eea7fbf0bc304 MD5sum: 2d0e48d6d62c84f199c091c148e56d88 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.0.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 167 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.3-1~nd14.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.3-1~nd14.04+1_amd64.deb Size: 21254 SHA256: 30561c6b7a9d395692427d2f06642e6c2a1c28ba093ea4b921c6ba83dceba952 SHA1: f0038a62cd3c2a6e9807f2fab7a68a8468aa41e6 MD5sum: 168a19dde7baceca399a55af2b72e6bd Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7667 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), libfreeipmi16 (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd14.04+1_amd64.deb Size: 910378 SHA256: f4d8cd9315be621883888bc76559e96d55e7a72f6c2d346eb31b0e1dcc42e646 SHA1: 714f36dc00b272d6fb0043efcf9c272d14668e93 MD5sum: e02682f4fa21cf5b4ebff5be97d6fdb0 Description: GNU IPMI - development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libfreeipmi. Package: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5039 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt11 (>= 1.5.1), freeipmi-common (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd14.04+1_amd64.deb Size: 814430 SHA256: 3e872a9b60833f36eb925f47f1589f339b26fec86c943512dc836c8f4cb46076 SHA1: 6799ddef2200975c638d902e0b72844f1b194ea4 MD5sum: 21c97b3a609eefbd749fa2ddaf85d17e 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 280 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.14), libfreenect0.5 (>= 1:0.5.2), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 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~nd14.04+1_amd64.deb Size: 54172 SHA256: f53c9dade6037dfe0924ba21f318d353aaab26b431406cab4a3a8a7f440216bb SHA1: 202473f3090176da4b983832797fc11364ceb349 MD5sum: 3c85b2a4446b646fcfc9c1258cdce2f6 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~nd14.04+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~nd14.04+1_amd64.deb Size: 8664 SHA256: 6232b49f57178bf0ca72147efc7307651cc777755bdbc16c9904762ea31c11de SHA1: 5087fd2279d72ab269ca0d94dd8cb364bfc80ef7 MD5sum: e15c173a0b092f79fe2e3828788f6fec 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.3-1~nd14.04+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~nd14.04+1_amd64.deb Size: 19434 SHA256: 26b7c10c30e755c86c98aaa4eac96c0cb129776517a699ef5870af48b92e1079 SHA1: 81a5fa3b23d5e162bd9a4c29d3294b41c5bc3cfd MD5sum: 760c451b21c91951367c14b2c5cc533b 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 677 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~nd14.04+1_all.deb Size: 92014 SHA256: 064146257b1c0cf6dfa96e77798278903cfa4733476bfd174ba941afb1b8c52d SHA1: 024619574042575fc101f79d8b57e876a7b4fb65 MD5sum: e429a46c5c5ecd339ff069594169ba2c Description: library for accessing Kinect device -- documentation libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the documentation of the API of libfreenect. Package: libfreenect0.1 Source: libfreenect Version: 1:0.1.2+dfsg-6~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libusb-1.0-0 (>= 2:1.0.8) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.1_0.1.2+dfsg-6~nd14.04+1_amd64.deb Size: 30900 SHA256: 3014bd91b27661b8e78e85d88b79ad57843f9597a340d67f4df1cede160ad936 SHA1: 31dbd78d5e219b8472a869aea03706c971523dc6 MD5sum: f427bd0a8aebd1daca206c522752b725 Description: library for accessing Kinect device libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the shared library of libfreenect. Package: libfreenect0.5 Source: libfreenect Version: 1:0.5.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 154 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libusb-1.0-0 (>= 2:1.0.12) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.5_0.5.3-1~nd14.04+1_amd64.deb Size: 41930 SHA256: 1e9619d6d189cb2276981117e7b69749949d07a46ffff9da23844e083411de02 SHA1: 4af7c6f60f4d9649f7e5e5b98e04d319aa6689ce MD5sum: 3aa4c80a5c0595948b2bce42fe380a0d 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: libgccxml-dev Source: gccxml Version: 0.9.0+git20140716-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 556 Depends: neurodebian-popularity-contest Homepage: http://www.gccxml.org/ Priority: optional Section: libdevel Filename: pool/main/g/gccxml/libgccxml-dev_0.9.0+git20140716-2~nd14.04+1_amd64.deb Size: 107100 SHA256: 200c18fdcf1e0114495b49e67e6e3ed5158e77f738eefe3180ec04e901118b56 SHA1: 637f5633a7bd5e40c097e9038c141920343730b1 MD5sum: 058fe330a9f1e961fa7d38faac4955ff Description: Libraries for building extension to gccxml output There is one open-source C++ parser, the C++ front-end to GCC, which is currently able to deal with the language in its entirety. The purpose of the GCC-XML extension is to generate an XML description of a C++ program from GCC's internal representation. Since XML is easy to parse, other development tools will be able to work with C++ programs without the burden of a complicated C++ parser. . These libraries are part of the GCC-XML tool. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 632 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Suggests: glew-utils Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.9_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 132134 SHA256: c9d01e14e16796de8ba59168f5e2aca780f731df4569da1fe4c3427ce2ed47ef SHA1: f7d204cecb486680a636592eee7c5020f9af12bc MD5sum: 4c2d98b5e4c71f0d37adbcd029e55a88 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 33318 SHA256: 39cb64ee10450cb843cf341cfed96a6ae490a2fb91eaf50d2459ea9a5d156b97 SHA1: 60942982c2309725027facd8cd61e1d8b6a8ec8a MD5sum: 6e2d32defc57216e0a5885c9b392f8b0 Description: OpenGL Extension Wrangler (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglew1.9. Package: libglew1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd14.04+1), libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.6-dev Provides: libglew1.5-dev, libglew1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.9-dev_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 109474 SHA256: 630cf44db5cd23c0b913225331431705c58e310f293b7b8cbc40f4d6f32f9bff SHA1: 2ac1f8b231e6bec9f937cc4a4ebf672fb17c24b2 MD5sum: 5023d2f6c7dc5fd7afd46ecdf1e2e7b8 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development documentation as well as the required header files. Package: libglewmx1.9 Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 555 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.9_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 119768 SHA256: 615f9882dbefc47d58b33c13b1fb40573606ae61d3d9e0527ef23ed201acb217 SHA1: 758dfddec881f59d3389baa2949679ef803c74b3 MD5sum: 599349c7537898948cc5c8ba52c53858 Description: OpenGL Extension Wrangler (Multiple Rendering Contexts) For more information about GLEW please refer to the description of the libglewmx-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 122 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd14.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 26922 SHA256: af29d359e95ef29914bf80431b89c58dbb22dacec1c02261e007a9a4c93309dc SHA1: 350a78d68ae9a41dd06343c4a5482d2e30285b6b MD5sum: 42bdd9efa582d1267576c2540be87444 Description: OpenGL Extension Wrangler MX (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglewmx1.9. Package: libglewmx1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd14.04+1) Conflicts: libglewmx-dev, libglewmx1.6-dev Provides: libglewmx1.5-dev, libglewmx1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.9-dev_1.9.0-3~bnd1~nd14.04+1_amd64.deb Size: 8464 SHA256: 540da779ac116c49b30950b1188b32cdc087e8245e5b32de7fdd33cec0c2ef96 SHA1: f382c52feab3fd897d893b91c948d4481a6646f8 MD5sum: b301bc39123594c1dc7e7f1dd44b24e6 Description: OpenGL Extension Wrangler MX - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development libraries compiled with GLEW_MX. Package: libinsighttoolkit4-dbg Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 41862 Depends: neurodebian-popularity-contest, libinsighttoolkit4.7 (= 4.7.0-1~nd14.04+1) Homepage: http://www.itk.org/ Priority: extra Section: debug Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4-dbg_4.7.0-1~nd14.04+1_amd64.deb Size: 37203754 SHA256: c7fac13a0c48fa1dd8ade8e126c839d7e2fcb0d061f9561dd2086f0c8153ca0a SHA1: d817c2250eeec9e42c189cfbcbb8cef689791b99 MD5sum: 35ac6fda2167940e9b320dec48dfaf11 Description: Debugging information for the Insight Toolkit 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 debug files of the libraries. Package: libinsighttoolkit4-dev Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 25287 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libinsighttoolkit4.7 (= 4.7.0-1~nd14.04+1), libstdc++6 (>= 4.6), libgdcm2-dev, libdcmtk2-dev, libhdf5-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_4.7.0-1~nd14.04+1_amd64.deb Size: 2934016 SHA256: 8105515de41410d74ee319b0d17e5e45556982adb09dc5f55198b994240b5aeb SHA1: a5d5e44f4cc1db4c4017c8137a6fa73e5ecfb151 MD5sum: f7d56d956e83907d30712cb2769c3ae4 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: libinsighttoolkit4.7 Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22211 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfftw3-double3, libfftw3-single3, libgcc1 (>= 1:4.1.1), libgdcm2.2, libhdf5-7 (>= 1.8.9), libjpeg8 (>= 8c), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtiff5 (>= 4.0.3), zlib1g (>= 1:1.2.3.4) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.7_4.7.0-1~nd14.04+1_amd64.deb Size: 4377930 SHA256: 3985dd338980b0ab107242fde85b651a98928c48251ec9b513100be6a90435f4 SHA1: 5388f1623b0be5170c7b7e4d9e2671f1105429c9 MD5sum: 507715e949e9fae2585f3b794988a4ab 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 496 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), libipmiconsole2 (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd14.04+1_amd64.deb Size: 98462 SHA256: 4965d52e9e5d7f286e7c27d031af8806b1d11be84f27f92bcfdedfd048846dd9 SHA1: ec2907812e6e62a1d5db1b939e45a222bf0835f2 MD5sum: 3dbc2698356ce9957f3d0ed276e70ef9 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 246 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd14.04+1_amd64.deb Size: 82754 SHA256: 68d2f2a0e87af93a98bd466e918b88664992092729e56898ec857cfe50ebe177 SHA1: facf9e5409ac74880b5f8b9cadc0ef4a12411ffa MD5sum: ddc9a5f34cbe8cda14fdb6c805f9fc49 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), libipmidetect0 (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd14.04+1_amd64.deb Size: 31016 SHA256: 85cee788e7df2d80cf6bd4682b8cf989bc7dac1e552036e99d8acdd6546e9ba1 SHA1: 16f72e47b20fdf1e1d898dc29581715cfb291224 MD5sum: 49e924eb9138ed2e1178f3878c6fda67 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 60 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd14.04+1_amd64.deb Size: 25100 SHA256: be870f8e2165fa8ddbbed6765c999ab783b7f23c6231bd40c79e9ad9d0855cd8 SHA1: 5d710ec2cf81ae229df27967e96c6f71efea40f6 MD5sum: 27d93b14dc01a54ac7a07f986dc00b34 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 301 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), libipmimonitoring5a (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd14.04+1_amd64.deb Size: 59916 SHA256: 31cebf1d7971578c126f309d7c2488d55e151a46892bd61f4bc9d1a9ccf72c35 SHA1: 4f03a2f048b3947f5c2bd2fb97e59e54283a16c9 MD5sum: cb63d77f5a99f3ed4467f1ba4c681497 Description: GNU IPMI - ipmimonitoring development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmimonitoring. Package: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 115 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd14.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd14.04+1_amd64.deb Size: 41798 SHA256: 8c6838ad7ac7ca4fdb9f45662d43304077df296d4a45936b7e8ea573eb3ab506 SHA1: bb3155e0db0fb422d05d69dcabfb9e31180492e8 MD5sum: a5855fe5c0470f2891c4eaaed7d453d9 Description: GNU IPMI - Sensor monitoring library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for sensor monitoring. Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd14.04+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd14.04+1_amd64.deb Size: 13802 SHA256: 4213c3282eb5c1a3a960e362db254b3961d29ac672419b4facfb30eac74b2c32 SHA1: cc924adadbd72c7c8df045f236e14fd83e32740a MD5sum: c60dacf3ef2f95f249d5bc2f39b6fcf2 Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2003 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd14.04+1_all.deb Size: 148632 SHA256: da7fb8cdacb033da65e02cb52138088d8feb3a83d26e0ebd9525d7c554661c1f SHA1: d996863712189c004d651b50fa974c1f852401a1 MD5sum: b4dac15a86155424c1c2cbcf61d975f2 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 361 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libhdf5-7, libpugixml1 (>= 1.2), libstdc++6 (>= 4.4.0) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd14.04+1_amd64.deb Size: 80318 SHA256: e62bcb3a5d5e6ea16b625973f3d2349a7bb77acf67cca58473b77ec61326fbf7 SHA1: abe1ecd2b6eb50f4ea6e1fc3394ff17ee1f4dd27 MD5sum: b2b80413c32affa4e4c2040a25d66631 Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24649 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-single3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp8, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 3734542 SHA256: 981545de2b73a039eb9073bf10bbb8c0e425343a5edb704b2fb141b6c0d69fe1 SHA1: fe67413e2998e17403c9163b81135e28259b0ad9 MD5sum: 54df8b6868cac79254b79ef059d59c31 Description: library for 2D and 3D gray scale image processing libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. Package: libmia-2.0-8-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67813 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 61603414 SHA256: 7ac528603e32723704cfebbc007b20b71745ee852b60e1d5685846e27159b703 SHA1: e12d914bea050a7b92fed6e197863fb29a918100 MD5sum: 195fe8e8322d6d67b62941f0379de88d Description: Debug information for the MIA library libmia comprises a set of libraries and plug.ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. libmia is library for general purpouse 2D and 3D gray scale image processing. This package provides the debug information of the library. Package: libmia-2.0-dev Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1087 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1), libxml++2.6-dev (>= 2.34.1), libitpp-dev (>= 4.2), libtbb-dev, libgsl0-dev, libboost-all-dev (>= 1.46.1), libfftw3-dev, libblas-dev Recommends: libmia-2.0-doc Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/m/mia/libmia-2.0-dev_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 170596 SHA256: 5320ef58eb4af06b42d24ab07eaf7c6ddc3f34e79c6dd662a9b108986498886e SHA1: c5b98a8c4b87ff8c0eb34fe7ec488ca1132bf91c MD5sum: 8c93b580ebdf71723b3856c55547be24 Description: library for 2D and 3D gray scale image processing, development files libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the development files for the library. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14003 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd13.10+1+nd14.04+1_all.deb Size: 828262 SHA256: b80877b4eb7ac26a8d128219be2df273b0d1115bdc039118aa39f0928a03a878 SHA1: 4f2d66594f12e0670fb739d4c7333bd5ffce4b44 MD5sum: 4880b2c099431c4b8afaa3e78dee6e67 Description: library for 2D and 3D gray scale image processing, documentation libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the Doxygen generated API reference. Package: libnifti-dev Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libnifti2 (= 2.0.0-2~nd14.04+1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-2~nd14.04+1_amd64.deb Size: 136386 SHA256: 5d3b9339c30c1b37e93d8d1e733884d17a28843c2c890594f99802028b172b6e SHA1: b091aa4daeb8854a3fc9ebfc2e5b4b370d3b5625 MD5sum: 447591c46fb42def7965b9647477f7a1 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1675 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-2~nd14.04+1_all.deb Size: 137676 SHA256: 3bab4349c0f35948663f799794b88328b12952dbb9eadb0e8a4085c0f270a5e6 SHA1: 8efa4c33a93f08cd665a505ac7aa01ce2a943db6 MD5sum: b29b153538f23cfdeddd32fc9dab6436 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 298 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-2~nd14.04+1_amd64.deb Size: 104646 SHA256: e93ecf3b7204191022fbc826cd7b9d6eef51696a51c941ea4e810d7a88d07068 SHA1: 4f8cc483b111bf5c27ffaf3bad6e20ae4cd0c954 MD5sum: 31adf0822b3af48f98e47e489f7fdcc0 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6371 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.54.0, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph99, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1226316 SHA256: 609321d47fa9bb92fe3c847c3de68ef910dfa3ca650317df024a661cc5c6ff60 SHA1: e341ef3c136c37f5bedd103d1eb3c3a100cd935e MD5sum: e8d30adf4f894a6cf74ea2d4530bb2bd Description: Framework for multi-modal medical and brain data visualization OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 3.0.0), libopenthreads-dev (>= 3.0.0), libboost-dev (>= 1.46.0), libboost-program-options-dev (>= 1.46.0), libboost-thread-dev (>= 1.46.0), libboost-filesystem-dev (>= 1.46.0), libboost-date-time-dev (>= 1.46.0), libboost-system-dev (>= 1.46.0), libboost-signals-dev (>= 1.46.0), libboost-regex-dev (>= 1.46.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 248388 SHA256: e1979f9ff461e4bd26b952e587c879464abc8805dde53b924226a1ba9957d869 SHA1: 8c707227d4e9a7783e77c11be320df628235fc84 MD5sum: 035d7cfb0b5854d0eff0e3f0039076a8 Description: Development files for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48075 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_all.deb Size: 2673508 SHA256: 6bfe8da2878784c3df24ef11993ad9d5b82019204eb362235bd094ac6865c0f8 SHA1: 714ad73ca23e5c34f65c7632c395534c4baf7898 MD5sum: 5f8cbf8fba45be0c2da0d39481c9c931 Description: Developer documentation for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 141086 SHA256: bb6124e7796fb2ec46a74995397dfbba18312339ec0fe849049b3b5bad060be3 SHA1: 116a59cad5a4eb2d9003e5e76551b38398a4e22b MD5sum: b2061aa60168de0aaef2c3828f277f14 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 141822 SHA256: f4b913b3478d86cb08b8d3a2869e1636a68e516d4f49df98c0c622b8ab3a9925 SHA1: 9bbe3595d3c1bbf9a3ca4db616135dc92ed9a942 MD5sum: b5eaf8376256f9d11aa3ddcd0ff7bc4d Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1311 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 325046 SHA256: d7007f17f588ef2f5e750af1c6cbff2e208445bdb6520bbfe25a92dc002edfd3 SHA1: bef37b08a1545e5a98c666e3d9fb32ba4c52657a MD5sum: 25d6934e9b0a01219311a6a8c86de7d3 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 105 Depends: neurodebian-popularity-contest, libvtk-java, 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~nd14.04+1_amd64.deb Size: 37910 SHA256: 28483c6ef7a28b52486b5eadb313ee73d21e2d81298b34b3db79e7ebd8f18d69 SHA1: f44b62796e398c36dc3d71510e75bd0a3f1604f9 MD5sum: 0545431b3ff4ff609b16e785ddf928ef 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1707 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libstdc++6 (>= 4.6), libvtk5.8, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd14.04+1_amd64.deb Size: 427228 SHA256: 619acdf6506535f9e4f8776f363353d9205fccbf2b99a5bcf305606424dcfe17 SHA1: 369032e6c9d7aa4099e55e7eb9f7246244663ff6 MD5sum: 1c226a6faa45072a7e02c4a0d46837b0 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 531 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd14.04+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~nd14.04+1_amd64.deb Size: 80790 SHA256: 0abec8f82af0d49ef0e9146dcb64bfff2576a05b75965ecb06d94db63f826b09 SHA1: 87890255b0a5a3db32f091af6ef98ea1af6eb0e3 MD5sum: 72649df1bf66f26b1fd07d54e0d30b5a Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.0.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.0.3-1~nd14.04+1_amd64.deb Size: 38486 SHA256: b999b6aae4003b2a1e9de7aaf859d96c3ac731166811efe5487c7b6f65be5af8 SHA1: 9ab1ca7c06800c0662b14a2f2cf9fb312648a897 MD5sum: 89a8f34778bbd335e5989aae9221746d 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~nd14.04+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~nd14.04+1_all.deb Size: 7520 SHA256: 306f62724d477630ccc2dfec6de9087b8453f9f7aa47f3fbc994fc4c43b72ac0 SHA1: ebcd6a3887968b987548d284ef4398e4b7403402 MD5sum: 4ebc4831c36822a6b9606d0c7b735787 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~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8458 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1), libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1438058 SHA256: 4175b7c0f2fc73d3100e6f0f05e946c559120697c9f092ff25fb2d7c59c02245 SHA1: 4674acee003cf4f21651daa385d4f6fbc19f550d MD5sum: 70ea147c6b5bab34fad8f1b2e394e3c3 Description: Command line tools for gray scale image processing Command lines tools to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29921 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd13.10+1+nd14.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd13.10+1+nd14.04+1_amd64.deb Size: 27660152 SHA256: 2cb6d437d0283d982b4a69681b6fd85b49152794f3780d90bda5b70ed705c39c SHA1: b034979d96b59da1e938cc6099f0a6aceb4af28d MD5sum: 47578d4bd436714a8b039345556cde28 Description: Debugging information for the MIA command line tools Debug information for the MIA command lines tools. These tools provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1138 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd13.10+1+nd14.04+1_all.deb Size: 71894 SHA256: be1b730b60e4e46c09f731c458418f51468a54bd0bcb30c1b3ae62895cf5195c SHA1: 13b72c29850c963b4b7163d5728101f262982fad MD5sum: 68aa342ecdbdd76b549b62f3a8a0cefb Description: Cross-referenced documentation of the MIA command line tools Cross referenced documentation of the command line tools and plug-ins that are provided by the MIA gray scale image processing tool chain. These lines tools to provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes interactively from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statistics over images. Package: mriconvert Version: 1:2.0.8-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5264 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase3.0-0 (>= 3.0.0), libwxgtk3.0-0 (>= 3.0.0) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.8-1~nd14.04+1_amd64.deb Size: 776018 SHA256: 64022f90bcd940aa85f44204824579a50ddd72110bd33e1d48cc673b1e59de1d SHA1: 5015fb67258a340cd715bffc90d7d1dc8e92231e MD5sum: 301d6d0f1f037d166c7f3f267b7c3208 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 16024 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Recommends: pigz Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20140804.1~dfsg.1-1~nd14.04+1_amd64.deb Size: 2205714 SHA256: 471e4b106f893910fb05163a0ed70cf8550005bfdac8f15b689dc8d487401127 SHA1: 7db3a7a792d8498328ca7a7e4d02123f18fe6fe8 MD5sum: 262c81c3fa6e174ea44c25a69a5a7ae6 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1708 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd14.04+1_all.deb Size: 1658672 SHA256: 8c6fbf4d4201736009058951a8b0a0649b14eb2b31222086e4c40337b7b701fb SHA1: d390758dd46655f60156a87578c4e8bde2f62f7f MD5sum: 5c2f269adc054ae2960074a3cfec33ba Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1019 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd14.04+1_all.deb Size: 577154 SHA256: 99c69da1658d3ad0d38a2e617b99c1e97b6dd659de73b4d17de6abe2c836bee6 SHA1: 40d30c9da283129d64c2490423bc06de65605f3d MD5sum: 1e4972d196978a16b51c6ab0b5170a0b Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mridefacer Version: 0.2-1~nd14.04+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~nd14.04+1_all.deb Size: 637348 SHA256: 4886e1aec5e9f3f839fdd2784eef4113eb90cd82ecdd9a4966d4d2eecf48e091 SHA1: 1feb4d5652dbc9bea40667c98ba830b8e31fa69b MD5sum: e7e127d2deea7a141e45d8ebee81107d 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~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 8802 Depends: neurodebian-popularity-contest, libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libsigc++-2.0-0c2a (>= 2.0.2), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.12-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1300186 SHA256: 551f98c5ed01a892ef30be69dd2632ca751be0a4c51bd2663478342ce4c981fb SHA1: e4faaf5483942391f9654b34ab335502b8112873 MD5sum: f543ec275d3ade8d4abf6e9d3f90a694 Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.12-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3490 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.12-1~nd13.10+1+nd14.04+1_all.deb Size: 3191882 SHA256: f32e1267d094094ab3cc0c0dea48e1ccf69fe473877e2e60136e4e6a27db354b SHA1: 31f466b044fd9b37817cda76e708ae9f65413a1e MD5sum: 391268dd332daa65f1524ad5d28fd893 Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: ncdu Version: 1.11-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libncursesw5 (>= 5.6+20070908), libtinfo5 Homepage: http://dev.yorhel.nl/ncdu/ Priority: optional Section: admin Filename: pool/main/n/ncdu/ncdu_1.11-1~nd14.04+1_amd64.deb Size: 37588 SHA256: 23e1c897de8ec7e32782205afe49bb3fee6c45a99a9619116087536e7e510d51 SHA1: 1845d5dd9a60ea3439c1a1c59d11c9377f76004a MD5sum: fb8cdb7032ecb507f84ebb4d1708d66f Description: ncurses disk usage viewer Ncdu is a ncurses-based du viewer. It provides a fast and easy-to-use interface through famous du utility. It allows one to browse through the directories and show percentages of disk usage with ncurses library. Package: netselect Version: 0.3.ds1-25~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd14.04+1_amd64.deb Size: 30902 SHA256: 85bcc0cb531b5e144101ecf8b3356e798ea1e256a212e6a395fe67f1191735d3 SHA1: d445f87a02a6be7f46662b4062087edb12adc3f9 MD5sum: 31e70fcb2d00e772f027e762c0d3f2fa Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd14.04+1_all.deb Size: 16732 SHA256: 6736e45053839e6ccff6ae6acee08c1b6946082a3551db89f5b75cf011f56942 SHA1: 5459e0e22973aeac24902aeb831afaca776152d2 MD5sum: 27d1f7525d5b1676fab50f43523897b3 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.4~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 112 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_0.37.4~nd14.04+1_all.deb Size: 33158 SHA256: 7dbab3849074592a24d14505a34706635835eb275297011d7f759ff9cc16c7d0 SHA1: ba952d94fb9da1e08189966d23c01c5c637577f3 MD5sum: b571a53854b09e20c256e9d070958556 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: 0.37.4~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47 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_0.37.4~nd14.04+1_all.deb Size: 10158 SHA256: 37103a8438fbb474612330926c9c5a4b0f4c76b0c184b9356c9ce46c1fb5af78 SHA1: 596ca175299596ae1e5a2fb6f338fc6c1fc50435 MD5sum: 653b913b548c36903cc83a1d491e42fe 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: 0.37.4~nd14.04+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 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.4~nd14.04+1_all.deb Size: 116182 SHA256: a600f37341160010abee96acaa86917c1cc7b9c35ed8b4caa5d50c4af016b14b SHA1: 868f918b560fd3bb8fa6eee4d58f12d857ea8192 MD5sum: 2d36e3d641ac89859d417cbcf20e34a7 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: 0.37.4~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 139 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_0.37.4~nd14.04+1_all.deb Size: 32506 SHA256: ffbc60ace270312eba3cd46be3af5f82fb118b5b1ae86a053eabc068ca6ce2bb SHA1: f70cda066b99c7c2aab3757ea8d1fb841898cc66 MD5sum: fea9398f3d3003e1208f492aa5b71776 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: 0.32~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 108 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd13.10+1+nd14.04+1_all.deb Size: 14088 SHA256: 97679301db4c313bf776a5d18ff76e0b1af04b77da1156d1b500a56e308379b9 SHA1: 0b00e3321e0d1bc70c40437abc74430adcf4db07 MD5sum: f3f984c91e04f7b9ab57e22d1bb1af9b Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.32~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd13.10+1+nd14.04+1_all.deb Size: 7470 SHA256: 8da1af69542f153184f6d344861f1557e1a7a783b6c0b6d90b67e8dee8a855e6 SHA1: fc17ac754d0a08a79a0b1615c6ae10dcd89f36ea MD5sum: 341bf775ee30c2071e1c49a1acf6f88e Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.4~nd14.04+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_0.37.4~nd14.04+1_all.deb Size: 12190 SHA256: f6e03c9e34d591312c6234848faa98db9c115a919b4aa53db52c89f1e1826e13 SHA1: d5dcbba2f28b7e551c91743b3f8108a78ce0af20 MD5sum: 859bda3cf2b37d755b1e213b10e769e7 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~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 176 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-2~nd14.04+1_amd64.deb Size: 55030 SHA256: cc5d92fdc77db140778d10fa11b5be665d4ae7faf54ff5f11b54702233bad5ac SHA1: 0d232196b8834b814ad82fe1a16fea494d5dcd76 MD5sum: c631cf7ffa6357a737832af18b7da9cd Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2231 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.8-1~nd14.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.8-1~nd14.04+1_amd64.deb Size: 333798 SHA256: 2e9d69cd17909b449a522ecc2f68f64bd477423aa664f70f765e3233556417c3 SHA1: 913f8a536decdd3ecddc47020b528ebc07356e85 MD5sum: 936334bcabdcd45977fe4d9dfb3cfa06 Description: convert 3D medical images to DICOM 2D series Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package includes the command line tools. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 606 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.8-1~nd14.04+1_all.deb Size: 615402 SHA256: 5c0c4de741d502aed671afa90ffd5f9d83bbb8d9b8fe3fb61e87a83207c51387 SHA1: 1e2cfa4676c02305b4cf2b7c081125917e51667b MD5sum: 35e250c61104ee3c777aa9d7ef48b08f Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nuitka Version: 0.5.21.2+ds-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2911 Depends: neurodebian-popularity-contest, g++-5 | g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.21.2+ds-1~nd14.04+1_all.deb Size: 612330 SHA256: c8ebb7ab24c0fae47ea782d135120f1428e3389858849ff588f2b8bd457a139b SHA1: 014a9a010488864341c6289b1414d8603779941a MD5sum: 9b0dcf878e94cc59eeef96b5c7ba58b2 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.14), liboctave2 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd14.04+1_amd64.deb Size: 19224 SHA256: 8b16a8d3f52e3158b91adba7cdd3383df180e9cf82e817ec333d8aa72eb21be0 SHA1: 97f4330a118fe8bfb5274f559a25110435b526d6 MD5sum: 98ad6970b192528c19897bf0b69c11a8 Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4594 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.0.0), liboctave2, libopenal1 (>= 1:1.13), libpciaccess0 (>= 0.8.0+git20071002), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.12.20160514.dfsg1-1~nd14.04+1), psychtoolbox-3-lib (= 3.0.12.20160514.dfsg1-1~nd14.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.12.20160514.dfsg1-1~nd14.04+1_amd64.deb Size: 899360 SHA256: cfc7425333103be5c17bf73ad80f09237333e7f58b91a73ec9bf46f1b4625844 SHA1: 9d308650b4c955a50edbaf76482f85849e439df1 MD5sum: 4c6aed73373ae0d5157c429ae1f076c5 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: openstack-pkg-tools Version: 52~nd14.04+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~nd14.04+1_all.deb Size: 52286 SHA256: a4df7374f259be2c071c76914b8360bb558b4312d78d890aec9c6118324a87cc SHA1: 19ba62f52e16fd00f449f4049759a8873f5a2b81 MD5sum: 9d4b190d850abd2a8956ca7a14f57edb 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: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19512 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph99, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 3331020 SHA256: ac0352d0c0475b930bdad2f3733fb5b4c6aa9cc1c90e1c07e5eefa7db7bcc976 SHA1: 1205548c7e07fc9ce38ca584665b5c4ec9d5721a MD5sum: ff72e5fcf6b957018732a1eb23d980ae Description: Loaders, algorithms and visualization modules for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1955 Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-program-options1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libopenscenegraph99, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.6), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_amd64.deb Size: 733244 SHA256: ed0d1ebf8644abd66f1d5e249319194cd42d32b4e20861a438c1438bdc0cbf81 SHA1: 1bab7b90c4d01b7c7d7408dbcc7828d55c0b9183 MD5sum: 9edda61cd48fb5debdf4be31ed0ffd0e Description: Qt based user interface for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: patool Version: 1.7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 154 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) 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~nd14.04+1_all.deb Size: 32710 SHA256: b55a4dd7d4b6fcae897c79098ea6c7fc3f44db099ae976bfbc8c2fe0e90e4023 SHA1: 9d8e823445d7bd29dfe4977ec96c5443660117d7 MD5sum: 7c8650415068489375b6a4744b344781 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15239 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-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~nd14.04+1_all.deb Size: 6139662 SHA256: 3d8762b44b5c77b4400a1c50764d575806e7889b8a3ec091aa1e7f89d392c649 SHA1: ff4b55dc30099dba80b0d0a269957e0e3058be39 MD5sum: 48c612f217f0d00154e7bf9cb8d57bf6 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 220631 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.12.20160514.dfsg1-1~nd14.04+1_all.deb Size: 24198142 SHA256: 0144d9a6b3ca329a09b78e4533770e8b8a61a93399be68c8aaa0488a485fb9e1 SHA1: 7ac8a4f3e6d51668b47052ddd982cd135bcd0456 MD5sum: 9e5c29289569e230e34f55b89bd3cd24 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3764 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.12.20160514.dfsg1-1~nd14.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.12.20160514.dfsg1-1~nd14.04+1_amd64.deb Size: 719788 SHA256: 1608159f9e9352337b284bf6f01f523fe5ad39a20c193ff75bcfd77240023666 SHA1: ca085b08f334ba861389134a98281ba7f82091bb MD5sum: bc2db8abc040381661aa59d50b5b3b90 Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 222 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.12.20160514.dfsg1-1~nd14.04+1_amd64.deb Size: 72080 SHA256: c5d4fe29add82cccd76359586e6c565eb39d9336085c64d220a26d9579a71064 SHA1: b51e32730356f8e681e19dd91a9195d0b3eb5621 MD5sum: 5f885cb44bed6f75c8f9e134d8b0bc3e 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd14.04+1_all.deb Size: 24554 SHA256: d5cabbc1905eb2d7ea5f55e77e97716ba9c00b77df63e9898b994ac7d61ca0f2 SHA1: cf9bae80c9fd4f1a7b8e350fbd2aa88d1a58a236 MD5sum: 7324a2d86401f52c399054fb6e46effc Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.14), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_1.4.1-2~nd14.04+1_amd64.deb Size: 42992 SHA256: 56fe63181011cc89cf812470f9f424c2e5d3a7be9f0ae42a7586237678ad8c24 SHA1: 79dce476e94e3b154c2d496dd6e08993fc69d79b MD5sum: 2eb1c28c443f76e5712fe80018363fef Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2449 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-brian-lib (>= 1.4.3-1~nd14.04+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.3-1~nd14.04+1_all.deb Size: 401994 SHA256: f5134e5254775f86b341da337f269211f4f57b6a6d000f2c1379a46f34a3d69f SHA1: 3cb36dfc2d17dfadd13dae4498e5d6e81ea9c35a MD5sum: 1c64dd142a5972a930f1f894b6feb127 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7021 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.3-1~nd14.04+1_all.deb Size: 1985046 SHA256: 16712a925e735cb2152f8f06887d85f19cd2f596a8b257ab0f3d8946c7e1b47f SHA1: 3cd8e0dc358b894b0e8c9af157a4d40f303577a1 MD5sum: d37f6f42d788d3674072ab728bb407da Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.4.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 192 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.3-1~nd14.04+1_amd64.deb Size: 39958 SHA256: e763499865b7b4c873f070604da09d1ec83d87e32e33410d9437e5c5f78892dc SHA1: c763601ebe9f56fef6ac3d019cd7d81148a690db MD5sum: e05ba0c08740ab3b47424895d981b11c Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-citeproc Source: citeproc-py Version: 0.3.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-lxml, python:any (<< 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~nd14.04+1_all.deb Size: 80330 SHA256: 5b5f6be622f54003050fb0f8a663cf3aa8a7f97366b5ea77b57533b8c8f07446 SHA1: 8decfdd25deee813d966d6406d9dd709e9995c5b MD5sum: 454929edf434ef2e5af0a46e869c0dd7 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python-contextlib2_0.4.0-3~nd14.04+1_all.deb Size: 8664 SHA256: 0b7d2e2de082b5a6fd9cc18b1a1141ce13073a3012289ad768da93e3a9ae0b70 SHA1: 28c6d174d1c27f1e81bdbfa47a91232246ece17d MD5sum: 1a277de9fb763099abadab3313179e1c Description: Backport and enhancements for the contextlib module - Python 2.7 contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 2.7 module. Package: python-datalad Source: datalad Version: 0.2.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1375 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160425) | git-annex-standalone (>= 6.20160425), patool, python-appdirs, python-git (>= 2.0.2~), python-humanize, python-keyrings.alt | python-keyring (<= 8), python-keyring, python-mock, python-msgpack, python-tqdm, python-six (>= 1.8.0~), python:any (>= 2.7.5-5~), python:any (<< 2.8), python-boto, python-requests Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-scrapy, python-testtools, python-vcr Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.2.3-1~nd14.04+1_all.deb Size: 254974 SHA256: e2d637d97a9f2ca4549901bf4c757e17fa67efa2dcd0e7cf52875a292ac0a0e8 SHA1: 6ee8671f388a1d4d1820b1c261fa6a975ebde966 MD5sum: bf8b3604f439a920585bada66ccfa814 Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming for neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare or update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of datasets (search, install, uninstall, upgrade etc) . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling and testing. If you need base functionality, install without Recommends. . DISCLAIMER: DataLad is Work-In-Progress and this package is not yet for regular user consumption. Primarily intended for demonstrations and development. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 515 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python:any (>= 2.7.5-5~), python, python:any (<< 2.8), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd14.04+1_all.deb Size: 78266 SHA256: 7a23acdf2448ad1c837600309ef4412059656d6bf9cad8e40fa5a25a48f8b9cc SHA1: ce40c5fa0c77453a2031a77c09afd13115749d80 MD5sum: e7c62e3fb270103f855d7c836bc61486 Description: DICOM to Nifti conversion DICOM to Nifti conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a Nifti header extension or written out as a JSON formatted text file. . This package provides the Python package, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dicom Source: pydicom Version: 0.9.9-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1522 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://pydicom.org/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.9-1~nd14.04+1_all.deb Size: 357476 SHA256: 945b26004df0bd99c707955bbd4c2f62ca2354a9634b35eac851deb93f8b4072 SHA1: 4068d98bbb0c39f2cb4de12dca51e71fa35a0733 MD5sum: dbe2aff786b7ce4469b7bf6b7773f623 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.10.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5778 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.10.1-1~nd14.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.10.1-1~nd14.04+1_all.deb Size: 2441610 SHA256: f167bcd77c6b5384bf0c7f67950735ba1a3efb2020f2456ab4777bf47f1d3d32 SHA1: 973c68b2f91da696229df112ae0695630deb01ec MD5sum: bd4aa46a15b82c7cb5a937e4dc4e4691 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.10.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14345 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.10.1-1~nd14.04+1_all.deb Size: 11464772 SHA256: 7e1e4e10d931dfe1b6a82e9a4338973bb09869411486e308a1b7b9df69ac9e8e SHA1: a9c4969eb66647b387444314baed86e6e37ba549 MD5sum: f324973ae8f011dad397eaf266bfe307 Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.10.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6791 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14), libgomp1 (>= 4.4) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.10.1-1~nd14.04+1_amd64.deb Size: 1199604 SHA256: 64e66f157fae664a15505b72f8683b99b50e6a69d7cc6c878572c6b0e95dc970 SHA1: 86b28e83a627ef995f191e41173d8aca2053dd0c MD5sum: 73c68593c91c6241d81e15cfd852a5b0 Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2388 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1_all.deb Size: 695948 SHA256: 37604b739e17ae561b68e1ffa8fd89495abab699acaa75ce4a4160ab0e9f1dc9 SHA1: ede08d0df1746f31ccb9eb6fbcdc49722e3b1b5b MD5sum: 95df9057ee0432389482bebb2bebc420 Description: Python library for cognitive and neuroscientific experiments Expyriment is a light-weight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments. The major goal is to provide a well-structured Python library for a script-based experiment development with a high priority on the readability of the resulting programme code. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones. Package: python-freenect Source: libfreenect Version: 1:0.5.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 164 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.3-1~nd14.04+1) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.3-1~nd14.04+1_amd64.deb Size: 42194 SHA256: 2f020f6fe80e769390547e803fde6dd4b540ef8c6f6495e993fd5ecd69099c41 SHA1: f04e44a3fed2a3358bdc5d5d0cc0e2eee896d3f6 MD5sum: 059ab9eea030954475de27cac8f4a085 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 89 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python-funcsigs_0.4-2~nd14.04+1_all.deb Size: 12750 SHA256: a6c50a81866eb65c9c537e5aeaf0759bc7462e40907c9fe0fe3ef74207e805fe SHA1: 7d3a78f5d60304466ea78ec3322afdbe3402ed80 MD5sum: 73c673b7466d986891e893635cc99ebc 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~nd14.04+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~nd14.04+1_all.deb Size: 24170 SHA256: 91020210e46dbf1ba30776a52fb45b5a2ebb0efd4e5a6b0d2812bf9fc40b2fde SHA1: e8a88a1101c2daefd42fdf0db9dcd120937fbe90 MD5sum: f68afc7bff6e189b89513589e9f83594 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1732 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python2.7 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~nd14.04+1_all.deb Size: 336038 SHA256: dc7401310968162b4ebed3645055285c874be325278a45db71dd1f7843632105 SHA1: 9d81fea409dba56a49279ccec79875de6f81ee04 MD5sum: 52e5592c4017dc73747fd1376c878a94 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1577 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~nd14.04+1_all.deb Size: 293316 SHA256: 35ae3d991bf118c268c62b0e11b65d3ee55f5383d4bd83214045e9c6d98c03cb SHA1: 0e113bbe784a0b1b4d9519a81dd347b85a8a8a86 MD5sum: f915855e035e4f2650021f7b348888a0 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1563 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 0.6.4), python:any (>= 2.7.5-5~), python:any (<< 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~nd14.04+1_all.deb Size: 290196 SHA256: 658aeed45c4bc69a4661d6bed91ec541be898f4b319f727ea7ed12a7f0159f9f SHA1: a373372680da7905a94ba7c37a213a11b8a133f6 MD5sum: 57c4029905e7cc2b0a6f5fd876f889f2 Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.0.5-1~nd14.04+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~nd14.04+1_all.deb Size: 122246 SHA256: 8ff16b1fce1a89f747c1867c304bdb19f3e7c8ac029982c62ca7e9d601133dae SHA1: c72d7e0771a8d9cb12d96bbde550539294632f7c MD5sum: 4e3583623c1666da0e3f9ba14484670b Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-gitdb Version: 0.6.4-3~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), libc6 (>= 2.14) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_0.6.4-3~nd14.04+1_amd64.deb Size: 55340 SHA256: 0c430df1168baaf2a623ce0754ca83bc5cd76eee3e8d6e7dbc2b615c5baec777 SHA1: 6fbb99cb5aee0ce76812ff8803cc483d507aa58e MD5sum: a788d2ec781dd8a78974b4e6f5f82e18 Description: pure-Python git object database (Python 2) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 2. Package: python-humanize Version: 0.5.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 117 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python-humanize_0.5.1-2~nd14.04+1_all.deb Size: 12952 SHA256: b9524acfb16d327e1a07b147b15f7904766d20a3ad66ca41dc5364025c5e5429 SHA1: 9f57df6560f1c54888b2f4054166e0d04459aad1 MD5sum: 681f7ac6228c80c5a7cabb101baf0983 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-jdcal Source: jdcal Version: 1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python-jdcal_1.0-1~nd14.04+1_all.deb Size: 7670 SHA256: 1f7d63bfde1855c23e02ebfce05181789c84b273daab7ea32c66f78b1cca884e SHA1: 9d0226fb987ab11a64f01766cf92eacb9543bd28 MD5sum: 35bcdfe5fe51152dddaaaffafe9b8576 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python-joblib Source: joblib Version: 0.9.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 363 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.9.4-1~nd14.04+1_all.deb Size: 81814 SHA256: 80fea9079f6cb37e8d9a822ca4d806781c1549d7085f2354f7c0a0543eed86b4 SHA1: 629ef5bba84de5bd4e4667a2bd62c1fd82958244 MD5sum: 72280420e364781aa4460a4fccae1326 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-lda Source: lda Version: 1.0.2-9~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1238 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd14.04+1_amd64.deb Size: 232456 SHA256: f4397947b6fd42e125faacfd49e9422e26e5a9e79edc106d958255b1990ca9d0 SHA1: b55253a8436ba1c99d2044686fe85768890ae12f MD5sum: 8898276b0474d512bd2b14aed4add4d4 Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-mdp Source: mdp Version: 3.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1375 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-numpy, python:any (<< 2.8), python-future Recommends: python-pytest, python-scipy, python-libsvm, python-joblib, python-sklearn, python-pp Enhances: python-mvpa2 Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.5-1~nd14.04+1_all.deb Size: 277596 SHA256: b341f34d09056803b902d8ba6074b485f8fd96027352d147298090555a2ba731 SHA1: 95e7b548f0a5e1854f7f6b40be03e11fd602f13c MD5sum: 1dc1ac7dca838571b91743cf7b31369f Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-mne Version: 0.12+dfsg-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9463 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui Recommends: python-nose, mayavi2 Suggests: python-dap, python-pycuda, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.12+dfsg-1~nd14.04+1_all.deb Size: 4432150 SHA256: 3f961a9d4529324d06c298ff2fed7ca34ab6180ef30d774f29413b018982dc76 SHA1: 1a153c12ed8b24fb7037e3b5406e5a53cdf4a658 MD5sum: a69af4bbc8bf059903cc8c8adeb2d2bd Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1292 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 308978 SHA256: 5d75b43e467de9a440b92c38aa21fd50b7200e1d9d9c4c765c8e00fa28e12d5b SHA1: 1e8f375529f499dc35686aa000a8f274d5f8b43c MD5sum: 9dbd82c96b890c7215da1337c8caa484 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5329 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 982798 SHA256: 5d5ed98cdb7c3afaccd197b2f8aeebc7d21d5a64f3359eba56898baa6d9b4112 SHA1: ac67a1309bc3f5f3c8c642416090d91de31e9a9d MD5sum: 3277c46895c12fb5b686fafe2ac09573 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 257 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_all.deb Size: 52650 SHA256: 89c6b2097aa4c46452fc4c94f25c9552c6bdbb11de0b74d3499a9fc731fcb138 SHA1: 180f3b068696bf9372da2ab0ebdeab29e18a44c1 MD5sum: ccd5f97d5b5360920b157174f29dcace Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-msgpack Source: msgpack-python Version: 0.4.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 171 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.14) Breaks: msgpack-python (<< 0.3.0-1) Replaces: msgpack-python (<< 0.3.0-1) Provides: msgpack-python Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python-msgpack_0.4.2-1~nd14.04+1_amd64.deb Size: 53230 SHA256: a0a64aeaf7f04032415d296fede052fdd443cc87f4cc2f0562325b90b751c843 SHA1: f8523e8e12370630fdf373136a6c343d8dbb7cef MD5sum: db115976cf03862280db72ec82aaf506 Description: Python implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python extension module implementing the MessagePack format. Package: python-mvpa2 Source: pymvpa2 Version: 2.5.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8370 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.7.1-0ubuntu2), python-mvpa2-lib (>= 2.5.0-1~nd14.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, 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_2.5.0-1~nd14.04+1_all.deb Size: 5076572 SHA256: 0686f2027ee6b2a23713b1d34c4d5f7366a042d83e59fa95066137415f7c636a SHA1: 9e61130c9a8230efd2977286ab4da2ff2983ebcb MD5sum: 93382048f9ab7a54bd54f92bad6e118c 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: 2.5.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 30074 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_2.5.0-1~nd14.04+1_all.deb Size: 4633538 SHA256: 244204357d3c038822484d84fe5d6a92b8a762121e183e9ce21b654e81ffafdb SHA1: be865c868ab76e2b969f4ca3369584b17e4bae67 MD5sum: 80fb042a940b552eebae4791e2324df3 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: 2.5.0-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 169 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.5.0-1~nd14.04+1_amd64.deb Size: 48308 SHA256: 11f972d920611053f5c3ebc31e97675cfa8703e41362549445bf2a629015b4fe SHA1: c7af48031a79c52357559746a0a93259476bf932 MD5sum: e02342e1d0065ffe6aa4834000edef32 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 28812 SHA256: 15d6ad200903f48f7d0ac38e08d3aea9a417b73085929fcdacce541b5ecb0f05 SHA1: ab997820ecbef62ee9805767c8810a4a4663c6a4 MD5sum: 6ca9dceaed50e4921f7759c6fe0b948f Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63313 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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~nd14.04+1_all.deb Size: 1962668 SHA256: 073f965071e19de979c9fbe85522edac0c26c9087c6b3c80323620d9599e1548 SHA1: 1fa5e5e2da1081c28ca5800c8b5bd09439123dff MD5sum: 27ff137eedffd09b7cfd86e0fba98d10 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5565 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~nd14.04+1_all.deb Size: 2682562 SHA256: 0f7a7a9658f5a0ef2b7762b8cd4eb2960227d776515e803c7d5ecddb3093c28c SHA1: 4b3721ce86e330b591716a044042a24bc3e26cfd MD5sum: b333e32895ab59e3dd2e61a11e03eb73 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2437 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6), python:any (>= 2.7.5-5~), python-nibabel (>= 1.1.0), python:any (<< 2.8), python-scipy (>= 0.9), python-sklearn (>= 0.12.1) Recommends: python-matplotlib Provides: python2.7-nilearn Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python-nilearn_0.2.5~dfsg.1-1~nd14.04+1_all.deb Size: 731138 SHA256: 27e64f205d899c6c771515afe37216ea3580025aa23cdb54c4e3215d4446fb78 SHA1: 0366f70e98fa1b0cbc268f6a28bfa1e096bf1880 MD5sum: aeae2c4d9b9365339daff1c25b57d453 Description: fast and easy statistical learning on neuroimaging data (Python 2) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 2 version. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.4.0+git26-gf8d3149-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3338 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.0+git26-gf8d3149-1~nd14.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.0+git26-gf8d3149-1~nd14.04+1_all.deb Size: 738094 SHA256: b78f66f8fc6ddb33f8e1555ccacdb550e2dfa7eacecf60b7f7a3ad8d0a344328 SHA1: 6f1a79e1ef39570ec54e63921bf0c461543c69d7 MD5sum: 19c74717eb684916121ebd736a63aa3d Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.0+git26-gf8d3149-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8213 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.0+git26-gf8d3149-1~nd14.04+1_all.deb Size: 1151748 SHA256: fb6decbab2e2f8d9c4e2825e7bd359b612b5941acc6fe2269eb6c1a8301345d8 SHA1: cb8fe719d0d1a5e3b1198b218923e0c020a99f46 MD5sum: 42b54ba5ebb7b67405a65faba18aaa5e Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.4.0+git26-gf8d3149-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2469 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.4.0+git26-gf8d3149-1~nd14.04+1_amd64.deb Size: 565064 SHA256: b142f7c9cde15b2ab0b492d19cbaf6439abc3afadf2286399fdf236bd6af5368 SHA1: 235ec07e275f9b93e7cce91e66fc70a224623bf1 MD5sum: 7fca0980324c7d9fa071106bd617293d Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.4.0+git26-gf8d3149-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3644 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.0+git26-gf8d3149-1~nd14.04+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.4.0+git26-gf8d3149-1~nd14.04+1_amd64.deb Size: 610258 SHA256: 1e9302afe12f619fde9eb196e45da2a83e76c2cc9b704d3f3c24fbb6095b424f SHA1: abd6786a8156befd85f79158340d1b6db79e5baf MD5sum: 117f3998469a575369a4bb3bb41ad5d7 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipype Source: nipype Version: 0.10.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4573 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.10.0-1~nd14.04+1_all.deb Size: 1158946 SHA256: 39836fcb648f64546c684c1831a50292c701b204b127ee8ea9a3ac3d162dce69 SHA1: fc0b5f3620bc163b435ce94c3537f601bd89ce0c MD5sum: f56846a6794f64b052f434dac5e5e4ca Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.10.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20779 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.10.0-1~nd14.04+1_all.deb Size: 8759220 SHA256: 4b2c7602f68541b83fefb69f9e2b3277109f40fb53ce0ab93fffdd461303f5e7 SHA1: b5dd929f7a8df02f697c2ca7e98fc28cf8f1e95a MD5sum: 91069fca772934ae6d749a309252bb74 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.6+git15-g4951606-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9397 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.6+git15-g4951606-1~nd14.04+1_all.deb Size: 2562110 SHA256: c314436d74f5c82ea236f12ac2e32fe961e479072c1f321160cbdb7847c857ad SHA1: 8bd382687d2550bb9035bf5f1bdd826202686f38 MD5sum: b964a8493b60fbaebc44ab84de4e6066 Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.6+git15-g4951606-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7690 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.6+git15-g4951606-1~nd14.04+1_all.deb Size: 5698292 SHA256: 40c86e26dc49cb4db962fdcd1ed062879a8c68e0d16b4e4af5c7a931e0fbd5e4 SHA1: f7593b5774bd1ec5b259eb5a389e7ce5602feb53 MD5sum: ddc6bc0a8bf740b8f7f8c483feb07bfe Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-nosexcover Source: nosexcover Version: 1.0.10-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python-nosexcover_1.0.10-2~nd14.04+1_all.deb Size: 5250 SHA256: b2ae93571b0725e740f89e8b03cb902089365182868a9a8c8545c5037a2ccbf0 SHA1: 256b21a4c6b869033aa366e3cd70e4557846983c MD5sum: 04cf2021c398ef47e5fcf18a72394497 Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python-numexpr Source: numexpr Version: 2.4.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 380 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7~), python:any (>= 2.7.5-5~), python (<< 2.8), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.4.3-1~nd14.04+1_amd64.deb Size: 134746 SHA256: 8088187c4196e35c33e334e8ec9a81d4709d0b32aa23d537cc1f62ffe490083f SHA1: b6f196cf5c82c7de0eb785ee5fa201897489aacb MD5sum: 168711ad8213f827e7bc1f861da48b79 Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numexpr (= 2.4.3-1~nd14.04+1), python-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.4.3-1~nd14.04+1_amd64.deb Size: 102694 SHA256: aeeef536c528e8388af4740f2ba6a7e4d897bf11f54cd2a2636c4ed3ebcacdc7 SHA1: b513a5237171a235e6bf6117c77863045252255d MD5sum: bb034487e6d8c0f90e73aedc67999f42 Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1121 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-jdcal Recommends: python-pytest, python-pil, python-imaging, python-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0~b2-1~nd14.04+1_all.deb Size: 191632 SHA256: df1c6182bb909af72b09ea8851da8e2c35717fdff7d298c5f8df9e1c01e96a6e SHA1: ce80135d40a9fc5e629b1ea13983beae49942ef9 MD5sum: 0631060ddd63fb027edeca77f0d8a195 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-pandas Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24201 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.18.1-1~nd14.04+1), python-pkg-resources, python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.18.1-1~nd14.04+1_all.deb Size: 2527632 SHA256: 7d7f696b3f35a86f86bffad275cba3cd9c50ffc019d6a6bf7528274c8c4d897c SHA1: 1537850796be6784bdc63d047e40873d657a777c MD5sum: da8eb9f836bef8fce71cd7faff5ce5ed Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56875 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.18.1-1~nd14.04+1_all.deb Size: 11547442 SHA256: 109386dee6d9887c77eeb31c9c3845e2c4fa7e78b50976892a20dc233d4921f3 SHA1: 775dd6018dad37dc79deb26aa7550e7fd1a674a6 MD5sum: 2a804c6a815ba54c61200c664345b4b9 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6290 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.18.1-1~nd14.04+1_amd64.deb Size: 1624192 SHA256: 241a53926fba56adfbe9c6baea45951e1ae8a0be7d896ed0e034bc6020aad004 SHA1: 74d7c2618acaf94a44fe053fdc50a5f91d4ab429 MD5sum: 38510e56242463fa1759ccac4afdcd62 Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 795 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-six, python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.4.1-1~nd14.04+1_all.deb Size: 171752 SHA256: 51be9da2ab4bf0707c425f8c975291f4f123ce78d586d59daf9da6607061e4dc SHA1: 6f27fe7cb2cc5436eae94d90d9b533039c3fe47b MD5sum: 878edc3d6090b111444cd1b04f692f97 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1303 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.4.1-1~nd14.04+1_all.deb Size: 357686 SHA256: 38dec6587534ab4a253473578e2387eaf0e57c119206e9c9954b763e071d23c0 SHA1: 5969531a0aa16eb62f889ed7f8cb8db6bd1e4aa4 MD5sum: f8d189c4a9b883d42ff82ec0a0f1347c Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd13.10+1+nd14.04+1_all.deb Size: 81638 SHA256: a3672edffea33c0135dc765fe3dbe3524115cf8cd1ae636f2bf7cbc09cfc47be SHA1: c317f00152e89dbf84b5a85ea883b44920eef65a MD5sum: 421e4d9f4c03a34b12fbffb0d0f92b25 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-psutil Version: 2.1.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 540 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python:any (>= 2.7.5-5~), python (<< 2.8), python (>= 2.7~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python-psutil_2.1.1-1~nd14.04+1_amd64.deb Size: 116160 SHA256: e18884e702b5b172fb98894fb96229a695f81a271fe3d3937f729fb6bb44c62e SHA1: 53c77e1021d97bd744b0f0f273319fbd060939e5 MD5sum: a9fa1922a49037a689110709ec38cf07 Description: module providing convenience functions for managing processes psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. Package: python-py Version: 1.4.30-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 269 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.30-1~nd14.04+1_all.deb Size: 66656 SHA256: b247e9257aa8067c8d3d4798716dd149ffcdeee0f161f7ddc0ea0ca6575e932e SHA1: 0a2216498793395a85739146301a250231177798 MD5sum: 62f120862eaaf8fd92e04296bda302e6 Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, graphviz, python-pyparsing (>= 2.0.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python-pydotplus_2.0.2-1~nd14.04+1_all.deb Size: 20246 SHA256: 2680420223b68b4e90a0e9fa995a31a5cc60f9f01d3f66d9ad667efbb7d42d60 SHA1: dfe94fade1ce954bdc6d6d2d91cd8022638af42c MD5sum: 406e4724c36431b6b0044f1d30ee4f51 Description: interface to Graphviz's Dot language - Python 2.7 PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 2.7 module. Package: python-pydotplus-doc Source: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 755 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-1~nd14.04+1_all.deb Size: 178508 SHA256: 6b083d0f654230dd8213720aa6cb97bdfac7e23bd8b4ebf0df14d83345b74e54 SHA1: 12eb8384d62b1467bf227659d49ac60786613235 MD5sum: 313af7833740ba616df312eca87c064e Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1366 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1_amd64.deb Size: 280316 SHA256: 18e1bf03b831fb92eb5c5842f0ac37626f4f4b72cd7166b5e096d7cda9bc733a SHA1: 9dc28ee207759930bfaa42697d7bd036f0506c12 MD5sum: 2f8617180be925aea587c05e501b028d Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1_all.deb Size: 819336 SHA256: 4fd57971c92c6cd4cefaf9f32063e2c926a4cb901726c02263d9b4ea8cc24bb8 SHA1: 13d0d3aa4656070b80d4bed6e11ef0228e43b195 MD5sum: 335b1dfa97a9d8678444c11354131088 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python (<< 2.8), python (>= 2.7~), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd14.04+1_amd64.deb Size: 73590 SHA256: be13c7a7be5626cf645f1d41df9be9fc5f729010888e03ead1781688b42efb04 SHA1: 9e776ad47bf2737f5d3afd6a0c7b955a71c2fbe1 MD5sum: e8c6277e845aacd8f439083361fde59e Description: Python interface to the Graphviz graph layout and visualization package Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. Package: python-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 337 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd14.04+1), python-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd14.04+1_amd64.deb Size: 108310 SHA256: 229eac3c9970ede78d56332c22253c3e414b2134a6f66c0707962559fa527c61 SHA1: e1456cbc6ed9103fcc142b636c15f8a04250d841 MD5sum: 4346dad87655ea084cad5ba29a7b8c1d Description: Python interface to the Graphviz graph layout and visualization package (debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python-pygraphviz. Package: python-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pygraphviz.github.io/ Priority: optional Section: doc Filename: pool/main/p/python-pygraphviz/python-pygraphviz-doc_1.3.1-1~nd14.04+1_all.deb Size: 67900 SHA256: 7c34df50d8f08bc1e04ea61edf29492ec557263a8f5c990a7c3bb22142d0f6e2 SHA1: c3a73b8871316b164182e70e862941e6db5847c1 MD5sum: 7e0f8aaa9f527c56ca61e3bad03d97ba Description: Python interface to the Graphviz graph layout and visualization package (doc) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains documentation for python-pygraphviz. Package: python-pymc Source: pymc Version: 2.3.4+ds-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1909 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libblas3 | libblas.so.3, libc6 (>= 2.14), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, python-scipy, python-matplotlib, python-nose Recommends: python-tables Suggests: python-pydot, ipython Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: python Filename: pool/main/p/pymc/python-pymc_2.3.4+ds-1~nd14.04+1_amd64.deb Size: 432094 SHA256: d97f463e38aadff7fae263fba77e95d92398d51ddecc6bcc2f486bb13be6a451 SHA1: 021942ac580742fa889a8372a0ed5dc4083142a3 MD5sum: 7d7492482f884ea8a985db141e981bca Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. Package: python-pymc-doc Source: pymc Version: 2.3.4+ds-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1860 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: doc Filename: pool/main/p/pymc/python-pymc-doc_2.3.4+ds-1~nd14.04+1_all.deb Size: 839822 SHA256: ca5b4a1c229d97f73a5efabb5bce300e4461516be6d6ca3fb09a71accd13d6dc SHA1: b7faad248279ffb84dc5464d0d050883c20afe1c MD5sum: c2f9774d355e63c5a38e9d90065b3aed Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. . This package provides the documentation in HTML format. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 122882 SHA256: 62e294043371c55fc47adddcd8c00ee9b823bfc2885a7fe6a17545f5a9ba2cea SHA1: ac1a6014356d9f0d27fe921f17abf9a006bc6dfd MD5sum: d08fcaa0e9cdb30bfb91d7d5082d4941 Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1595 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 331006 SHA256: 052d31fcb635f13e829a8eccfb5c81e56f6bb80ea9959feba88c783c7f3f536d SHA1: 50504f93bc680645c8cfc60dfce411486ed501df MD5sum: 05b04f538af2513542848e856c492d13 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pytest Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python:any (<< 2.8), python:any (>= 2.7.5-5~), python Suggests: python-mock (>= 1.0.1) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python-pytest_2.7.2-2~nd14.04+1_all.deb Size: 102268 SHA256: a5bc67d196abb4d30d1d59f9ddb6cc31ba957acd0cd6a1238661d5f1d9b64eac SHA1: 4dcfe73451f8b239c438acb5319988f1f6f42608 MD5sum: c0a87dff9798b7418e011f2d0d38428e Description: Simple, powerful testing in Python This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. Package: python-pytest-doc Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2879 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-pytest | python3-pytest Homepage: http://pytest.org/ Priority: optional Section: doc Filename: pool/main/p/pytest/python-pytest-doc_2.7.2-2~nd14.04+1_all.deb Size: 401394 SHA256: 9454eed49ee66eae353e2980c3d4eb49cda6377b0a129038702726d6e993a988 SHA1: f4c4aa66f6106f3715640dd31bc4d987df510199 MD5sum: 6daf8937fe0654a85e2290e98d04119a Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python-pytest, python-werkzeug (>= 0.10), python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python-pytest-localserver_0.3.4-2~nd14.04+1_all.deb Size: 19208 SHA256: 6dc0826378989aa452e64dd8197b2daf87e5421da9dcd9780c7cfcdce32d90d0 SHA1: 918c1eed4cda552d75b0fb8d2cb4f9c59558c0ee MD5sum: 77c5995e27fabad5d0e0dacd2d6e9f85 Description: py.test plugin to test server connections locally (Python 2) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 2. Package: python-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-pytest, python-tornado Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python-pytest-tornado_0.4.4-1~nd14.04+1_all.deb Size: 5674 SHA256: 3df1aabe30adc5bcdb999720babc481798f61c8bd2af76cc81f4cb84a5fb8b8c SHA1: 0cc076b5af86d42d85122d8b771de2a4dd734835 MD5sum: 1d7b0e30f16aa344c6dbfb70f9900944 Description: py.test plugin to test Tornado applications pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 2 code. Package: python-scikits-learn Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.17.1-1~nd14.04+1_all.deb Size: 55990 SHA256: f0a6f294e3314f775f3ea42fd4b2ae4da1d08f0f376aac017f6ef11f08640d00 SHA1: 17235989aac1916f6ffe19efad0250b791f2cb09 MD5sum: 9b6898ed16828f80823a0dd746861d98 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scrapy Version: 1.0.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 812 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-lxml, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python:any (>= 2.7.5-5~), python:any (<< 2.8), python-twisted, python-six, python-pyopenssl, python, python-service-identity Recommends: ipython, python-django, python-guppy, python-imaging, python-mysqldb, python-pygments, python-simplejson | python (>= 2.6) Suggests: python-openssl Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.3-1~nd14.04+1_all.deb Size: 175830 SHA256: 43ae160995859d66d0969c6597daa3610ac3a38b35ac822e0185b15c57c9bc11 SHA1: 5a96e9daa65d1cd722efd64527f2f4d7089e38f4 MD5sum: 05bd415ef1af3f5e412b2e611376f0e8 Description: Python web scraping and crawling framework Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy script and modules. Package: python-scrapy-doc Source: python-scrapy Version: 1.0.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5944 Depends: neurodebian-popularity-contest Recommends: libjs-jquery, libjs-underscore Homepage: http://scrapy.org/ Priority: optional Section: doc Filename: pool/main/p/python-scrapy/python-scrapy-doc_1.0.3-1~nd14.04+1_all.deb Size: 651116 SHA256: 3c566a34a50e23f25f2202b780c695376e27978f404620c6bc4d389616af90ae SHA1: 9790445a5217b150a3649ac65456f9a1305cce43 MD5sum: 1e260cbd681a4cbf11874aa000a97b81 Description: Python web scraping and crawling framework documentation Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy documentation in HTML format. Package: python-seaborn Source: seaborn Version: 0.6.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 676 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-numpy, python-scipy, python-pandas, python-matplotlib Recommends: python-statsmodels, python-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python-seaborn_0.6.0-1~nd14.04+1_all.deb Size: 117710 SHA256: e47fbc84aea13872455b4266a9a8834d61341ee207b83a1d0fbde3e2fa20b799 SHA1: 81de27b81b120ac6e276a41cecb6dd862dde2442 MD5sum: 644fb5dad9a465cec2748c4c8131977f Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 2 version of the package. Package: python-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python-setuptools-scm_1.8.0-1~bpo8+1~nd14.04+1_all.deb Size: 10144 SHA256: 81fa741285e7fcba5088c45e5b0438f16fb94ecb2ce15d54362a66bdc635b62a SHA1: 0337593c9317611d4e8437b4a08a1767d868925f MD5sum: 4bdc1a720e93fecf17c65b8e1690ce09 Description: blessed package to manage your versions by scm tags for Python 2 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 2. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 11018 SHA256: e541fbf52c8d157e98be2e3d3d54fb033d5e30880458d9b143aab22f9fcbe65e SHA1: dd2095a9d2b56400abeecd526982b047084f0bdf MD5sum: 0bf7c71f9bb8cc5137d0e12156ad46d5 Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 13266 SHA256: 3a2a5d68772088d86ddca061fa261ce001e746c4c5b567216bf9f8aa641569bd SHA1: a86caffffa3a87341f18e5d13fa820e2e764bf1c MD5sum: 770748590bd24a026041c4970f925111 Description: Python 2 and 3 compatibility library (universal wheel) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six as a universal wheel. Package: python-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15134 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-six (>= 1.3.0), python-skimage-lib (>= 0.10.1-2~nd14.04+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-imaging, python-matplotlib (>= 1.0), python-nose, python-pil, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11927494 SHA256: 82c528be9e874b39de21a4bba62421c1d6bd7589c9596093dcf97becccbfa3ae SHA1: 172a2e19e17e3b5e2b165127f92fe4ef51f60003 MD5sum: 5c1c7e773ca81f8494f6b4b97e17b06d Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21865 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.10.1-2~nd14.04+1_all.deb Size: 17205200 SHA256: 60b9c823532f9aad362ddf844c783ae8afc19152e3a8633699c1b906979ba876 SHA1: ffda4a2dd76fb4d7df9deefa82715439553fa6fd MD5sum: 34188666367a224580d2a0306199c599 Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6595 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Recommends: python-skimage Provides: python2.7-skimage-lib Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.10.1-2~nd14.04+1_amd64.deb Size: 997084 SHA256: 9501af0012ef938b82e41c83c271da1ecfd4954320997db29b92cc5ec3986691 SHA1: e2d6410ecbaaf2feb9549fd33374da5c957584fe MD5sum: 688112921367a0f9422190d0dbf01fe4 Description: Optimized low-level algorithms for scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 2 libraries. Python-Version: 2.7 Package: python-sklearn Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5281 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.1-1~nd14.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.17.1-1~nd14.04+1_all.deb Size: 1223580 SHA256: 2d118f52164ca688511e479bd62286496b99cdde3d73a3ba24e4700557950bc4 SHA1: 576003c44a3dc80b51792a10bbacf8417d6bfbc4 MD5sum: 890ba71b39aebeac176ee887320d5eac Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23790 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.17.1-1~nd14.04+1_all.deb Size: 4063478 SHA256: 5dec4e0df4d0d8ca6cbda979a4f418d997fe6f8842689a7b878ae4c72e461c1c SHA1: c4ad9be521ca1fc044d1256951f26faa7a6aa2fb MD5sum: d8e683e99f46957afe49c0eced832100 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4881 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.17.1-1~nd14.04+1_amd64.deb Size: 1102674 SHA256: 9f15e951c07430a9c31501210590793f018ae8abf460d7a87b6fdc7c18b836b6 SHA1: 979253fd7f355caba127bb1be5b3f0ec6facd12e MD5sum: d9ef4fc8a9253c8fc8a5cefb30355e5a Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-smmap Version: 0.9.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-3~nd14.04+1_all.deb Size: 20296 SHA256: c3f503b544b506d56122a20792630e01f6f96796d047b791382c973d15159aea SHA1: 15bc5137e3e36e7a60019e5118f6901ba140af1d MD5sum: e7e6c67383d824cef31be886c5c9dbdf Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 2. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python:any (>= 2.7.5-5~), python:any (<< 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~nd14.04+1_all.deb Size: 117170 SHA256: 8d17f4cf1b75a6ea2e35dcc4ca9eb270006eeed87c54cd5eb0899e710fef410b SHA1: 7d682ebcb2df6a4681a2347d1d6f2931718ef0c4 MD5sum: 74729ef3e6968eb8ae00592b5ba23e8f Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-spykeutils Source: spykeutils Version: 0.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2090 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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~nd14.04+1_all.deb Size: 309540 SHA256: 820c3ca420f026ec91cc0fa2018226bacd069ca010fdbf3a7a612a12be31ee15 SHA1: 11d04fd42bf9a14850534d5bf4a7b33347902451 MD5sum: 0722e50cf3dff91d8fab11c5a79c3d1b 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-stfio Source: stimfit Version: 0.14.10-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 898 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python:any (>= 2.7.1-0ubuntu2), libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libbiosig-dev, libsuitesparse-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.14.10-1~nd14.04+1_amd64.deb Size: 302008 SHA256: 0ef4c0762617f8a73156dcc6699acd19da586b65780bd89b1a725153513c5b50 SHA1: b55a4dfa8137fe13c643cd91fdb4f9f963ae1797 MD5sum: 058c3d4f30589082ffd98551691c4e2e Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.6-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 226 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-nibabel, python-numpy, python-scipy, python-pil | python-imaging, mayavi2, python-argparse Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.6-1~nd14.04+1_all.deb Size: 41646 SHA256: 80e873c3d00ac287b75dbf915977f7e49557aa514d7d3abcc2827b79e3629e5b SHA1: b372b5e75e7c68857b885f461ec60fcef1722073 MD5sum: ed47bdcff3940d9b0bcbdb732db98535 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-tqdm Source: tqdm Version: 4.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 160 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.4.1-1~nd14.04+1_all.deb Size: 35334 SHA256: c14b06ee30bcdfd69cedb08eba44ca00ab87fd50d52fc395180d3989a6a46987 SHA1: 1742f84dc9001263c9b1d060838d60e26ed9fcd3 MD5sum: 8e9fd211de40853dd1287bdad3bbd529 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-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd14.04+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~nd14.04+1_amd64.deb Size: 61500 SHA256: e554bc7d660ee86e5dff61b09ef667201c42194deec1a5f31962759f7e77f8a3 SHA1: f936ceaa1e11fe6b4ea2e4d6247de77aaa746188 MD5sum: a6cca755894e52b03f0b7a721a2041a0 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python-six (>= 1.6.1), python:any (>= 2.7.5-5~), python:any (<< 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~nd14.04+1_all.deb Size: 14094 SHA256: a143ab050c507692654ddeae18ca7ac254b7d86ac239c5046c0fe27d9f426366 SHA1: 8eb4554d5350ada80f23c95f42aea045a4554427 MD5sum: bbc1d292a81d284a45060953fac74aa8 Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), libjs-jquery Recommends: python-simplejson | python (>= 2.6), python-openssl, python-pyinotify Suggests: ipython, python-genshi, python-pkg-resources, python-lxml, python-greenlet, python-redis, python-pylibmc | python-memcache, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python-werkzeug_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 163266 SHA256: 30d72ddc76c40209588e9aca6110a9e7ccad863cb1e2e56d94652993743512f4 SHA1: 49839c379ce6906a8c7d6673650a6530ab1db7e7 MD5sum: a5499bc02b89cf7549e9e8cfd8e65ad9 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python-werkzeug-doc Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2559 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Conflicts: python-werkzeug (<< 0.9.3+dfsg-2) Replaces: python-werkzeug (<< 0.9.3+dfsg-2) Homepage: http://werkzeug.pocoo.org/ Priority: extra Section: doc Filename: pool/main/p/python-werkzeug/python-werkzeug-doc_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 879504 SHA256: 587cfad920e8ede1479ad00bd06417bd6839666b44fa595e8a6fcaec11d135a1 SHA1: 0901b6f1e3dca6bbc5800ae98324e4972a848276 MD5sum: 7cef970aad6fc4f6ce0fd38f8b68c13a Description: documentation for the werkzeug Python library Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 123 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd14.04+1_all.deb Size: 20990 SHA256: fcfb82d58ed9db706b5fb445a5d1a7b92c8af3c6e50e9ab6824a4b044ffa06c9 SHA1: 56062ca9770fd9bb9dbb58b7ba697a1395277aaa MD5sum: 62290f7da03fbe39f1ca8ffb65d81006 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-citeproc Source: citeproc-py Version: 0.3.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 731 Depends: neurodebian-popularity-contest, python3, python3:any (>= 3.3.2-2~), python3-lxml Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd14.04+1_all.deb Size: 81778 SHA256: 5ca21fbd35228899a0a548d3b2fbd7b70c3d3a90d59ee7598948acf90656e426 SHA1: 9a1da1d78f649a29d9957a000aa9d96323c7812a MD5sum: 6b26c48e4aaa89ffb0cc338355c500ea 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python3-contextlib2_0.4.0-3~nd14.04+1_all.deb Size: 8736 SHA256: 72841c88eabc50f3a870806d07a94f2e4c8b8c17f132af58a14eaac4099af14a SHA1: 1668fe8f673231165b07873c808a929702e3c90b MD5sum: 87622dd630ad0afc1284146b2ead624f 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-funcsigs Source: python-funcsigs Version: 0.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 89 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python3-funcsigs_0.4-2~nd14.04+1_all.deb Size: 12832 SHA256: 37684478429b457dee602d6aa1519743da4149c9be0a9b9631853f5072a5be68 SHA1: 5186c91038a589d1f00ffb17022c1ed706403718 MD5sum: e225fa83d1cdfeec6ca881c05924e9a0 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1663 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python3.4, python3:any (>= 3.3.2-2~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python3-future_0.15.2-1~nd14.04+1_all.deb Size: 333824 SHA256: d80df414502fa8896b82cd934dfdb63b1e8322696c947f84d8254fed9145b758 SHA1: fa57c7e6361593c539b26afbd413a9a9b3cf34de MD5sum: 062922c9fd88c6a3d8a84ab08dd474fa Description: Clean single-source support for Python 3 and 2 - Python 3.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 3.x module. Package: python3-git Source: python-git Version: 2.0.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1559 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 0.6.4), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.0.5-1~nd14.04+1_all.deb Size: 289978 SHA256: 9d5c78c46d91fa8936535b0364f165a05b8a9fd40aa5249923b00dc639d7c3dc SHA1: 45d7dcb21d7d9de7580879e54c1f1d1cc9b4fbe4 MD5sum: e651de95a2263b58d08b121e8ac5d4b0 Description: Python library to interact with Git repositories - Python 3.x python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 3.x module. Package: python3-gitdb Source: python-gitdb Version: 0.6.4-3~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python-smmap, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.14) Provides: python3.4-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python3-gitdb_0.6.4-3~nd14.04+1_amd64.deb Size: 55548 SHA256: 49a7b677a1d77a3007fb133220e71b32923d4fec34b396ef4b55e3364b910749 SHA1: 423c559d235d3af3becc31a6d10451acb526b418 MD5sum: 97e2b6f34d992f293741ae4f869d6c23 Description: pure-Python git object database (Python 3) The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. . This package for Python 3. Package: python3-humanize Source: python-humanize Version: 0.5.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 114 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python3-humanize_0.5.1-2~nd14.04+1_all.deb Size: 12682 SHA256: 392c4a2e07c72ad76f98a7bee9625ed7631477c377a61275e855c48a5ebafbd9 SHA1: d6f38ce9bbf537c685316b39f486acf21e96f11f MD5sum: 83735535f9e1e28f2251831c80e2e640 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python3-jdcal_1.0-1~nd14.04+1_all.deb Size: 7468 SHA256: 94b7e4cf3470fc765314561c161e497952f1597f87ab641b702080c2dc2c4249 SHA1: 64f8dbeedd11a34c60e16344e5943e5977723c4a MD5sum: 3f05614962ed5a2ba097afe9a6646e99 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python3-joblib Source: joblib Version: 0.9.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 357 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.9.4-1~nd14.04+1_all.deb Size: 78572 SHA256: 94ad8727e392dd6fce9cbb3e58085b74b06f2f393d806ff07173ac2b043ad7d0 SHA1: c8e4d9151cfacf5251722c58cfe2096bb6069354 MD5sum: 4d58f34d3b7f49f4edf99dd48e2fb6fd 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-lda Source: lda Version: 1.0.2-9~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1238 Depends: neurodebian-popularity-contest, python3 (>= 3.4~), python3-pbr, python3 (<< 3.5), python3-numpy, libc6 (>= 2.14) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd14.04+1_amd64.deb Size: 232182 SHA256: 6091c24e2dbf858c6b304a7a27b07aba2d8b01d53516dc919147ec1ae10e4ba3 SHA1: 696cd614a5de921029a99143e251496005b4f349 MD5sum: 1a137c12e5fd671d443f10d628d086b0 Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-mdp Source: mdp Version: 3.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1373 Depends: neurodebian-popularity-contest, python3-future, python3:any (>= 3.3.2-2~), python3-numpy, python-numpy, python-future Recommends: python3-pytest, python3-scipy, python3-joblib, python3-sklearn Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.5-1~nd14.04+1_all.deb Size: 275288 SHA256: 933a89a5ed29ea4fac21629f5c29ea097b0677a531e0ce61b501c5f7dc10fb9c SHA1: 4cf2240a0cebaacccb73390a1d3eba3f61a2df27 MD5sum: 67945f3d1e3c5dd87c3c3549ce0d29ea Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 3. Package: python3-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1268 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.6, python3 (<< 3.5), python3 (>= 3.4~) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 306068 SHA256: 8bf3ac861eb683f771ac25919e67ba3ce2e516a6c959eb48d99f1c2e6965b781 SHA1: 62b98395c907e009ab81cd84e66554157ccf5fae MD5sum: caa4ff7d88aeba2bdd490c3b8d1414f6 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6031 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1+nd14.04+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1+nd14.04+1_amd64.deb Size: 1100780 SHA256: 26e1864fc34cd5cc8abc70ad4441e529e242efd6f83829141aaf9e263e6e90e9 SHA1: e91fad9a55c55f2cbd57ca3dd549bc10e39619cb MD5sum: 57e3bc0846bae86506e429c5952c74f6 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python3-msgpack Source: msgpack-python Version: 0.4.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 177 Depends: neurodebian-popularity-contest, python3 (>= 3.4~), python3 (<< 3.5), libc6 (>= 2.14) Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python3-msgpack_0.4.2-1~nd14.04+1_amd64.deb Size: 50902 SHA256: 1688a260b9336841a1dabf5b562e9cee23588f578d2fd661dba17d66ab08b0ec SHA1: 51c60a4d77b2198bc422fa93684a202f2baeed7d MD5sum: c8b5fc99035954d2bb86cbec3625ff15 Description: Python 3 implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python 3 extension module implementing the MessagePack format. Package: python3-nibabel Source: nibabel Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63272 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~nd14.04+1_all.deb Size: 1953050 SHA256: 0fa3cf6d49f9d175568cf4169598f7c38b56378af64613cf7689c9fd4889d1b3 SHA1: eeee5b416997d7e0160d501571f90db2fff92ee7 MD5sum: 959eb490c9b7870cd9f8cca1abecf7bf Description: Python3 bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. Package: python3-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2189 Depends: neurodebian-popularity-contest, python3-nibabel (>= 1.1.0), python3:any (>= 3.3.2-2~), python3-numpy (>= 1:1.6), python3-scipy (>= 0.9), python3-sklearn (>= 0.12.1) Recommends: python-matplotlib Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python3-nilearn_0.2.5~dfsg.1-1~nd14.04+1_all.deb Size: 685238 SHA256: c44dbee085adfab56fcbfbf6c1f47665af6fd05aceb20aebfaa0d7465eea65eb SHA1: a6d967748befc9a05af6fbd3a9838afac2dc4fb0 MD5sum: e897612bf3bb824aaeb0289859073b7c Description: fast and easy statistical learning on neuroimaging data (Python 3) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 3 version. Package: python3-nosexcover Source: nosexcover Version: 1.0.10-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python3-coverage, python3-nose, python3:any (>= 3.3.2-2~), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python3-nosexcover_1.0.10-2~nd14.04+1_all.deb Size: 5190 SHA256: ec5797bfbbb38a2fd876dba8ae84283f67241da2c3e556e304c23a77f77845df SHA1: af0de88db9af2a743a7c6fac7099ad5eb0da11f7 MD5sum: cd2819a0290d34d8d1e4db6474e2d9fb Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python3-numexpr Source: numexpr Version: 2.4.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 369 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.4.3-1~nd14.04+1_amd64.deb Size: 129350 SHA256: 45f38e9fd23f9f180847ddb264b783c6b1e347d4d257d7ac335ad0d3e54b500b SHA1: 0f7a763713f0834eb6264016d0dd3cd5ae755ca2 MD5sum: 02eb172a7ca791b8f98343ddb9eaf336 Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (>= 3.4~), python3-dbg (<< 3.5), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.4.3-1~nd14.04+1), python3-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.4.3-1~nd14.04+1_amd64.deb Size: 102568 SHA256: f8dec13cbd0957de6ec860f849d0e51f6be1d51c526e938940bad62f20fd6c72 SHA1: 78e05f0a31da5bd2fd870c6c98ad940a89fa85ef MD5sum: a302047d0413a97f6c2c5b731f39bacc Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1115 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-jdcal Recommends: python3-pytest, python3-pil, python3-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0~b2-1~nd14.04+1_all.deb Size: 190148 SHA256: fde43ee0bc57973ed26742d30d0cf5b1afb96c75dfc77e8b310ef1a639f97ba3 SHA1: 94781407d5fbe3630d81ae0779d03b080210ea3a MD5sum: 162cda742a0df264ecb31c12a2cc20e0 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24174 Depends: neurodebian-popularity-contest, python3-tz, python3:any (>= 3.3.2-2~), python3-dateutil, python3-numpy (>= 1:1.7~), python3-pandas-lib (>= 0.18.1-1~nd14.04+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.18.1-1~nd14.04+1_all.deb Size: 2524926 SHA256: 987b81ef49a5b74e7f8dbbf4b1d7f4994bfae5b333ed3ffcbf482f92f0675892 SHA1: e3b55eb16705c59357df7f869a87f3f65f3e7715 MD5sum: 0a5dc35ad1dccdbb250aacb3c33cb3b4 Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6219 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (>= 3.4~), python3 (<< 3.5) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.18.1-1~nd14.04+1_amd64.deb Size: 1627372 SHA256: 77ec9163df214be09b5f62a67908575ff0fee76d0f82476f413898bbb7954042 SHA1: 442c88f264ec979ae5d1f744d0920bbbec196f61 MD5sum: d3c964cd937be0bba6b54879c780b5b6 Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 793 Depends: neurodebian-popularity-contest, python3-numpy, python3:any (>= 3.3.2-2~), python3-six Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1-1~nd14.04+1_all.deb Size: 170658 SHA256: 2b1c4715c9dbd5a7dd3b7b24b6b78bc132b3d6c14fa377389fbfde0a175104ce SHA1: 5567b2335a55f4bdcea62906b76a2c9e30d7c402 MD5sum: ee4642ab47735474651deb6bcdec1b31 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-psutil Source: python-psutil Version: 2.1.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 248 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python3 (<< 3.5), python3 (>= 3.4~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python3-psutil_2.1.1-1~nd14.04+1_amd64.deb Size: 59804 SHA256: 221d8c34ef999deeaaa8d7e630c98af853de397738159dbbdd5db2a454cf9eb5 SHA1: 3bae4de769b768f0bdd99c0db85721ba7c0d9dd2 MD5sum: be4614304d66823dad1f0b88903ef2e2 Description: module providing convenience functions for managing processes (Python3) psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. . This package contains the Python 3 version of psutil. Package: python3-py Source: python-py Version: 1.4.30-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.30-1~nd14.04+1_all.deb Size: 66732 SHA256: e4dcfe9e8309d67391f594dda9d7269daafc070875fe12b73024f8ed01380fbd SHA1: 094aa133c0e1a436c886640ebb23027d7156c562 MD5sum: 64d7b6a21473e75644ae095e83d922e9 Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pydotplus Source: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, graphviz, python3-pyparsing (>= 2.0.1), python3:any (>= 3.3.2-2~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python3-pydotplus_2.0.2-1~nd14.04+1_all.deb Size: 20328 SHA256: f878b5238169859cdfca8f65be40ae18381ba955417d26ee2f9817d559ce616b SHA1: ab8151f6d6dc0ba917068caf83dc90953f3db4b7 MD5sum: a3b03af3de91f24f3694bf839962a4d5 Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-pygraphviz Source: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Depends: neurodebian-popularity-contest, python3 (>= 3.4~), python3 (<< 3.5), libc6 (>= 2.14), libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd14.04+1_amd64.deb Size: 73448 SHA256: 32136288586f97537cbe000ac7b5aa2ec61d34b1e7a110203cc243ab8f7679fe SHA1: 78f70f32e0f5eea19a53b363a4f06d93d11a5b06 MD5sum: 8fac7b97d9fa8f14fa8dcc014da57aa4 Description: Python interface to the Graphviz graph layout and visualization package (Python 3) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the Python 3 version of python-pygraphviz. Package: python3-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 334 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd14.04+1), python3-dbg, libc6 (>= 2.14), libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd14.04+1_amd64.deb Size: 107616 SHA256: a5e0a643e754a82ad84099e2a9596c2176cb90202cc5a5036430c241bcf7c839 SHA1: 2a2f51194fdadb07eb2aa013305aa72fbfffa417 MD5sum: bf09264532438b08e928c1b71fbc4200 Description: Python interface to the Graphviz graph layout and visualization package (py3k debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python3-pygraphviz. Package: python3-pytest Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3:any (>= 3.3.2-2~), python3 Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_2.7.2-2~nd14.04+1_all.deb Size: 102354 SHA256: 7d9fb489c914e606248a0294617b538a5193215ecf854ad29f08f28a65b97b68 SHA1: b3c50c08769a54606316afd8ec30a8c563c5a82a MD5sum: 26b41695fda6c1ec4c738f37d4570110 Description: Simple, powerful testing in Python3 This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 3 module and the py3.test script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python3-pytest, python3-werkzeug (>= 0.10), python3:any (>= 3.3.2-2~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python3-pytest-localserver_0.3.4-2~nd14.04+1_all.deb Size: 19282 SHA256: f04709d1c2db63f580e469b1f85733085237f906a06df554696474abd2df6f35 SHA1: 956eca0fd74095f7bf25e43f4dad4004e1bdd606 MD5sum: bb5531e1156ea9242f6270db14158e07 Description: py.test plugin to test server connections locally (Python 3) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 3. Package: python3-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pytest, python3-tornado Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python3-pytest-tornado_0.4.4-1~nd14.04+1_all.deb Size: 5738 SHA256: ed4ef503575a9ddc8f97b3d71b5b187de160ed49dd9c0a191fc2816a3ea31ef3 SHA1: 4dd119a69a7f70acfa2924f149ac973a10c9b35a MD5sum: 085c9055f034291d1ce05eec7de6655e Description: py.test plugin to test Tornado applications (Python 3) pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 3 code. Package: python3-seaborn Source: seaborn Version: 0.6.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 676 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-pandas, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.6.0-1~nd14.04+1_all.deb Size: 117808 SHA256: 6a23a5022fcb745801cc9224189e0789a03f8e182b949890012fd76c1cc92b72 SHA1: 16d74485aabf829249323d555da245fec8fec2cf MD5sum: f23b413abf7ffa1927df6b54c6da4a86 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 3 version of the package. Package: python3-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70 Depends: neurodebian-popularity-contest Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python3-setuptools-scm_1.8.0-1~bpo8+1~nd14.04+1_all.deb Size: 10198 SHA256: ff11bd9f5b7c1d7d2e2eed7f9219d3ded1d3d8d73d01e08637362b6c7e35a84f SHA1: 27fcdd8880354be354775a704569bcc0f80a5d17 MD5sum: e63ae3aa2d57a735ac152d987a263b4e Description: blessed package to manage your versions by scm tags for Python 3 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 3. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 11092 SHA256: 79a6de23973f24df722d22b027db5db5b132861197a2ca85de60db65a4045cb9 SHA1: a8ae88a5d47c0725e8e7db7f9485915ab5594566 MD5sum: 54c44c9fe9707b2f852bda2e5fed9373 Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15115 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-six (>= 1.3.0), python3-skimage-lib (>= 0.10.1-2~nd14.04+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-matplotlib (>= 1.0), python3-nose, python3-pil Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11919718 SHA256: 1d1b5c2fbf5fef5eb25d8d619bac87cfcb6362a1c97dbd10fae204f3acbeb3f4 SHA1: ca840ff46b54b7653bfbc18b965e09f2cfe9dd97 MD5sum: 42a0247cf46cf44a61b843f8c6c13542 Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-skimage-lib Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6280 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.14) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.10.1-2~nd14.04+1_amd64.deb Size: 954786 SHA256: 4efcd1de2c28b268a130903955c4e4937833e5451a3158f49fdde759420f710c SHA1: e810079e674b2545eac06aa9e097d7fafb4b7a04 MD5sum: bbe8c9bb26ee11359ce73bb44fb1780a Description: Optimized low-level algorithms for Python 3 scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 3 libraries. Package: python3-sklearn Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5281 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.1-1~nd14.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.17.1-1~nd14.04+1_all.deb Size: 1223446 SHA256: ab6211ebbc737d34504299e8509826fd95f1a17c789a817803661f99ebd6dc6c SHA1: 383caec81131296f77620f551c2608789d245444 MD5sum: d0ef996d48f5c5eaa5ed5e971db194f1 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.17.1-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4559 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.17.1-1~nd14.04+1_amd64.deb Size: 1044718 SHA256: ad922959b24901404a14d02f12fda7fe88c3fbe75c7569ecff9df0c8e596732b SHA1: f0292e7d807d95c53740168fb2ed3d7a51f65d01 MD5sum: f238e9418f6455417841cf6a65c40a8f Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-smmap Source: python-smmap Version: 0.9.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-nose Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python3-smmap_0.9.0-3~nd14.04+1_all.deb Size: 20214 SHA256: cda44a9bd7fd2d600821890244e1efb781e16a47c3304851e94261a4b46a179e SHA1: f7befc9c26523273862deb8eae4d8d2667ec2cc0 MD5sum: 65c3b4e6a7390cfcd750393173ec8121 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 3. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3:any (>= 3.3.2-2~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd14.04+1_all.deb Size: 117200 SHA256: 16e1aaa6f2ea3e37894d69d01a1b30aa08b677a195343faf5f359d3c7adbea0f SHA1: e9a95bac6f5e7264d3035deb962fe65dfe02d031 MD5sum: abb571938ace7e00ea171c003e50a9ad 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 164 Depends: neurodebian-popularity-contest, python3, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.4.1-1~nd14.04+1_all.deb Size: 35610 SHA256: d069307c26a64719686d40835ad5bd3af381fe12033abcc7dc9352834f413c8e SHA1: 8b3170ee1f2931f35b5813c18533e3e3f1ed72d4 MD5sum: 8c0c54aaae44b01164cfe57386e0b2e9 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-w3lib Source: python-w3lib Version: 1.11.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), 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~nd14.04+1_all.deb Size: 14190 SHA256: 008f9ec2dd25186b977ab66c67873429efcf26bbc5ffaa02650ab0ed4c103a63 SHA1: 775d95cf272476a5deaa8eef7c1941e362c784a5 MD5sum: 0562a201189207e45c218e5a5465deb2 Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: python3-werkzeug Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libjs-jquery Recommends: python3-simplejson | python3, python3-openssl, python3-pyinotify Suggests: ipython3, python3-pkg-resources, python3-lxml, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python3-werkzeug_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 163216 SHA256: b685e053e4c5536d78e641e5b26441a9938a61038832b9d616215ddd4082b56b SHA1: 4787e0c8be6967ba696d4b011edd2562cbde87cb MD5sum: c02d0f4c7f7e88cc1acde12249702472 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.8-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2922 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.5, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk6, nifti2dicom (= 0.4.8-1~nd14.04+1), nifti2dicom-data (= 0.4.8-1~nd14.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.8-1~nd14.04+1_amd64.deb Size: 409470 SHA256: 24e5d509bb59afb6eb08f799df0c5f197390cc31478034361614350894680d27 SHA1: 027a13571b641be7f3771ee51d9bf3c1d4029a08 MD5sum: 5300b6da08958fabb787d21c322adee9 Description: convert 3D medical images to DICOM 2D series (gui) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the Qt4 GUI. Package: remake Version: 4.1+dbg1.1+dfsg-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 336 Depends: neurodebian-popularity-contest, guile-2.0-libs, libc6 (>= 2.17), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_4.1+dbg1.1+dfsg-1~nd14.04+1_amd64.deb Size: 150664 SHA256: ee318f10204f7e4fa0eb7b8d6e155bef06bb21344940546a6fba4002dd925af5 SHA1: a4d722c8229ec69331ff935dd3099be8976227ba MD5sum: 2ed6d873972363f0ed280e68cfaed743 Description: GNU make fork with improved error reporting and debugging Modernized version of GNU make utility that adds improved error reporting, the ability to trace execution in a comprehensible way, and a debugger. Some of the features of the debugger are: * see the target call stack * set breakpoints on targets * show and set variables * execute arbitrary "make" code * issue shell commands while stopped in the middle of execution * inspect target descriptions * write a file with the commands of the target expanded Package: singularity-container Version: 2.1.2-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 335 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.1.2-1~nd14.04+1_amd64.deb Size: 54476 SHA256: 9b83b9ad4615057203e7745ab556bffe882a696df799b5152af8c71a6e3e7d4c SHA1: 3178454a4944a7cbbdaae4ef92f03f7751c84820 MD5sum: 10d2a5f409d949b6689001455ee27e90 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 9749152 SHA256: c83baf314478407e2f1b908e55554b5645b4a1d52f9ef5be18864a6ec74c454b SHA1: 993dd179e97b25766a9dd6b1d5884041448089a3 MD5sum: d92e890135a7c0c8eb5f4102b380b07c Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 45484386 SHA256: 182e2818ac165f6a04ef610a17226e4019e76b6403242ce5106dc8084088f456 SHA1: 4ede6932c3e3b32e11bd0e1360522b3cda6e69e2 MD5sum: dd2edf6746682da9d77ea73d1ee36418 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 8935290 SHA256: 5742ed7248b597e91212ca03e53541e520bbeccc2d59f865b278b7c94362661e SHA1: 32542240cefbb5d936731db01ffc3175348bc80e MD5sum: 511c71c1ed452c9f1c5dd547eaade5c8 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: spykeviewer Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1975 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.4-1~nd14.04+1_all.deb Size: 1291946 SHA256: 60a2857f96c3cd0e6f58d20a188950adf7574b8d5289daf8ba2d7dabe63f58dc SHA1: 69a899c9566acd0b4a3babe34e37a5173d046249 MD5sum: 777bf20e134ee592f75d0ef5c1d63a1f Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 22678 SHA256: ea800adb74820759f1c8041031b4b396c15b127a50f03a44c9e7e374649c351e SHA1: 0b16001f8fc76a1fadef374d9f61187cc11edfcf MD5sum: 3ece230b8a5225d2691618b7b10e78ba Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: stimfit Version: 0.14.10-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2388 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1+dfsg), libwxgtk2.8-0 (>= 2.8.12.1+dfsg), python-numpy (>= 1:1.8.0), python-numpy-abi9, python2.7, python:any (>= 2.7.1-0ubuntu2), libbiosig-dev, libsuitesparse-dev, python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.14.10-1~nd14.04+1_amd64.deb Size: 651658 SHA256: 8e312f994612ea799951c666fa502828c2b518b9f026510d3b77f23063c5c19b SHA1: 40f7de64e9c8c8c5ff5020215af5b4f66a637c22 MD5sum: 6df10bd987a3d24e3f1b6252bad306a5 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: 0.14.10-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29577 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_0.14.10-1~nd14.04+1_amd64.deb Size: 5972502 SHA256: f6243c9c3ad4bdf9f79efb5c3de427b879cf20efd1c4b227a259b453a62699ac SHA1: 67b42935550185bfcbd2f200a48fadbaaf75c7aa MD5sum: 9d5b59332f5e8ec777c0097d1f106a3c Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. This package contains the debug symbols for Stimfit. Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 358 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 85950 SHA256: 9a51b163a417b1a421415111ce4ddedea08a840e943a7a144f782b37944d8699 SHA1: 77a25da70008038d7ccaa99042ef1b0fe2a04229 MD5sum: f54d2b8e28fcffe650211599731dab19 Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: utopia-documents Version: 2.4.4-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19367 Depends: neurodebian-popularity-contest, libboost-python1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.10 (>= 1.10.0), libglu1-mesa | libglu1, libpcre3, libpcrecpp0 (>= 7.7), libpython2.7 (>= 2.7), libqglviewer2, libqjson0 (>= 0.7.1), libqt4-network (>= 4:4.7.0~beta1), libqt4-opengl (>= 4:4.5.3), libqt4-script (>= 4:4.5.3), libqt4-svg (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libraptor1 (>= 1.4.21-3), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), python:any (>= 2.7.1-0ubuntu2), python2.7, python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_2.4.4-1~nd14.04+1_amd64.deb Size: 5158484 SHA256: b75e4838af05fc074984e33c3dc1a0a0968afb89b57b9944de7f646498662800 SHA1: afa027cf35010b12323d2267074ef9db6a38f7b0 MD5sum: 4dbebd3b035248d3e384ff709705a35d Description: PDF reader that displays interactive annotations on scientific articles. Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. It makes it easy to explore an article's content and claims, and investigate other recent articles that discuss the same or similar topics. . Get immediate access to an article's metadata and browse the relationship it has with the world at large. Generate a formatted citation for use in your own work, follow bibliographic links to cited articles, or get a document's related data at the click of a button. . Various extensions provide links to blogs, online data sources and to social media sites so you can see what other researchers have been saying about not only the article you're reading but its subject matter too. Package: utopia-documents-dbg Source: utopia-documents Version: 2.4.4-1~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47385 Depends: neurodebian-popularity-contest, utopia-documents (= 2.4.4-1~nd14.04+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_2.4.4-1~nd14.04+1_amd64.deb Size: 46251400 SHA256: 38be8f579de44ab6c20c96eca5103793a68efe0d786a8913abcdf6a3f86e5c66 SHA1: 917ba544ad67901bd00836b705af847a3c3c4e44 MD5sum: 04498e72ef22c1069067bbf7ea2a5c91 Description: debugging symbols for utopia-documents Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. . This package contains the debugging symbols for utopia-documents. Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 315 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 46628 SHA256: 99879ed027ea24549ba6c17fd51901a0282aea89609fad41fc4cf6e6919294e4 SHA1: e78f9e27a5b9cc7d1f18d571eb549caf7aed28c3 MD5sum: 220ed03353fa1bf02c2a1f9cdc18905a Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5258 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_amd64.deb Size: 1098504 SHA256: a567a702e1c24615265c3c07a530c2edc93b34118bd54deb639a086f992f3fda SHA1: b31602640c7180049f8c3138e7c5c347df0eebec MD5sum: 5676362401ef27d93a32ffc7451914fa Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 194 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~nd14.04+1_amd64.deb Size: 54016 SHA256: c5e6640391b7ff54144974d1b909fa8b3630ab8d1f58bbfa55f682584588f7ae SHA1: 895765f646a9849e4af4397c7b86a6819d7a007c MD5sum: 8a624dddf1567abc7d31f3031539f74d 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