Package: aghermann Version: 0.5.3-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1740 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.3), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libfftw3-3, libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.16.0), libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.0.0), libitpp7, libpango1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.6) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_0.5.3-1~nd70+1_amd64.deb Size: 445494 SHA256: 9b43bddcdda9572a6821821d72d3e6d8fa921b8312984ca056d540d973b38679 SHA1: 765e0c7dc03da252769c1055db4cf5aff2bf7092 MD5sum: 0ca0084930758c9de3639d08f82b3036 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility, EEG power spectrum and power course visualization, and Process S simulation following Achermann et al, 1993. Package: ants Version: 1.9.2+svn680.dfsg-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 41892 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.20, libstdc++6 (>= 4.6) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-3~nd70+1_amd64.deb Size: 12729054 SHA256: 516a2648d007e63c4de69c2784bbc3204bce6c3b5ee548ebefd562edd8a36f2c SHA1: a772e941b219c49d6f8ba0ea0fd1a606bcf0910b MD5sum: 8ae964829eaa5a0f1de06ca4241ef029 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). Package: biosig-tools Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.2.5), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 13884 SHA256: e030285a150bcfe41d68a5522f488f6302aa225abf2c609755823daf673984dc SHA1: 230b4b2ae1bcbefc6b157e2dbc55d36d4e5b3901 MD5sum: 5a038f1ebb73f958a4857fc7d8cab279 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: caret Version: 5.6.2~dfsg.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19128 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvtk5.4, zlib1g (>= 1:1.2.3.3.dfsg) Recommends: qt-assistant-compat Suggests: caret-data (>= 5.6.2~dfsg.1~) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.2~dfsg.1-1~nd70+1_amd64.deb Size: 7373942 SHA256: d636f6be4736d17c78f06bb805dd6d469aa4bb4a3dc736cbb6c877e26adf9ad2 SHA1: 5007aee770f501a4f0002d7167c688e6625f51d9 MD5sum: 3828f2e67918844573e8b877bcf6ae8c Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes: . - Map volumes to surface via PALS atlas - Multi-resolution morphing - Projection of foci via PALS atlas - Surface-based registration - Surface flattening . Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more imformation. Package: cde Version: 0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 988 Depends: neurodebian-popularity-contest, libc6 (>= 2.3) Homepage: http://www.stanford.edu/~pgbovine/cdepack.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1-1~nd70+1_amd64.deb Size: 356878 SHA256: 3435a03ebc0bd6cecbf3d6bad539be0bae39d575c327e2bc7c8a93e168edfc69 SHA1: e8a256b6a47a28b80111cd535375853106ada2f0 MD5sum: 4457b40973d5e7fa0bf3cc4ae40167a5 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cgroup-bin Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcgroup1 Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/cgroup-bin_0.37.1-1~nd70+1_amd64.deb Size: 66046 SHA256: 6943e3e514829289c63c84f6112178c4bf02a24b7b6a31c688839b83aa659a59 SHA1: 904415be370d6ab952e17e040fadd0ef13a611e0 MD5sum: f11926de39d36d36c044fb12e6eb2da0 Description: Tools to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . These tools help manipulate, control, administrate and monitor control groups and the associated controllers. Package: cmtk Version: 2.1.3-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 21429 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libcharls1, libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libmxml1, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), libtiff4, zlib1g (>= 1:1.2.6) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_2.1.3-1~nd70+1_amd64.deb Size: 5828386 SHA256: dbbd1fb08f4efdc7c5bbfd40aee12cbc6dfc5baa96cb5c651e8220fd043829f5 SHA1: 113fea5579349d8c5615c19704d828dd4def17f6 MD5sum: bb5e61f511b4b619e9beceea881cd760 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: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 13549 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.7), libcgroup1 (>= 0.37~), libclassad3, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 1.95.8), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 2), libglobus-common0 (>= 14), libglobus-ftp-control1 (>= 4), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 5), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 8), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 9), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgsoap2, 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 (>= 8.10), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), perl, adduser, libdate-manip-perl Recommends: dmtcp Priority: extra Section: science Filename: pool/main/c/condor/condor_7.7.5~dfsg.1-2~nd70+1_amd64.deb Size: 4554358 SHA256: e1f658971580c38fb4ebd048aba21811686c7951594ca876c8882273dde6c173 SHA1: e9cb1d8d5ab5e36adb538284ad222bdcb9485115 MD5sum: 523e7334a1aa356fb341431a79034e36 Description: workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor 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 system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . The Debian package uses Debconf to determine an appropriate initial configuration for a machine that shall join an existing Condor pool, and moreover, allows creating a "Personal" (single machine) Condor pool automatically. Package: condor-dbg Source: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 33311 Depends: neurodebian-popularity-contest, condor (= 7.7.5~dfsg.1-2~nd70+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.7.5~dfsg.1-2~nd70+1_amd64.deb Size: 11460516 SHA256: 4434c05d45808676aa73f3135ca5c3580121b2f56afc5c261f7cd2a1debbbc99 SHA1: 759cdc3f2b271d21d267c13660dcfb42350f2896 MD5sum: 60eb403f26e2b03eae8f4a4819fee6f3 Description: debugging symbols for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor 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 system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-dev Source: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1870 Depends: neurodebian-popularity-contest Priority: extra Section: devel Filename: pool/main/c/condor/condor-dev_7.7.5~dfsg.1-2~nd70+1_amd64.deb Size: 422074 SHA256: 0b04828538460520feaa804e0a796fce6353ac663164a9092224fd2246de9297 SHA1: 51d8ad168b3bc35a5595e61d8d7453f5031503e1 MD5sum: 384e2d9344bf526079825e2ad7fc5925 Description: development files for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor 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 system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of Condor add-ons. Package: condor-doc Source: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5269 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.7.5~dfsg.1-2~nd70+1_all.deb Size: 1285836 SHA256: 8ccccc6f4be9620b48d9883a2aa5cf91e7af9e98ddbbb2f664c2e6eb8f697869 SHA1: 734869e20e10b1e495b4eea9b91c90c041d40579 MD5sum: e6364a52cf39b93af6f86446e011f65b Description: documentation for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor 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 system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: connectomeviewer Version: 2.0.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1884 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-cfflib (>= 2.0.5), python-networkx (>= 1.4), python-nibabel, python-numpy (>= 1.3.0), python-scipy, python-chaco, mayavi2, ipython Recommends: python-nipype, python-dipy, python-matplotlib, python-qscintilla2 Suggests: nipy-suite Homepage: http://www.connectomeviewer.org Priority: extra Section: python Filename: pool/main/c/connectomeviewer/connectomeviewer_2.0.0-1~nd70+1_all.deb Size: 1354960 SHA256: 8dac2dd8c94bd722022ce66a8626888c5098824e377c6ba59f9e6007f069fc0f SHA1: 08ae32fb442249cb21e757c5e46147ff6b4baeef MD5sum: f7f8eadd91fc20cecc0c5acbfd65b215 Description: Interactive Analysis and Visualization for MR Connectomics The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics. . Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit. Package: coop-computing-tools Source: cctools Version: 3.4.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4143 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfuse2 (>= 2.8.1), libglobus-common0 (>= 14), libglobus-gss-assist3 (>= 8), libglobus-gssapi-gsi4 (>= 10), libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), libncurses5 (>= 5.5-5~), libopenmpi1.3, libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), libtinfo5, python Suggests: coop-computing-tools-doc, condor, gridengine-client Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.4.2-1~nd70+1_amd64.deb Size: 1385724 SHA256: 3e3d109bc2270fb3aaa50af892e1758c0a833bc2b4142041d24b58f8ec47bb9f SHA1: 2f24ce46104eb364890a38d7b3fb230dfaeb2eac MD5sum: 1cb17a03918c8b97568dc66fb129be01 Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.4.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 956 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.4.2-1~nd70+1_amd64.deb Size: 223124 SHA256: 966931cea9c2772f2f274e8f28f56862ea3bb2ce7e75b925db29948b5a327135 SHA1: 7823084ce78245027b30988d842a5c2059714e33 MD5sum: 73c8560240dd6698aceb86886f1abe28 Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.4.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2319 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.4.2-1~nd70+1_all.deb Size: 310890 SHA256: ca1fc4a117105875244c5c1a16994aa4e1c7496de9d177e96bbd351def1da0b5 SHA1: 154b372d4c5b7a25d5885e2ae8d79e64808671b2 MD5sum: c5f2ca94795a12217de0438befa22e8d Description: documentation for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides the documentation (manual and API reference) in HTML format. Package: debruijn Version: 1.5-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfftw3-3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.5-1~nd70+1_amd64.deb Size: 38360 SHA256: 236ade5448b1bbf42d3b197b6f7ff00767b3d5246e8f8bdc6f1cd96dc5b74875 SHA1: cdf5ed29292d1cf1df8ed586c1c24640ffd288ff MD5sum: a97ffc4e028722206cf3c01d904e9044 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: dicomnifti Version: 2.29.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 580 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_2.29.1-1~nd70+1_amd64.deb Size: 182656 SHA256: a3ba4bb07371746bb6f95b6cfe4679021ca3ef7bfa916bba41dfa8e0ab00e75a SHA1: 4568212d816e88d19a79687686936b28250538b9 MD5sum: 018bb760a8962ba58032724ddef8e22e 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: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1907 Depends: neurodebian-popularity-contest, libmtcp1, libc6 (>= 2.9), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_1.2.4-1~nd70+1_amd64.deb Size: 820528 SHA256: b980f0f02c9d5a720b11afef082b43c232c93e4092039bdbab64a3dc4e038ed9 SHA1: c483de1f49b6901434c3b3129bbcd2795c762837 MD5sum: e70c834d021b1bda37e4e6ee4684a618 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 OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains DMTCP binaries. Package: dmtcp-dbg Source: dmtcp Version: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18412 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_1.2.4-1~nd70+1_amd64.deb Size: 5095148 SHA256: a30e5d56c15347807abe90920567fa2b1ef9938034511a87bfd91eae67d6dcfe SHA1: f027b6abcae4519890157ce2819dc7215378084e MD5sum: 403b0d8ec983f44d6d9d69cd931eaa57 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 OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: eegdev-plugins-free Source: eegdev Version: 0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 45 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd70+1), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libusb-1.0-0 (>= 2:1.0.8), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/eegdev-plugins-free_0.1-1~nd70+1_amd64.deb Size: 19138 SHA256: 679eb81fb34a953cd70cf60e0a37978545a0e523630099d3f787d6312fb95060 SHA1: e08286049ee42326926d1152b18d316a82522dbf MD5sum: 3ef386b8a01b831962081a5926595a30 Description: Biosignal acquisition device library (free plugins) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the devices plugins that depends only on free components. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd70+1_all.deb Size: 7224720 SHA256: a25c47daa7e5cabbab1e2864994d7ca0d5b207e5609c31fe0f62c32fae733590 SHA1: 6a5b78425b50d335c0f1e49bc20cd68aae0ab3fc MD5sum: fdcfc99b0c53436258c20f5eee125e50 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: eegview Version: 0.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libeegdev0, libmcpanel0 (>= 0.0), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegview.html Priority: extra Section: science Filename: pool/main/e/eegview/eegview_0.0-1~nd70+1_amd64.deb Size: 13090 SHA256: 0cd9b3391951f0b54841cc3f4cadf3acd9069f94518f9e9629f75d63340cc37b SHA1: f0450b1a88c93694bd1d23ce2bbb25a8d4a6ebd1 MD5sum: 55e8a7fe33d248c3d17c4d9332f1ffab Description: Software to display EEG data in realtime This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment. Package: fail2ban Version: 0.8.6-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 339 Depends: neurodebian-popularity-contest, python (>= 2.4), python-central (>= 0.6.11), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-gamin Suggests: mailx Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.6-3~nd70+1_all.deb Size: 103474 SHA256: 7411a9f1a59f35f2ce8577fefc8166f6427cefb06658182bcbf71b6e891beff9 SHA1: 97021044a86477b6d10483835d3941d86cb734f1 MD5sum: 83a9eca41b424ffe7aa0d86ce093f936 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. Python-Version: current, >= 2.4 Package: freenect Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.1, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 7170 SHA256: bf064b5ace1fbd820ffd7c5b55daeef3d12aaa03658c86d09efdd32388ce6aaa SHA1: 7a62dfb6914c1131fdb3f109b63318a671829b95 MD5sum: 8f5ff135ec8165ffc4b6ea148fe4ef60 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: gdf-tools Source: libgdf Version: 0.1.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-program-options1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.2-1~nd70+1_amd64.deb Size: 54644 SHA256: f90120949dd4f968be1db4abd0d73287c452e13140c992fc1bd8eb2922c0dbb5 SHA1: 1ab3b5412cda6a86578b4569c69f644306e6ef70 MD5sum: 1ad60dc1b0d0300a9e8c83afaaeb0d27 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: glew-utils Source: glew Version: 1.6.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd70+1), libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Replaces: libglew1.4 (<< 1.5) Homepage: http://glew.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.6.0-2~nd70+1_amd64.deb Size: 122682 SHA256: 4c20bc1643326f55e9aa4f94749d8a6afbc898160934f2fca18d49d629b53ade SHA1: b97ed329470fb6c025a6910621b6cd84d6fac010 MD5sum: 4f86ee94b6047977d4c986265305d6f2 Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew1.6-dev package. . This package contains the utilities which can be used to query the supported openGL extensions. Package: guacamole Version: 0.5.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 255 Depends: neurodebian-popularity-contest, guacd (>= 0.5), guacd (<< 0.6) Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole_0.5.0-1~nd70+1_all.deb Size: 234238 SHA256: 96b75d8fe0c1fbbe639e93ec390f41e97171b41dde97d88602738d4721fedd75 SHA1: ff41438c3ea0373c119425ccda720f0fd0600bdb MD5sum: 210c564f9a1bce9d9a102a6da951900c Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole Version: 0.5.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole-tomcat_0.5.0-1~nd70+1_all.deb Size: 4944 SHA256: bffcab094d4ac872970a7b85d6858b36c1158cfdd1c95e1e2c40a44ce06f723c SHA1: 8d5cfb16c429fb1eb7679a0fb58036f6ae517fa1 MD5sum: 83b28305081b19dc04ac74a04cccfd65 Description: Tomcat-based Guacamole install with VNC support Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. . This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Version: 0.5.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.2.5), libguac2 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacd/guacd_0.5.0-1~nd70+1_amd64.deb Size: 11132 SHA256: 0526e6a667be5459996b206696324bfb7619af5d6896cb2bde78782a6f0911e0 SHA1: c63406dbbdab6469445969bbfc2d8148c6542ddf MD5sum: c15e79b32a64d8112208abbde87caad9 Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: ipython01x Version: 0.12-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3463 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-zmq, python-matplotlib Suggests: ipython01x-doc, ipython01x-parallel, ipython01x-qtconsole, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.12-1~nd70+1_all.deb Size: 941230 SHA256: 80a8235e537a3d09fc714f3efc3331718104ddd2d107797e44010edc33d90d7b SHA1: 084c50d1370ec7ff036521c8d97aab58545cf8f8 MD5sum: b933129d106e8860f94ad5d099f47963 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.12-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12419 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.12-1~nd70+1_all.deb Size: 4308518 SHA256: afb8b829d47c1a778dfef601d1e88e4691fb02c84f2e566e0d952a0ace379d23 SHA1: 348f580408a1617d1f6ba3c4f53e6986e679bde8 MD5sum: 80ca15ac87d8b64b1b18f02783510a81 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-parallel Source: ipython01x Version: 0.12-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 508 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~nd70+1), python-zmq (>= 2.1.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-parallel_0.12-1~nd70+1_all.deb Size: 116082 SHA256: 4d1681c7a3b11bae9e8f4a7a12765f8a6aebd8ec0d5f009efc534c90c90f31fd SHA1: 5cd9a67a28ca41878a474ca1c29641dfd535dd8c MD5sum: d2bcee68c02a9f6a8a3656bf58a4e7aa Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the parallel processing facilities. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-qtconsole Source: ipython01x Version: 0.12-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 339 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~nd70+1), python-pygments, python-qt4, python-zmq (>= 2.0.10.1), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.12-1~nd70+1_all.deb Size: 80542 SHA256: b9de549149bf7e613610ce341ae67bc1b432bd600662ed5127763666b9accd56 SHA1: 720b5714680e5937e210d36b76fbb18ddca88a35 MD5sum: ce401cdf02f5b83ce261637bbbec4f0e Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the qt console. Package: isis-utils Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 941 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmuparser0debian1, liboil0.3 (>= 0.3.1), libstdc++6 (>= 4.6) Homepage: https://github.com/isis-group Priority: extra Section: science Filename: pool/main/i/isis/isis-utils_0.4.7-1~nd70+1_amd64.deb Size: 271212 SHA256: 4017f4a3e56c998b5f276c39ed371cd04b8140907540be37d606ef40aea7376f SHA1: 5c685ea0a27a05eb1a29f22bfecece60e9ca6a2d MD5sum: 8c989e2f0ed79484796e7667374cfcd8 Description: utilities for the ISIS neuroimaging data I/O framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides a number of utilities to process neuroimaging data. This includes a multi-format converter and tools to inspect image meta data. Package: klustakwik Version: 2.0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd70+1_amd64.deb Size: 23078 SHA256: 408ce54522f5db716c99edea2089993436feb23cef17c2dfa7766beea8b76a68 SHA1: 0287982a5f922663215618f48730f7b209f7f7c9 MD5sum: 93df9b567b8a475c135145bc332a5656 Description: automatic sorting of the samples (spikes) into clusters KlustaKwik is a program for automatic clustering of continuous data into a mixture of Gaussians. The program was originally developed for sorting of neuronal action potentials, but can be applied to any sort of data. Package: libbiosig-dev Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1596 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd70+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 390066 SHA256: c3cd17f967217596234dfd1fd37fdb118ed44f2c5eb11076d105d3f5ef42e613 SHA1: 8aa24415d86eb27ad0bb655aa57aa31f6be4b0c7 MD5sum: 05c369110d00dd30956fe701698203db 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: libbiosig0 Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 884 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 312346 SHA256: 00d03d614a0c671bab08d50e450daf9a8fb9b3de7e35d0daa3c1ce44f00982e6 SHA1: 4ad16ca49856211712e371b93c1fd0d1aa5e8cf3 MD5sum: 173d7f896db489cf8d0cca2fdb69324c 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: libbiosig0-dbg Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd70+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 68004 SHA256: bdbaed6dbcaee2e24711d4001dc1b8ef25a30afa1075bad36bfcf3fe3adf9519 SHA1: 9fd907c0f86f4aa80a39358d3626d7d0db04758c MD5sum: 2f034bceaac84eefb68e19665a435263 Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libcgroup-dev Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd70+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd70+1_amd64.deb Size: 17398 SHA256: 9b70596ab471f2ab23d987d531483f1af36055bc5d8d4772a5545aa8081811c7 SHA1: e324f022fe2b3482fbf00beddb40146569f9b644 MD5sum: 4a13cc06d0cde6bc9aed2b5c4c837380 Description: Development libraries to develop applications that utilize control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . It provides API to create/delete and modify cgroup nodes. It will also in the future allow creation of persistent configuration for control groups and provide scripts to manage that configuration. Package: libcgroup1 Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd70+1_amd64.deb Size: 38540 SHA256: 0bcf895f197ed19172cc3998452ef5d7c1b2fea61d68f385557d957a70e09047 SHA1: 3d877f31553b67cbac17086cb5ddc48aef394ad8 MD5sum: 8fefbb087322d3ca99c0d7bd5957c707 Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libclassad-dev Source: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2746 Depends: neurodebian-popularity-contest, libclassad3 (= 7.7.5~dfsg.1-2~nd70+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_7.7.5~dfsg.1-2~nd70+1_amd64.deb Size: 505142 SHA256: d4e2bd9d515a885f9c0a65b6fc5dc4881bf052bd1bfc14b71b69102d86e9212f SHA1: 46422ebe0a6e17a2029c180982b578aadfbec3e6 MD5sum: 26dd9cd365262b1b3a508dea8ffd5f39 Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad3 Source: condor Version: 7.7.5~dfsg.1-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 873 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Priority: extra Section: science Filename: pool/main/c/condor/libclassad3_7.7.5~dfsg.1-2~nd70+1_amd64.deb Size: 269800 SHA256: 23cf685296828981f3afe7dcec747518853cb45f6e062ec2e2bd142e04ac7128 SHA1: adc27274db6c40d6be2337478218a681a68aaa78 MD5sum: dfa0c99ecf171bcb02c3db6bb47a0f72 Description: library for Condor's classads expression language A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the runtime library. Package: libdmtcpaware-dev Source: dmtcp Version: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.4-1~nd70+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.4-1~nd70+1_amd64.deb Size: 6926 SHA256: f8582e7ae618fb76b56c65b297b93c9fc68d87067b12a24bb75359a66261cc72 SHA1: 2128d9450cbcf71b5e5658832439cfd7bedbe647 MD5sum: 18db9ccef86c93f27d27954286f6120f Description: DMTCP programming interface -- developer package DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides libraries for developing applications that need to interact with dmtcp. Package: libdmtcpaware1 Source: dmtcp Version: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.2.5) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.4-1~nd70+1_amd64.deb Size: 6794 SHA256: 368d1126f71ebc9756943c53876d206d5ce40c127f75d6bbd2ad4b3e9d348bcf SHA1: 8b028022eced3dea859e1850ba5ce4cbfe419bb4 MD5sum: ce532c409003de34cabd7ac16e1e286b Description: DMTCP programming interface DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides a programming interface to allow checkpointed applications to interact with dmtcp. Package: libdrawtk-dev Source: drawtk Version: 1.0b-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 57 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_1.0b-1~nd70+1_amd64.deb Size: 44284 SHA256: f25ca99b37c9bcbe2217883c442346dd4cf0e150ee9fc9622d85961c6dd765d5 SHA1: 6364319d66c7328a077a2556ae06aff9b7d57b32 MD5sum: 3fee99c7126fefe1dcfa8d2973cceea0 Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL which allow us fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 1.0b-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.8.0), libfreeimage3 (>= 3.10.0), libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.10-1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_1.0b-1~nd70+1_amd64.deb Size: 33372 SHA256: 496c41f0da944bf083c3d5752db04ea7754af38f10920be8b8921bacfb5fe40b SHA1: bf943db26e4bd47d34b5e31c2c900dcf22b5fcdb MD5sum: 87a7c4d0574e1b5f364639af9613a072 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL which allow us fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 1.0b-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 154 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_1.0b-1~nd70+1_amd64.deb Size: 63328 SHA256: dfc3a2d9d8819452773149dee8905bfc3f99dc91fe9ff68aebde4531c7649df0 SHA1: 5e04e87f9a2aaddd81919c3a64f46bcd9f2e6fb5 MD5sum: 3d528a189df2822e97aa3b4a7c8fbe9e Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL which allow us fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Package: libeegdev-dev Source: eegdev Version: 0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libdevel Filename: pool/main/e/eegdev/libeegdev-dev_0.1-1~nd70+1_amd64.deb Size: 25324 SHA256: 62478e9b3dbf2320f337ff8083af261fd9807ef558dc74df2780e901a8cf17f3 SHA1: 031e10108543143383cf5f284c59d074a095a0bc MD5sum: ce424dc84d8bd56e8f5365549603f479 Description: Biosignal acquisition device library (Developement files) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the files needed to compile and link programs which use eegdev. Its provides also the headers neeeded to develop new device plugins. The manpages and examples are shipped in this package. Package: libeegdev0 Source: eegdev Version: 0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 43 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.2) Suggests: eegdev-plugins-free Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/libeegdev0_0.1-1~nd70+1_amd64.deb Size: 28576 SHA256: cc75d6e4562d43f9af08c7526d52109d829e2b02157ff986b7ed11441971a701 SHA1: cba15cd8714c018e6bb67add2f73df85122be523 MD5sum: 3790c0d1ce25cd59656211f3c650f71a Description: Biosignal acquisition device library eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the core library Package: libeegdev0-dbg Source: eegdev Version: 0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 153 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: debug Filename: pool/main/e/eegdev/libeegdev0-dbg_0.1-1~nd70+1_amd64.deb Size: 55018 SHA256: 97646fd489dcbeaff0af482630c142876949d5277e909b33cdc1aa07a5076238 SHA1: 246b336247076bcfc32b3adb5d2462f344089613 MD5sum: b9cefe0535a4e555b5a2e9a9522a1a2c Description: Biosignal acquisition device library (Debugging symbols) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package provides the debugging symbols for the library. Package: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd70+1_amd64.deb Size: 509864 SHA256: 9d12cf00824b926884b6259eea04aad3c85b603603b490a96d0ff4ce45064756 SHA1: fbce8e2f0c2bcb9306b10abf8d53c2fffbc36fca MD5sum: 28d181ca81e4c367057b63a98f8761d4 Description: lightweight C++ template library for linear algebra Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . Unlike most other linear algebra libraries, Eigen 3 focuses on the simple mathematical needs of applications: games and other OpenGL apps, spreadsheets and other office apps, etc. Eigen 3 is dedicated to providing optimal speed with GCC. A lot of improvements since 2-nd version of Eigen. Package: libeigen3-doc Source: eigen3 Version: 3.0.1-1.1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10344 Depends: neurodebian-popularity-contest, ttf-freefont, libjs-jquery Suggests: libeigen3-dev Homepage: http://eigen.tuxfamily.org Priority: extra Section: doc Filename: pool/main/e/eigen3/libeigen3-doc_3.0.1-1.1~nd70+1_all.deb Size: 2377384 SHA256: a49fd82e5f6a6d048154bd60d83245d840e38ec31ca1c90607c04479eaf6f04a SHA1: 551f098e9a8eae57dc8ac6baceb92ff5c87871e9 MD5sum: aefa7c3d5f3f5bfd5e3a481d932d7477 Description: eigen3 API docmentation Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . This package provides the complete eigen3 API documentation in HTML format. Package: libfreenect-bin Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 131 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.1 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) Breaks: libfreenect-demos (<< 1:0.1.2+dfsg-1) Replaces: libfreenect-demos (<< 1:0.1.2+dfsg-1) Homepage: http://openkinect.org/ Priority: extra Section: utils Filename: pool/main/libf/libfreenect/libfreenect-bin_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 48250 SHA256: a6929af29f450e9991fdd43f714eccb67ddd8a63ec3de057a3a74c430c184c6f SHA1: 1794e278955ec3618f548f493ab7ffef0be73348 MD5sum: f1382d6dc3de49ee9842c23741df4ad4 Description: library for accessing Kinect device -- utilities and samples libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package includes utilities and sample programs for kinect. Package: libfreenect-demos Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 7202 SHA256: 61725a8f5495d6c782374bd0e4d087d73b8ec339eabc8ec803f79b0ca236d2e1 SHA1: 72ef2f646036a04eb6c890d56e2977f2662bd013 MD5sum: 5e58099cb7f0032a4e15ce80366badc3 Description: library for accessing Kinect device -- dummy package libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package is a metapackage to do the transition from libfreenect-demos to libfreenect-bin. This package can be removed after installation. Package: libfreenect-dev Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libfreenect0.1 (= 1:0.1.2+dfsg-5~nd70+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 17142 SHA256: 1a6a5512c5657a3d1c4240de4cd9152e8f73c7e6977fb4f19bec5a24f1ed6e2c SHA1: 70cc2cbaad1ccdf74fde50a715404dc3000757f3 MD5sum: 00fb8b2d3120ba8c8bb1c60b019ddfa0 Description: library for accessing Kinect device -- development files libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect-doc Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 482 Depends: neurodebian-popularity-contest Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.1.2+dfsg-5~nd70+1_all.deb Size: 90648 SHA256: 4b3435d1a3e16b9d16c52421c7d9d2691b7b7b482a59cc27708d2640d87d4f3e SHA1: 86c081d288a0a66f6421745bbc1c5875f500a96c MD5sum: e29cec7c59813fa2cdfc5fd461c30e7e 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: libfreenect0.0 Source: libfreenect Version: 1:0.0.1+20101211+2-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 57 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+2-3~nd70+1_amd64.deb Size: 28732 SHA256: 2ee500f64f0b9df31b9823f1676eb19efc05d6593b8b11c242068bcd9fbfd39f SHA1: 6113dd1d45f9f5e64a6fe02ddcb3e2459d1b146b MD5sum: 20798503558a81a9fa1fb6d8e0a8bf49 Description: library for accessing Kinect USB camera libfreenect is the core library for accessing the Microsoft Kinect USB camera. Currently, the library supports access to: - RGB and Depth Images - Motors - Accelerometer - LED Package: libfreenect0.1 Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8) Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.1_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 37016 SHA256: 2bd4e7a31005143e5e322c2b37710a9ec9b58ee776b39b3add2d367fd1e9cda3 SHA1: 4e40437008fe3da4451a1ff38c215bf6d1a0cb65 MD5sum: 65901724d101676f53602e0ca515bf70 Description: library for accessing Kinect device libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the shared library of libfreenect. Package: libgdf-dev Source: libgdf Version: 0.1.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-1~nd70+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.2-1~nd70+1_amd64.deb Size: 19286 SHA256: fb90d626f097528ad32bf868c9ab3cde6a7663e2d72d1d0782beed8053ecf152 SHA1: efea37a64c3d74ecc54987f7ad055fbe2adb2b5b MD5sum: ae89541668e950098fb8c58ead57e521 Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 802 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.2-1~nd70+1_amd64.deb Size: 215276 SHA256: f5c2e5fe25b2fc84c12e0689eb7cee9f094e6e5af849d56b5fab506e55109677 SHA1: 4d7395b18c061a4eb8e2e54db6f2233f224fbf54 MD5sum: f95794557eaf21a3900cd6a47283aa9a Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2154 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-1~nd70+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.2-1~nd70+1_amd64.deb Size: 529590 SHA256: a6c6a9829abf54bde772dd56b0d8a1ff72f10a664926236b56aca87276bd32c8 SHA1: ad39a70f9333b6d89bd04bee4f131c9884f94053 MD5sum: 945242b270cb606c91c1940f2f3e4aab Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libglew1.6 Source: glew Version: 1.6.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 452 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.6_1.6.0-2~nd70+1_amd64.deb Size: 123940 SHA256: 33a9ba0fe3ac802b6d23f2f86fb888996f94515f4c994756309d8a71eb9fec4c SHA1: ee5c79e3b4c2809411bcbd35eb4795eb84c45492 MD5sum: b091e1b1b72e7e9eab3bee6b38531cbe 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: libglew1.6-dev Source: glew Version: 1.6.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1516 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd70+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.5-dev Provides: libglew-dev, libglew1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.6-dev_1.6.0-2~nd70+1_amd64.deb Size: 244766 SHA256: 879e8cbc171a0d91a53f976fa1d9fc88643d16aa088fd55cd9c916a3a8a901a4 SHA1: 109c74e755a47f8fc2d381b69bffdffa467e9c53 MD5sum: 45ca3944c7e5479c1ee68e58d07f051f 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[1]. . This package contains the development documentation as well as the required header files. Package: libglewmx1.6 Source: glew Version: 1.6.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 396 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd70+1_amd64.deb Size: 109656 SHA256: 58e344a1cd8d978dbace53ce9b21fa8d99ef7f3086c26787ffb132074baab324 SHA1: f32b2418baf85f7135817cf68e32ab1092250a87 MD5sum: a0388578786931dc368d72f8a26ae550 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, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.6-dev Source: glew Version: 1.6.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 524 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd70+1) Conflicts: libglewmx-dev, libglewmx1.5-dev Provides: libglewmx-dev, libglewmx1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.6-dev_1.6.0-2~nd70+1_amd64.deb Size: 101858 SHA256: cd8cae75207ef5007c0b32897aae9f0fde9198cd46d19cd645d90d3d5bf84108 SHA1: 9beee56dd7f49b08ab1e0a5eb5c5fc80f2a996af MD5sum: 6b759410b248e2cf1dae2db78903ba8a 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[1]. . This package contains the development libraries compiled with GLEW_MX Package: libguac-client-vnc0 Source: libguac-client-vnc Version: 0.5.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 30 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcairo2 (>= 1.6.0), libguac2, libvncserver0 Recommends: vnc4server Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac-client-vnc/libguac-client-vnc0_0.5.0-1~nd70+1_amd64.deb Size: 10628 SHA256: c8f3e926151316c35a8674dbbe611b931ca47a04391f12377de2b16e8f0a58d3 SHA1: 5930661b8a96315982f72d214b4b8d3f23e63bb9 MD5sum: 18f228dd22c40af5e203b2ebcf39ac93 Description: VNC client plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: libguac Version: 0.5.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, libguac2 (= 0.5.0-1~nd70+1) Conflicts: libguac1-dev Replaces: libguac1-dev Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac-dev_0.5.0-1~nd70+1_amd64.deb Size: 21998 SHA256: a8f25ee26ddbabab2e4860f5418f2139639ad3ceadd84f8bc1be873b2905e668 SHA1: 2868e57c8b6aed867febd1427774b666baa1cb47 MD5sum: ded3ac54ae691646e4e8d0af53d3de47 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac1 Source: libguac Version: 0.4.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 53 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac1_0.4.0-1~nd70+1_amd64.deb Size: 12812 SHA256: 62f7ee5c9ecc078d18af2c93fae1dbac804178a9954ea56ae65975585483bb49 SHA1: 1b5330fb0af9d61927517af719162ec9e58690a5 MD5sum: d26eea309cece99727574da40dbf24ee Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libguac1-dev Source: libguac Version: 0.4.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Depends: neurodebian-popularity-contest, libguac1 (= 0.4.0-1~nd70+1) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac1-dev_0.4.0-1~nd70+1_amd64.deb Size: 19532 SHA256: f209af0ff3971f8924f624d671df00e83a595eac2313a65e14932a09fa35c177 SHA1: 0975a566a40151542d25c2df5ae9ac24b720cc71 MD5sum: 7ab7ac83e9fd535e46815e4f4816331c Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac2 Source: libguac Version: 0.5.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac2_0.5.0-1~nd70+1_amd64.deb Size: 13786 SHA256: 9ba064c3c0da826e993137c6930f558e852cd8686cada2190b440c7de987a8bb SHA1: c4aa9ce4335bd8c3960ed6ac35ff6f9e6727abb2 MD5sum: b4aa10a43db02c91a15f5b24825556e4 Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libisis-core-dev Source: isis Version: 0.4.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 260 Depends: neurodebian-popularity-contest, libisis-core0 (>= 0.4.7-1~nd70+1), libisis-core0 (<< 0.4.7-1~nd70+1.1~) Homepage: https://github.com/isis-group Priority: extra Section: libdevel Filename: pool/main/i/isis/libisis-core-dev_0.4.7-1~nd70+1_all.deb Size: 68948 SHA256: 71ba81e336312edd85331e45ad6c689d1133fe332506a79eb1d4e41946534675 SHA1: 7761d9efa1a6a2cadc67a0f2e546b165f088f855 MD5sum: cc18de68a3f8d8942ad55d38751a2d01 Description: I/O framework for neuroimaging data This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides headers and library to develop applications with ISIS. Package: libisis-core0 Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9875 Depends: neurodebian-popularity-contest, libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.10), libstdc++6 (>= 4.6) Recommends: libisis-ioplugins-common, libisis-ioplugins-dicom Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-core0_0.4.7-1~nd70+1_amd64.deb Size: 2019594 SHA256: cdcafe66dd15c461a2729edeb8c576d48e2c7851ef89cfab489fd1ddfced9393 SHA1: b1f67caecec61424ed12e4ec992f7d1c03bb97f1 MD5sum: 43729e2dbee8c7de1dba835c87c60324 Description: I/O framework for neuroimaging data This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This Package provides the core library needed by all applications that are build upon ISIS. Package: libisis-ioplugins-common Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5602 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-iostreams1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libbz2-1.0, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libvia2, zlib1g (>= 1:1.1.4) Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-ioplugins-common_0.4.7-1~nd70+1_amd64.deb Size: 1459852 SHA256: 8c2acccca750c8f3eaf4fe0d731df4a4fdd413adfd3f1474f6dec1daba0f5de4 SHA1: b2ee68c5d832ecc73abc72e937c703518f23ee4d MD5sum: 4951b4b7f40ae7256669a41dedde5026 Description: data format plugins for the ISIS framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides plugins for data in NIfTI, PNG, VISTA format, raw-data access, as well as plugins for gzip-compression and tar-archive support. Package: libisis-ioplugins-dicom Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1414 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtiff4, zlib1g (>= 1:1.1.4) Homepage: https://github.com/isis-group Priority: extra Section: science Filename: pool/main/i/isis/libisis-ioplugins-dicom_0.4.7-1~nd70+1_amd64.deb Size: 371354 SHA256: bf0e86c60f5afb37972c9288c23f8bce8d840764fa8dac36955751a4a6516128 SHA1: 45780c7dc372670244e5190d46bf8bfcc9c5161f MD5sum: 7a94ddb3a274e1d32dfe1ca95fe9d563 Description: dicom io plugin for the ISIS framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. . This package provides a plugin to read data from dicom datasets. It reads single files, or whole directories (a DICOMDIR is not needed). Package: libisis-qt4-0 Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 Depends: neurodebian-popularity-contest, libisis-core0 (= 0.4.7-1~nd70+1), libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), liboil0.3 (>= 0.3.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6) Conflicts: isis-qt4 Replaces: isis-qt4 Homepage: https://github.com/isis-group Priority: extra Section: libs Filename: pool/main/i/isis/libisis-qt4-0_0.4.7-1~nd70+1_amd64.deb Size: 48828 SHA256: c67b545cc531d7bda63c31b639d8e4d6489de01d0372cf8dfd45d22f31920933 SHA1: 6888db247f5fd474e1fb39f24f81c8c1e6c94ef1 MD5sum: c12584164ff4e2cf63435f53322009a3 Description: Qt4 bindings for ISIS data I/O framework This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: libisis-qt4-dev Source: isis Version: 0.4.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Depends: neurodebian-popularity-contest, libisis-qt4-0 (>= 0.4.7-1~nd70+1), libisis-qt4-0 (<< 0.4.7-1~nd70+1.1~), libqt4-dev Conflicts: isis-qt4-dev Homepage: https://github.com/isis-group Priority: extra Section: libdevel Filename: pool/main/i/isis/libisis-qt4-dev_0.4.7-1~nd70+1_all.deb Size: 5992 SHA256: f848c976204b1b3090c9bcba159204365ee5620986f0cadd15bc6a6b8a9dde80 SHA1: a9cc9f1a3bd89a7545ffe60b6ccc874c874986a6 MD5sum: 96ef7f5956383a9fe46cea8c8843d7cd Description: Qt4 bindings for ISIS data I/O framework (development headers) This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libdevel Filename: pool/main/m/mcpanel/libmcpanel-dev_0.0-1~nd70+1_amd64.deb Size: 2392 SHA256: ae18b5e17e9b254156d3ffb73fdc17c8abe7e9da8d32a5408930a6c7dc7037a9 SHA1: 352b39d8b8b6a630b1dea50de1ec6d89bf41eb07 MD5sum: 30b0c24b2f9a2c1ac9b8557a5ab47712 Description: Library to display multichannel data in realtime (Developement files) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the files needed to compile and link programs which use mcpanel Package: libmcpanel0 Source: mcpanel Version: 0.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.14.0), libgtk2.0-0 (>= 2.14.0), libpango1.0-0 (>= 1.14.0), librtfilter1 (>= 1.0) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libs Filename: pool/main/m/mcpanel/libmcpanel0_0.0-1~nd70+1_amd64.deb Size: 54376 SHA256: 25aa09e49b93c8e306d3cf6fe7a3e2fa376cb1a39304b1944b3129b7eee5f14d SHA1: 9bec70ba1a28eb6562c376f097085683f527fd28 MD5sum: 5cee97a95228cbc6b03adf60abe5be4f Description: Library to display multichannel data in realtime This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. Package: libmcpanel0-dbg Source: mcpanel Version: 0.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 333 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: debug Filename: pool/main/m/mcpanel/libmcpanel0-dbg_0.0-1~nd70+1_amd64.deb Size: 122690 SHA256: 76d45f284f3fd61530546a5cb9202c5043d150312bfc6542246b5850a9bedd03 SHA1: 7ddee15e9c74c06b3dcee67f03af9c4801a491e7 MD5sum: 1a04d1cab0226f858266d1b58d10baae Description: Library to display multichannel data in realtime (Debugging symbols) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the debugging information of the library. Package: libmtcp-dev Source: dmtcp Version: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libmtcp1 (= 1.2.4-1~nd70+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libmtcp-dev_1.2.4-1~nd70+1_amd64.deb Size: 5346 SHA256: 8d3194b1494d3fa4f4efcaff66b504f58c99970942ba08d844643030cdcf7cfe SHA1: 4935f0f75134c557f5bd32ac888fd5ee39c82812 MD5sum: 967f3b2e63f9fe501e1435e239defaa0 Description: Developer package for libmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides header files needed for building programs with libmtcp. Package: libmtcp1 Source: dmtcp Version: 1.2.4-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.3) Suggests: dmtcp Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libmtcp1_1.2.4-1~nd70+1_amd64.deb Size: 42860 SHA256: 38ae74c8d36ba88326191b963147e4d2649f0e6f1d81c3ed07e06f8fa682110e SHA1: 7f40068622fc0f2d4da5abb56a19d62db590cf2a MD5sum: 0c394f880bd2f591ad2c522f21262f04 Description: DMTCP library needed for checkpointing a standalone process DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides libmtcp which is needed by DMTCP to checkpoint a single standalone process. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 252 Depends: neurodebian-popularity-contest Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-3~nd70+1_amd64.deb Size: 45648 SHA256: aaae22b7e6fb2cff0e333527eba2060353811161478b63e87f5683463e7610d4 SHA1: 4526a11fb63fd77b8814c07124cff631dda0b1a5 MD5sum: 1905a4da3042c914b708639fdba010b7 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1020 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.5) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-3~nd70+1_amd64.deb Size: 287870 SHA256: a47e3a2cb22760b3ed3ff1edccf906f4cd1c0783a0d811c08b594ef22a63f209 SHA1: 52c0772ea5f62b336ab232aa87b19889039f0b0e MD5sum: 27365b9e37b8d091027ff1bc5d9397c6 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. Package: libopenwalnut1 Source: openwalnut Version: 1.2.5-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5248 Depends: neurodebian-popularity-contest, ttf-liberation (>= 1.0.0), libboost-date-time1.46.1 (>= 1.46.1-1), libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-signals1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph80, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.2.5-1~nd70+1_amd64.deb Size: 1555922 SHA256: 21ee2752108caa30c45c253084906623a2ad034a3406e91418d9553a9698c5ad SHA1: def50aca5a11087f7aa606a80e43cb625cbf5965 MD5sum: d2df816bea8af7e66858415dc5041603 Description: Multi-modal medical and brain data visualization tool. 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: 1.2.5-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2092 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.2.5-1~nd70+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 2.8.1), libopenthreads-dev (>= 2.8.1), libboost-dev (>= 1.42.0), libboost-program-options-dev (>= 1.42.0), libboost-thread-dev (>= 1.42.0), libboost-filesystem-dev (>= 1.42.0), libboost-date-time-dev (>= 1.42.0), libboost-system-dev (>= 1.42.0), libboost-signals-dev (>= 1.42.0), libboost-regex-dev (>= 1.42.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.2.5-1~nd70+1_amd64.deb Size: 262300 SHA256: 5e7690fe143ebe4ceb159abf12d34064c5e0d1535fc39df7c75cd90336e49402 SHA1: b4f0f2a15d21db115ef0e571d6a739647b65a6e8 MD5sum: 2cdc468efd8620310b1cac0cad986bc3 Description: Multi-modal medical and brain data visualization tool. 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: 1.2.5-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41720 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.2.5-1~nd70+1_all.deb Size: 4303110 SHA256: 1c57d2c28420a18f4b5ee2c1c9d3a66956f42079ba9ff42d8872ac652b8bd1bd SHA1: daa3481e9ad2ef89349ba80d9343f0d79373f4fd MD5sum: 6108dc4a2e4f7318c7d9e1995123ae15 Description: Multi-modal medical and brain data visualization tool. 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: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd70+1_amd64.deb Size: 7792 SHA256: fd0540e8e09f8ec8b4f042032b107a65f506c52a9ec0e982c92be0f9affd3b66 SHA1: 6bf5ae5b92a7138626e6484e649f6d8357435f90 MD5sum: 2d86a22ab20cb9cb160e320a13e0daf9 Description: PAM module to move a user session into a cgroup Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This PAM module will move a user session into an existing cgroup by attempting to match uid and gid against the defined cgroup rules configuration. Package: librtfilter-dev Source: rtfilter Version: 1.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-1~nd70+1_amd64.deb Size: 12554 SHA256: 5ee6b14eefe27da305a340ca229c9513d123c5ba0a875c17fe705c3d90ae0919 SHA1: b4c951f803fc494bf38aa1e5e8a0ef8d10f7b3c3 MD5sum: 636676c0cce038db36562612970dd86b Description: reatime digital filtering library (development files) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package contains the files needed to compile and link programs which use rtfilter. Package: librtfilter1 Source: rtfilter Version: 1.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-1~nd70+1_amd64.deb Size: 30850 SHA256: 7a1391f2e9b639573c92e8aa675ff3bb44a1824278e90b410308deba721871da SHA1: 12fc868db8da2302be72bd1249bf03f14e49e02e MD5sum: 734e9614a2a202da19bccb5c5d0dac47 Description: reatime digital filtering library rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). Package: librtfilter1-dbg Source: rtfilter Version: 1.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 131 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-1~nd70+1_amd64.deb Size: 37006 SHA256: 45654ca06b779cec329f37f63f867070efaa3db7c397b43973ae6bc355ad53c7 SHA1: 61a2f9e3f907ad3ca10b816b8b5050cb73dd8a36 MD5sum: bc15f1500ccc9cfb07dd21bef042ee3e Description: reatime digital filtering library (debugging symbols) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package provides the debugging symbols of the library. Package: libvia-dev Source: via Version: 2.0.4-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 969 Depends: neurodebian-popularity-contest, libvia2 (= 2.0.4-2~nd70+1), x11proto-core-dev Conflicts: via-dev Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_2.0.4-2~nd70+1_amd64.deb Size: 212220 SHA256: 44b0d7f45533514a58d18da7477f8147320d23d1ca2e2da513ca0638c84372f0 SHA1: 279054de6615f664af82030520218d6bfd1d2d22 MD5sum: be7834dfbe616b25919944ea6968072e Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 2.0.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 903 Depends: neurodebian-popularity-contest Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_2.0.4-2~nd70+1_all.deb Size: 118466 SHA256: c508ad5f2de2d726a6ec321a5dda11ae53d8d1991ad9d407c85cfd9190a25184 SHA1: 20c0141728ccf9539a2a460c758d63970ddd85a2 MD5sum: 7094bbe0e4041f7c7ad8b07781132693 Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia2 Source: via Version: 2.0.4-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 568 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia2_2.0.4-2~nd70+1_amd64.deb Size: 172346 SHA256: 9006b22186b7f0e8cbc4e3914bd7bcb674379c3b8eaa01b69066eae7749a8415 SHA1: 69879a36111156fa87c5ff68e17d904d9487bd71 MD5sum: d2fc837ccadee5f7581304f29ad60a77 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: libvtk-java Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10911 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libvtk5.8, zlib1g (>= 1:1.1.4) Suggests: libvtk5-dev (= 5.8.0-7+b0~nd70+1), vtk-examples, vtk-doc, java-virtual-machine Homepage: http://www.vtk.org/ Priority: optional Section: java Filename: pool/main/v/vtk/libvtk-java_5.8.0-7+b0~nd70+1_amd64.deb Size: 4911660 SHA256: 68229a9bf87e3a1b9799f6ca833ed4bc50e6bff78f0b5459f2d5f37adaa965d4 SHA1: 63c1b0a65daaa2df22b45079c1a88bca460e4b78 MD5sum: d8c8e0aa2f5e0c6e630eca91a5dec181 Description: Visualization Toolkit - A high level 3D visualization library - java The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK Java language support. Package: libvtk5-dev Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12852 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd70+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev, libx11-dev, libxt-dev, x11proto-core-dev, libc6-dev, libxss-dev, libxft-dev, libexpat-dev, libjpeg-dev, libpng-dev, libtiff-dev, zlib1g-dev, tcl8.5-dev, tk8.5-dev, libavformat-dev, libavutil-dev, libavcodec-dev, libswscale-dev, libgl2ps-dev, libfreetype6-dev, libxml2-dev, libpq-dev, libnetcdf-dev, libmysqlclient-dev, mpi-default-dev, libqt4-dev Suggests: vtk-examples, vtk-doc Conflicts: libvtk-dev, libvtk32-dev, libvtk4-dev Replaces: libvtk-dev, libvtk32-dev, libvtk4-dev Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-dev_5.8.0-7+b0~nd70+1_amd64.deb Size: 2565214 SHA256: 13c1ba8002c22cd09b24bbff4334db11310c4fe26eb8ce46c7c85eb1ae90bdf8 SHA1: 83441de1304fc5cb4136fd128b1f601274a215eb MD5sum: 2581309d3c9ac507f18bed2d8075bd29 Description: VTK header files for building C++ code The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK to do 3D visualisation. Package: libvtk5-qt4-dev Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 549 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libvtk5.8-qt4 (= 5.8.0-7+b0~nd70+1), libvtk5-dev (= 5.8.0-7+b0~nd70+1) Conflicts: libvtk5-qt3-dev Breaks: libvtk5-qt4 (<< 5.4.2-8) Replaces: libvtk5-qt4 (<< 5.4.2-8) Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-qt4-dev_5.8.0-7+b0~nd70+1_amd64.deb Size: 109450 SHA256: f8a5d96cd72c4689d152150c988da0788fbf7a5f8f03642744d33b6a51b97cf5 SHA1: d4274d37e0fda0b58d5f54600cd1a248d2f8a7b6 MD5sum: 2918cf3fce1921511fbcac4acc8173f9 Description: Visualization Toolkit - A high level 3D visualization library - Qt devel The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK GUI support for Qt4. Package: libvtk5.8 Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47808 Depends: neurodebian-popularity-contest, libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libgl2ps0, libjpeg8 (>= 8c), libmysqlclient16 (>= 5.1.50-1), libnetcdfc++5, libnetcdfc6, libopenmpi1.3, libpng12-0 (>= 1.2.13-4), libpq5, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libtiff4 (>= 3.9.5-2), libx11-6, libxml2 (>= 2.7.4), libxt6, zlib1g (>= 1:1.2.3.3) Suggests: openmpi-bin | lam-runtime, libvtk5-dev, vtk-examples, vtk-doc Conflicts: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5, python-vtk (<< 4.4) Replaces: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8_5.8.0-7+b0~nd70+1_amd64.deb Size: 15257918 SHA256: ed0323761444227f6664e788787b82249dc87fe12f4b55d6785bdc8fb259e472 SHA1: 71433fdf990dc407df7b0f4acdbcf6eeb3263897 MD5sum: 67a046cfe213ed96361d228646b5cdd0 Description: Visualization Toolkit - A high level 3D visualization library - runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . VTK enables users to concentrate on their work by providing a large number of excellent and feature packed high level functions that do visualization. The library needs OpenGL to render the graphics and for Linux machines Mesa is necessary. The terms/copyright can be read in /usr/share/doc/vtk/README and README.html. VTK-Linux-HOWTO has information about using vtk, getting documentataion or help and instructions on building VTK. . This package provides the shared libraries needed to run C++ programs that use VTK. . To compile C++ code that uses VTK you have to install libvtk5-dev. Package: libvtk5.8-qt4 Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1360 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqt4-network (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.8 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8-qt4_5.8.0-7+b0~nd70+1_amd64.deb Size: 484074 SHA256: 422d8109b5f7b7b0af999c02a9568d0e03070c42e4202466d109bc76cee92c8a SHA1: 9d54d7d16173da33685bbb978b2bc229d343b656 MD5sum: 282bad631a4e495636f5ad980f6ca789 Description: Visualization Toolkit - A high level 3D visualization library - Qt runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK GUI support for Qt4. Package: libxdffileio-dev Source: xdffileio Version: 0.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.2-1~nd70+1_amd64.deb Size: 27708 SHA256: 4aa91c8c508f9365120b0ee004864e4886c9eebc92c92908103eeaba0ae7271c SHA1: 34fc3100b675c388925240a2be42479e5f8c251d MD5sum: e67a8bd4ff70fe9dce28cc7c39ad63e3 Description: Library to read/write EEG data file formats (development files) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package contains the files needed to compile and link programs which use xdffileio. Package: libxdffileio0 Source: xdffileio Version: 0.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 77 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libs Filename: pool/main/x/xdffileio/libxdffileio0_0.2-1~nd70+1_amd64.deb Size: 40860 SHA256: 3aab39615ceea5df3258238a1db6b89f0d33ca3cf6ca9aa282039381ff9812c0 SHA1: 8b30a695bd249dcdfc5523d5723e0d5386a7ba79 MD5sum: 0a6b5eb661c747c29730182b59e3b239 Description: Library to read/write EEG data file formats xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead of the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. Package: libxdffileio0-dbg Source: xdffileio Version: 0.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 195 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd70+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.2-1~nd70+1_amd64.deb Size: 62952 SHA256: cc491ad5c6fbed3856f22f96bd388c0c82753c7e9439f2d669cd5cd5e1174634 SHA1: 863ca2a9daf934eece3b521453f197f4fdff8eda MD5sum: f7672c575bf78a01ad812f691488fa85 Description: Library to read/write EEG data file formats (debugging symbols) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package provides the debugging symbols of the library. Package: matlab-support-dev Source: matlab-support Version: 0.0.17~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 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_0.0.17~nd70+1_all.deb Size: 6698 SHA256: 2b3805e6b6d76ed3a13b743fc1720bc6278ff12b5ad400df4cd779ae5e7a7d07 SHA1: 79fba2d558b66bfe56fc35d37a3a8b20e6fad3fb MD5sum: f765d2590d91ea382312b1ee5224994c Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mriconvert Version: 2.0.203-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2288 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.203-1~nd70+1_amd64.deb Size: 808774 SHA256: 51f81906723e358dc5dda0a42871b8c92a2640a18aef7aae2a5b4d74b49a10ff SHA1: 7fe16da1094ee9d74a85d65e97cbc6f2d5d25d2e MD5sum: 88642f5ce4f3944ca92faea2131e350c 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: 0.20110413.1~dfsg.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15636 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20110413.1~dfsg.1-1~nd70+1_amd64.deb Size: 4902290 SHA256: 9dd3d8cf496f17d3db3c2dc7837fb4768bde2b51352f8bc0597860785cb329c1 SHA1: 8c33316e5e889a2a60ec38ed4c65d935a1698a84 MD5sum: 42a6bf8374e311361ca7d7b0c1e8ba30 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: 0.20110413.1~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1808 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20110413.1~dfsg.1-1~nd70+1_all.deb Size: 1666500 SHA256: 1863a5c0ee314f94c26edaf3c1175e2d973087cf40dd3d38a8703ed633bf1841 SHA1: a7321d87c46a63ad18cf102cdbd9a6422671c8dc MD5sum: e6df8193e4808b3d1858ab291028ecb8 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: 0.20110413.1~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1180 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20110413.1~dfsg.1-1~nd70+1_all.deb Size: 738128 SHA256: 763790b62ad56fcb001ca949941aaac2f9128e0280bcb88bbaed4b11d2cf3a7b SHA1: 0ff30e7a856f3274d6aea10d13649ed954ae04a1 MD5sum: ae382305344a567ac3bd6cb406b81bd3 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.10-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8119 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.30.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.27.1), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.6), libx11-6, libxmu6, libxt6 Suggests: mrtrix-doc Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.10-1~nd70+1_amd64.deb Size: 2610938 SHA256: 4c9909e37837eb715ab16f3799ff8404b1777fd736aa4fb7164493c9f587a39a SHA1: c321d56c1e3766668ac1936e9aa34ff0d92747fb MD5sum: 4f9bdb1f95097e2237b12ef9ac18c38c 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: 0.2.10-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3491 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.10-1~nd70+1_all.deb Size: 3322016 SHA256: c2268744669b0b2143112d1a1461fb4a5b99e9c102a4852e65f0d83a711ae63a SHA1: 3cdd127233e21960d2567367934029df0a69d2ec MD5sum: 8ff9467f45ceac4eb7425623f6545507 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: neurodebian-desktop Source: neurodebian Version: 0.27~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 141 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.27~nd70+1_all.deb Size: 113958 SHA256: 817a4acf4fd8ef9842aadfec7ad8caa0946739353f2b976cb1c49f26e6102617 SHA1: 89d00d068e6dda383c4068848c376a652c938eca MD5sum: 78aac7a70201750e0cdac92db9d61860 Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.27~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5450 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.27~nd70+1_all.deb Size: 5087718 SHA256: fb516ad7a1fddf0e91d921bd2e349265c8c095253f4c6e75db7659aae7b11974 SHA1: c8be5cae602f1d873473e6103955fd721cb12647 MD5sum: e12939bfeef5f33d0b41e4f91624978f Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.27~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 105 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.27~nd70+1_all.deb Size: 13464 SHA256: 969038d6bb9778b466b13db405ee2fc71ccdeacd328e6146618fbd67fbf362ce SHA1: 81cf94e4f4fd81b5a30bf0b5a0b9b55b36aeddfe MD5sum: b836ab4a16a23a54d454b72aaca5e3d9 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: 0.27~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.27~nd70+1_all.deb Size: 6400 SHA256: c3fdb95c9df83b31c0b57fb0356a99a4cdcf8a67686af9536e867be9fde18a1f SHA1: 0e94fe26bc1894c9dc2cfb9296a60e7306f2727a MD5sum: 434a2a8e834bda12de3d1c90ea6769cb 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: 0.27~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.27~nd70+1_all.deb Size: 5568 SHA256: d25bf1f33484d998457d7531fa214d800a5b6e5a3e606597aab2061e151e0b67 SHA1: 395034b9538f7909a9750047d4c7f4eb3593a0c7 MD5sum: 9f625146ef71d8372411c2d83c370492 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: nuitka Version: 0.3.20.1+ds-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1347 Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1) | g++-4.5, scons (>= 2.0.0), python-dev (>= 2.6.6-2), python (>= 2.6.6-7~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6) Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.3.20.1+ds-1~nd70+1_all.deb Size: 305812 SHA256: d0317f7929681101f9db9bf2ac18f6db904da2376fd60686b13268cbc5d6cf62 SHA1: 289abde8922759d7fb4aad5b1983f42a178aaad1 MD5sum: 3840d80c9da0dff67d1a55b086762c68 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 to pure Python objects at all. Package: numdiff Version: 5.6.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 857 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.6.0-1~nd70+1_amd64.deb Size: 597436 SHA256: 9a87c4bc5f50898003ea1e5b7d878a07272dd746fb2a09c23f1fe7932e35c076 SHA1: a1273fa841c9e27b2c8b0f308efa768c553375e9 MD5sum: f984f122c6cb98339f6b6f76433650b4 Description: Compare similar files with numeric fields. Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Depends: neurodebian-popularity-contest, libbiosig0, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.5-5~), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 18248 SHA256: 0c9dfcca761c698f9d9f70d62120b7b05bed4f517c3b11ad5f108765a17d02a0 SHA1: 046b57b6054dfc1772e2a17cfc357e0ad3c26d3b MD5sum: 9a9c8aba4ebc052b5f7ed5888b4c1b1b Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 275 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.2-1~nd70+1_amd64.deb Size: 118156 SHA256: 9ae193b7d3e2e8c4da393aae43e2fc7d883587c9e1e6a844aa881871f258dbae SHA1: 3f57072df87d7cc45c005f3db7e67fc7965a3929 MD5sum: 24d38b731ae917c3bbfd2acfb235255c Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.9+svn2514.dfsg1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2471 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.1 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglew1.7 (>= 1.7.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libopenal1, libpciaccess0 (>= 0.8.0+git20071002), libusb-1.0-0 (>= 2:1.0.8), libx11-6 (>= 2:1.2.99.901), libxext6, libxi6 (>= 2:1.2.99.4), libxml2 (>= 2.6.27), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2514.dfsg1-1~nd70+1), psychtoolbox-3-lib (= 3.0.9+svn2514.dfsg1-1~nd70+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.9+svn2514.dfsg1-1~nd70+1_amd64.deb Size: 848152 SHA256: 5e4cfeef02a7c0601e1faa1aa8fe6abdd323960de408607b601496e462255b2c SHA1: 726c8424bcb3bee83c6bc88ed385952af95fe262 MD5sum: 65579a44f6ed0ed4e97a8c993a87b732 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. . This package contains bindings for Octave. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 600 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-3~nd70+1_amd64.deb Size: 183066 SHA256: 2514882171f7db2dc5ecbee1bb759a797f3970cfe109508ab73f8e17a91e96d5 SHA1: 5efa2c3b2062f260bf1c9cb5b3db7b553d131139 MD5sum: 5b534063d3e13c1f7e4cf184015b2a74 Description: tools for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides command line tools. Package: opensesame Version: 0.25-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4142 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2 Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.25-1~nd70+1_all.deb Size: 2844714 SHA256: 4b4e6f880b11d1de5c95c66f781d108ab2923bf64f0beb0a5dbea747a9b029a1 SHA1: 2dc93ebab98e31c929aa1a3b89f86f3439157332 MD5sum: d040fbf6c040eeeb83c4e492c6e39e1c Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Python-Version: 2.6, 2.7 Package: openwalnut-modules Source: openwalnut Version: 1.2.5-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15368 Depends: neurodebian-popularity-contest, libbiosig0, libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-signals1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.3.2), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph80, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.2.5-1~nd70+1_amd64.deb Size: 4683170 SHA256: b3c779a038ac89131ba58edbd69f28ca2a9b40ab773c8511c9f34cee7b08a4c2 SHA1: b4c9165571153dffd3947ff4bbd9b072c6f9ca5f MD5sum: 3a55210bfd0c7770ee844282bb5fe935 Description: Multi-modal medical and brain data visualization tool. 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: 1.2.5-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1768 Depends: neurodebian-popularity-contest, libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-program-options1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.3.2), libgcc1 (>= 1:4.1.1), libopenscenegraph80, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.0), libqtwebkit4, libstdc++6 (>= 4.6) Recommends: openwalnut-modules (= 1.2.5-1~nd70+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.2.5-1~nd70+1_amd64.deb Size: 586330 SHA256: 767760b4318acbeab03e1551cdeab2d15d21ed0825f5e746ca9635bca64ded79 SHA1: a22a54756d5274420c07f00fadfa3469c2c71a19 MD5sum: d62cf5b89bd9122d9f288d59fb5953b4 Description: Multi-modal medical and brain data visualization tool. 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: packaging-tutorial Version: 0.2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 836 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.2~nd+1_all.deb Size: 680180 SHA256: 4f1c39bc3f108a98284df69fc1734c3eb97957be6e441928596ccbf1ba0d1292 SHA1: 1117c3ff4a15d620a0d8fc62edcc1bfcf45e6329 MD5sum: a3c8023d51d265c6a801496c98620528 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: psychopy Version: 1.73.05.dfsg-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4454 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.73.05.dfsg-1~nd70+1_all.deb Size: 2686034 SHA256: c46a7e379a5e6feebcb0debbd37b6762b2ecf4fd1a9209e02d492b2a6ee5f65b SHA1: 8d7cc73cdba7987d5313348b9c85ad05d845360c MD5sum: 9debbd41a929e4aa56bed8d611785dba 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: 2.6, 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2514.dfsg1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47144 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2514.dfsg1-1~nd70+1_all.deb Size: 19474762 SHA256: ab25c03f184a89587168a9b2eb372ac17caeb77a0520d5e1de71903e5fd7469e SHA1: cf4def9bb0f958393e36690ecd2d7091faa9aeac MD5sum: f2b952eb7c9177979af2839c14d6ed7a 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: 3.0.9+svn2514.dfsg1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2499 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2514.dfsg1-1~nd70+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2514.dfsg1-1~nd70+1_amd64.deb Size: 831948 SHA256: 7c09b7d8d18acd0a9fba2cb7807cbb939b45f341b0ad5b6b808d2fe4b90ed386 SHA1: 4c0fa6c0d6e3e6478a5aa950a15c99eabca34aad MD5sum: eb58a1d1346017d93e0a14bcbf47f3f8 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: 3.0.9+svn2514.dfsg1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good Suggests: gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.9+svn2514.dfsg1-1~nd70+1_amd64.deb Size: 121432 SHA256: 3d7594318b19fdf6f6163b03a4b01429b7077013202f8955512cb586ad2d530f SHA1: df202229e71c93f35ef9c2177c61e82cd4358214 MD5sum: a8278bed8f7a91ae594aabe3cd2be0c5 Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.2.5), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.96.3+svn2677-1~nd70+1_amd64.deb Size: 53080 SHA256: 11202d5df00651f180977abacfa04f9c20baa38ccda71dc25fc368a4e1036d90 SHA1: 162f6e7962ac5eb04ba5183da7eba2510f609f36 MD5sum: 4e2c4a46b66dec8b574678d9bbb49e63 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: 1.3.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1597 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.1-1~nd70+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.1-1~nd70+1_all.deb Size: 393372 SHA256: 6ee0239820d611ec2d8bf99a1bc8b8f3b614979813440313064cf2e9e6e12fe2 SHA1: 47157135f89d352b7e632eff07f877fe1d68072d MD5sum: c3efc437ee9aa93b6d3789f80b9a72f5 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: 1.3.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5245 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_1.3.1-1~nd70+1_all.deb Size: 1957876 SHA256: 024ab9ef376c133226df5371d45e49ec50428b522bd5e32c0551545449967330 SHA1: bf3a10bc64d553f4d623583508014ee56dd4549f MD5sum: 340b01388780c5b2de08e1236b1bf192 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: 1.3.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.1-1~nd70+1_amd64.deb Size: 106346 SHA256: aebe99af8a4493c317ab358015f93262b4c45d407f635331b7835d797fe7d8df SHA1: b15f11097ecbb22fcfa1575c1d832f6fc19e8e44 MD5sum: d0013170bcdbad07552ae7fc19e62b3c Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-cfflib Source: cfflib Version: 2.0.5-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 768 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-numpy, python-networkx (>= 1.4), python-nibabel (>= 1.1.0) Recommends: python-nose, python-sphinx, python-tables, python-h5py Provides: python2.6-cfflib, python2.7-cfflib Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd70+1_all.deb Size: 217682 SHA256: 315d0c9976626dc452d7a4f03c9ff782c4caa12e182713db2c33d71233777b37 SHA1: 2f09d150c91742140a16fba4f03eceb4ad364e04 MD5sum: 34ba30e9fe7f1e59a608e67b241ca26c Description: Multi-modal connectome and metadata management and integration The Connectome File Format Library (cfflib) is a Python module for multi-modal neuroimaging connectome data and metadata management and integration. . It enables single subject and multi-subject data integration for a variety of modalities, such as networks, surfaces, volumes, fiber tracks, timeseries, scripts, arbitrary data objects such as homogeneous arrays or CSV/JSON files. It relies on existing Python modules and the standard library for basic data I/O, and adds a layer of metadata annotation as tags or with structured properties to individual data objects. Package: python-dicom Source: pydicom Version: 0.9.6-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1690 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.6-1~nd70+1_all.deb Size: 390198 SHA256: c4b2a28ce7560813c2df7627aa5d8e0a2ce4f3fd7371759216fd21cabe51f183 SHA1: 62daf34a029bd194537e534d1e1c3cdc7f88eddf MD5sum: 368c757bcb228236df8557ee9bf6a165 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: 0.5.0-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2072 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-2~nd70+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.6-dipy, python2.7-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-2~nd70+1_all.deb Size: 1457822 SHA256: 4443cbf5779f02ffe5530677cf32eff5cf87a7461a93d14109430914c3165eb9 SHA1: c7f18d5fd82226e9bbb55758cce4a32ece5b17fc MD5sum: ba37aeaec90ddd3b4c3ea1b168b195cb 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: 2.6, 2.7 Package: python-dipy-doc Source: dipy Version: 0.5.0-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3224 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.5.0-2~nd70+1_all.deb Size: 1943460 SHA256: 77110288eda92de717c7cb8a59a7b78b0c2f34ba818cc9453fd6aa8ca2a931ba SHA1: 08a3c7a35794127674800f21193aaa2b3943a732 MD5sum: 2249175ca13861e7842cdc7b9d0d64ca 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: 0.5.0-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1120 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.2.5) Provides: python2.6-dipy-lib, python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-2~nd70+1_amd64.deb Size: 423068 SHA256: adac35c7fd9da9ceb9d8eb5f2246bf7370b9e7bbcf2c7c8ac9db28b374899b13 SHA1: d9b640098bccca8ed836f5747ae19f3793ab2679 MD5sum: b3cb748043265117bd709e204b6834be 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: 2.6, 2.7 Package: python-freenect Source: libfreenect Version: 1:0.1.2+dfsg-5~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0), libc6 (>= 2.4), libfreenect0.1 (= 1:0.1.2+dfsg-5~nd70+1) Suggests: python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.1.2+dfsg-5~nd70+1_amd64.deb Size: 43078 SHA256: 5327105efac7c52fe9fed0db5e3d534e6f76d42dfe45f25756a59601ad6d0a8a SHA1: f15ac5cbb434ffe5ed153a9a6859d412bcec293a MD5sum: 0d94b3cdfd19c6b6f97501b1fdfe746d 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-isis Source: isis Version: 0.4.7-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11805 Depends: neurodebian-popularity-contest, libboost-date-time1.48.0 (>= 1.48.0-1), libboost-filesystem1.48.0 (>= 1.48.0-1), libboost-python1.48.0 (>= 1.48.0-1), libboost-regex1.48.0 (>= 1.48.0-1), libboost-system1.48.0 (>= 1.48.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libisis-core0, liboil0.3 (>= 0.3.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.6) Conflicts: isis-python Replaces: isis-python Homepage: https://github.com/isis-group Priority: extra Section: python Filename: pool/main/i/isis/python-isis_0.4.7-1~nd70+1_amd64.deb Size: 2456274 SHA256: 68944d6d3f77b7bd01128a055e9dee329e7aa3d449caebfb458bc2043811879e SHA1: 2b64501a36ba03af8a5946f3a93746233f45a216 MD5sum: eaa08181943340e25bedbc39e53f68be Description: Python bindings for ISIS data I/O framework (development headers) This framework aids access of and conversion between various established neuro-imaging data formats, like Nifti, Analyze, DICOM and VISTA. ISIS is extensible with plugins to add support for additional data formats. Package: python-joblib Source: joblib Version: 0.6.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.6.1-1~nd70+1_all.deb Size: 51010 SHA256: 5b3279eb3d3fa1af3d0c91318f08aba3693bd9cbfc3410eb622030ef347e33c7 SHA1: e7bb77ab62e6f3304521957f4021b14042062851 MD5sum: d62d5b34eb4780e819480cf232b65b8b 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. Package: python-lazyarray Source: lazyarray Version: 0.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Homepage: http://bitbucket.org/apdavison/lazyarray/ Priority: optional Section: python Filename: pool/main/l/lazyarray/python-lazyarray_0.1.0-1~nd70+1_all.deb Size: 7334 SHA256: 72dadd7fab4a8d37309793af8b50d73a7ea93f6c223509fe58ad502936fa852d SHA1: 3a45ca7b469e524691c3ed6ec708b24bd59391a8 MD5sum: 80d3117e7a8b1fa74d6551c6f2f306ed Description: Python module providing a NumPy-compatible lazily-evaluated array The 'larray' class is a NumPy-compatible numerical array where operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Consequently, use of an 'larray' can potentially save considerable computation time and memory in cases where arrays are used conditionally, or only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array). Package: python-mdp Source: mdp Version: 3.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1520 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-joblib, python-scikits-learn, python-pp Suggests: python-py Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.2-1~nd70+1_all.deb Size: 479010 SHA256: 4088f590060b6f9073dba7b13a1ba691336590c967cc4e2806fc42ae9db9819d SHA1: 201d60e0136d0c258c16913988a263504cb0c48e MD5sum: 60013b59e2a882d2b1d642b861d69fbb 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. Package: python-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2204 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libopenmpi1.3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~pre1~nd70+1_amd64.deb Size: 742764 SHA256: 765919b84b4945c2dcd28ff63c1ab68394ef8ef26d86d0c5ca8043b5093e1181 SHA1: 26e873e984d457cd04a345608b587ec6e36334ec MD5sum: 85ed12667feb4a068388d02c84048b8a 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: 1.2.2-1~pre1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5828 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd70+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.2.2-1~pre1~nd70+1_amd64.deb Size: 1398498 SHA256: 026fdb9c58a9a822171674db0a8d0d7bf5965f86977e3d3e5eb701d6ceb11b92 SHA1: b0085ce4ae1d462674d8706fb67f712184b71b63 MD5sum: 2eac51e82de7b38d54c474685258bb50 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: 1.2.2-1~pre1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 272 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.2.2-1~pre1~nd70+1_all.deb Size: 54792 SHA256: e65ef3140fcb539d40e7745b643c32bdee17f2fb9ae6ba576cc2ecebd22801af SHA1: b12a32f6f58b8b8b80c75be6bd2c599670ca2685 MD5sum: b4140511b67177c75ac80f54315eeba0 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-mvpa Source: pymvpa Version: 0.4.7-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4076 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-2~nd70+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-2~nd70+1_all.deb Size: 2196856 SHA256: 9d39b6dcb10b26ae2c77f8cd8abb71fb0fbe307729ee7fe31ca453a8e9cd3f8b SHA1: c109d52cef7217ecba871c95505c7cfafda98f06 MD5sum: 6e13e63b05a945094d185942d0ee16ab Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41220 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.7-2~nd70+1_all.deb Size: 8776798 SHA256: b8da7f6d97e1e74e3fae68137c7f611e6e7ec9ce6e04956b7c537f23821eb4e7 SHA1: bb1a53dbc712bb338fc4ad77d41ece23df82b081 MD5sum: c553a2569335088f4a56df792847b39e Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.7-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.7-2~nd70+1_amd64.deb Size: 72642 SHA256: d52c99e0e9e024a0939e2b8aad48096bd445c01ba13f8a95ed78ea89255fb1bf SHA1: 8f097921a815517eec4b3e4825fe5df41224878d MD5sum: 0f5a64de0c2b8f6f40465ff36002adae Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa2 Source: pymvpa2 Version: 2.0.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4023 Depends: neurodebian-popularity-contest, python (>= 2.4), python-numpy, python-support (>= 0.90.0), python-mvpa2-lib (>= 2.0.1-1~nd70+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py, python-psutil Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa2-doc, python-sklearn Provides: python2.6-mvpa2, python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.0.1-1~nd70+1_all.deb Size: 2334028 SHA256: b24bcca5b5e8c275f0d907879d4b8baa8658579f44e0b5f395b69fd137a8b607 SHA1: 79b5c0575d621c0e832153af2713439d017c88ec MD5sum: 22bde55a9cdb182ec81f2a31629b5496 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: 2.6, 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.0.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15380 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.0.1-1~nd70+1_all.deb Size: 4549692 SHA256: e2c2e673e9513682cd2f497ad91c8bf859f3b4649b6c89d1c6e1ebc33b79e183 SHA1: 510362d2e9c1db38aaf866a1d68f756d8135a61b MD5sum: bf7f93f128d24ce4ca7298796fbd9c7e 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.) as well as example scripts. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.0.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 195 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.6-mvpa2-lib, python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.0.1-1~nd70+1_amd64.deb Size: 75066 SHA256: 520e78892218b221fbc6e055397e1c6f0c78ddf6d92a6e1e548cb296a3b9f5c3 SHA1: b8ea237f3352c6d8201748473ec8f1eb59f420a1 MD5sum: 153030dcf36d73656a6c5ffd23955b14 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: 2.6, 2.7 Package: python-networkx Version: 1.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: http://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.4-2~nd70+1_all.deb Size: 647240 SHA256: d330d947a368e24c1c211bb38680d39b541734610380b2eae4295581dc4cd792 SHA1: b2038a2f713e9b53f792369bacc2b37b26f406e1 MD5sum: 80ada5a82a23d92f2ce8d69d952d4f7f Description: tool to create, manipulate and study complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-networkx-doc Source: python-networkx Version: 1.4-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15840 Depends: neurodebian-popularity-contest Homepage: http://networkx.lanl.gov/ Priority: optional Section: doc Filename: pool/main/p/python-networkx/python-networkx-doc_1.4-2~nd70+1_all.deb Size: 6234176 SHA256: 8a284c712351861f561505f6f7a85a6d6b86732f9020951066fca67be022c7a9 SHA1: d7da2a947abc8026e87191c4ff5893cdbd013adb MD5sum: d0470a135f7b7ae6fbb4252e2b688f86 Description: tool to create, manipulate and study complex networks - documentation NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains documentation for NetworkX. Package: python-nibabel Source: nibabel Version: 1.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3616 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel, python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.1.0-1~nd70+1_all.deb Size: 1675194 SHA256: b8fa1364a16e1ca98e270d91ea8c920202028fd264240e83f6b51a9a74029c9c SHA1: 6915395650e821a709e72e310c31ac33e829833e MD5sum: 6fac62cf4b7a2be372cfdad236fd070a 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 tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.6, 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.1.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2756 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.1.0-1~nd70+1_all.deb Size: 411348 SHA256: 0d24e7b2dd4012e351adc9777ffd3f7ecfdaf122c001961501b84dd043394acc SHA1: bc65298dee8bd75f1152deb5fd0b848a21042e77 MD5sum: c6303851a69d864df76c8eef05448339 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nifti Source: pynifti Version: 0.20100607.1-4~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1480 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libnifti2, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python2.7, python-numpy, libjs-jquery Provides: python2.6-nifti, python2.7-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-4~nd70+1_amd64.deb Size: 375728 SHA256: 7a4ac791f54109e24feabe3d4afc0be1d6dc52e7d1c78541d41bb515cca6a6f0 SHA1: 488170931671b03655c6e5db5a53e9fc9409ebd3 MD5sum: bc525d5d55673a048e1bcfb70e30c514 Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.6, 2.7 Package: python-nipy Source: nipy Version: 0.1.999-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2713 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), python-scipy, python-nibabel, python-nipy-lib (>= 0.1.999-2~nd70+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.6-nipy, python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.999-2~nd70+1_all.deb Size: 743478 SHA256: a43a9b77dbe8951fc9097b9dfd76721da816acad16e67a3293316f54063d7cd6 SHA1: 5bea3bde8aa0bdb3946fc8217cb8c9879ef4e877 MD5sum: 44264c3b96a77afbd4774e0116ceeadd Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.6, 2.7 Package: python-nipy-doc Source: nipy Version: 0.1.999-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9361 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.1.999-2~nd70+1_all.deb Size: 3546004 SHA256: 585b936565c1f139e08906b3ca3584b6810918d0b3af5e7de819db8ba6895307 SHA1: 7d07b63f71eb8db967c6cb0b0fdb89017857c329 MD5sum: e3a188254f6992a81ef0f31316b91e7c 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: 0.1.999-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2515 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Provides: python2.6-nipy-lib, python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.1.999-2~nd70+1_amd64.deb Size: 950366 SHA256: 9a1ff5d034dedd6a099081dd646e827541d6e5c4b57736b66406d52d52672094 SHA1: 829dfc2f6400a190abb99f62ab55ecaa56dbe1d6 MD5sum: 955531055ef8fd4252acb65503242f96 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.6, 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.1.999-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3703 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), python-nipy-lib (= 0.1.999-2~nd70+1) Provides: python2.6-nipy-lib-dbg, python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.1.999-2~nd70+1_amd64.deb Size: 1172122 SHA256: 770e1f208a0ee32a73cf3fc952ad8aab6c0b3f1dd2f24ae5a5657c7cdb3c8336 SHA1: 73aa501a1a642a83de8c45daaa01a16bd670a980 MD5sum: 428192ec48215a01ca9898089647b2c0 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.6, 2.7 Package: python-nipype Source: nipype Version: 0.5.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2243 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), 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 Provides: python2.6-nipype, python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.5.2-1~nd70+1_all.deb Size: 500796 SHA256: 9f58ef26d3dd35faf299b07b5c20a0578cc9c84a89ba660f2cf1980534e79fc7 SHA1: cb6f88957da825cb86298e2c275a81d4e5cd50e4 MD5sum: 63b98a531e570d559c52c9fdaaf2a527 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: 0.5.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12077 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.5.2-1~nd70+1_all.deb Size: 5717502 SHA256: 5c50797c026f9c438bdb463b123aa5f84b2502c16e702f683348b02b47e9b408 SHA1: 83c10e7a6a3b956e5f7685cd61e4b06175aa1f46 MD5sum: 4a8700fdea29ce4365db9d7d9aeec258 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: 0.3.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9404 Depends: neurodebian-popularity-contest, 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_0.3.1-1~nd70+1_all.deb Size: 3902352 SHA256: 5a5ac43b3dc6c1e8c8c1d20c6f8732b446df702cacb3f6a1a04a4263b3c8bee1 SHA1: dbb741a48c7acf9a8a2fb9743517935f43a62d0d MD5sum: 3e34e9c6ee2b0613bc1dbbf70b968b3a 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: 0.3.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7008 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.3.1-1~nd70+1_all.deb Size: 5267266 SHA256: 5cc4f411cf911742be2a45ed68cda4086c45d83decd3c601e9af1b71b2d247be SHA1: ad0a073b7b0991dfb867e802372c4b237e968ab5 MD5sum: 6731916bc104f32338c404f4c68e4654 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-numexpr Source: numexpr Version: 1.4.2-1.2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 801 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), libc6 (>= 2.3.2) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_1.4.2-1.2~nd70+1_amd64.deb Size: 286488 SHA256: f4bb8201a98d7a2bc3470eaf0d59f85c9e47394032b4ec2c4d106e06c272e2e8 SHA1: e7029211be194cb8a085d49d2cecb84933770ae9 MD5sum: 5c0afde976921ae53e9022ec72d6f828 Description: 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. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-3~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 572 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-3~nd70+1_amd64.deb Size: 168038 SHA256: ff7ca94bcfb60c47a4f0d6c95e422a5e4ebe5ac3efbd1098bd3c1a82eb354526 SHA1: 5c9be22190abf3184847f9ab48bfefc46bfd953d MD5sum: b1282a798c89447db0ac2d8bb5a3183d Description: Python bindings for openmeeg library OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides Python bindings for OpenMEEG library. Python-Version: 2.6 Package: python-openopt Source: openopt Version: 0.34+svn1146-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1448 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.6-openopt, python2.7-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.34+svn1146-1~nd70+1_all.deb Size: 206376 SHA256: 61fbed72b84a94fafcacdd5821f380d00b49fd74ab4943b2449d1c16376d3121 SHA1: 646ac7c8ac82120a9e1a007f0d9975fd7104433d MD5sum: c16f8183fe292d6b51b074a4485f5a9f Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: 2.6, 2.7 Package: python-openpyxl Source: openpyxl Version: 1.5.6-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 333 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.5.6-1~nd70+1_all.deb Size: 67036 SHA256: 446ba8160a7006ce355f4f22160830dd60c74c7aae530ea3133802ba132ab750 SHA1: 6e4645a3b836a59b4389d20663fec8ab3df980ba MD5sum: ade71d3e1192c6182bb399d62311db20 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: 0.7.1+git1-ga2e86c2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1787 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-dateutil, python-pandas-lib (>= 0.7.1+git1-ga2e86c2-1~nd70+1) Recommends: python-scipy, python-matplotlib, python-tables, python-tz, python-xlrd, python-scikits.statsmodels Suggests: python-pandas-doc Provides: python2.6-pandas, python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.7.1+git1-ga2e86c2-1~nd70+1_all.deb Size: 399332 SHA256: 6e7fda7a50d5ad6e828c8e7874cd662494c51f7058118960618f751a6ff2a7d7 SHA1: 399f26e248f3694ceedb7ec2a9a270d794c19ead MD5sum: 5f80e595e34be59b3f676191cb99a584 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 Package: python-pandas-lib Source: pandas Version: 0.7.1+git1-ga2e86c2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3077 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.6-pandas-lib, python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.7.1+git1-ga2e86c2-1~nd70+1_amd64.deb Size: 1122264 SHA256: af629f2ad375129425b2b3ab4b876ccfe5094688076acd317f96d4647ca81919 SHA1: 2f5d38e72d4468e04795141922e57b71cb7abe7b MD5sum: 530aabd90d59fd52d91080691b69d18c Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. Python-Version: 2.6, 2.7 Package: python-pprocess Source: pprocess Version: 0.5-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 884 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~nd70+1_all.deb Size: 107932 SHA256: 9e2808d481734f4f0937fb9a468d30716a8eb811518d684abf9844ee21ee8a4a SHA1: d4ab6e31eadff85c7e7f8b7220cb97c7d66d303d MD5sum: 33924f1ceaba1a3a3ba22f172ff8a0d1 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: 2.6, 2.7 Package: python-pynn Source: pynn Version: 0.7.2-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 740 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), 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_0.7.2-1~nd70+1_all.deb Size: 183462 SHA256: b2104a7a2a53a3133b55a847c245049d70050730a0af026f597970e9c1e5e9c4 SHA1: e73570a777ccb7586a8797af2fd53ebc8da6161f MD5sum: 1ba1b974ce71976f8c4011edab661d5e 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: psignifit Version: 3.0~beta.20111109.1-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2414 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit/python-pypsignifit_3.0~beta.20111109.1-1~nd70+1_amd64.deb Size: 675198 SHA256: c396896b0908f04f351eb754820780474e89c90cdf0bebba0565f4bd01bfb4d3 SHA1: 917c8dc46a8108f350ae530a102f08c256657f13 MD5sum: 9cb95e8ab518eb62d0740ab4169d3088 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pyxid Source: pyxid Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Homepage: https://github.com/cedrus-opensource/pyxid Priority: optional Section: python Filename: pool/main/p/pyxid/python-pyxid_1.0-1~nd+1_all.deb Size: 11020 SHA256: 1031c0d69dd73cb38f3e0b826193211706a94bfd04da4287288418b257e54249 SHA1: 0f0d0524354e5d07eb89efcb11779d9acd9d57e2 MD5sum: 1f2a9bc07952b1f5c6b65fc5c092f75c Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-pyxnat Source: pyxnat Version: 0.9.0~dev0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 660 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Provides: python2.6-pyxnat, python2.7-pyxnat Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.0~dev0-1~nd70+1_all.deb Size: 107002 SHA256: 5a552ade1f20f81cf863edf8a565e8e9e4a3cf6b64e55239cbdd10adf6f844f9 SHA1: 187de938796998e7f58ef38604de4bba55b1cf5e MD5sum: 33dab688b9a8dea348181a34b65c08e7 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-quantities Version: 0.10.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy (>= 1.4) Homepage: http://packages.python.org/quantities/ Priority: extra Section: python Filename: pool/main/p/python-quantities/python-quantities_0.10.1-1~nd70+1_all.deb Size: 62650 SHA256: 7105f0be0bad6a6896943c81ffc4f7ebd4e7ce36829bf3747f8fbb603246e059 SHA1: c36035905534efefa681ab02a9b30a297c46c3fc MD5sum: 370baf01ebbe89b0e73e46b3b3dee9e2 Description: Library for computation of physical quantities with units, based on numpy Quantities is designed to handle arithmetic and conversions of physical quantities, which have a magnitude, dimensionality specified by various units, and possibly an uncertainty. Quantities builds on the popular numpy library and is designed to work with numpy ufuncs, many of which are already supported. Package: python-scikits-learn Source: scikit-learn Version: 0.10.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest, python-sklearn, python (>= 2.6), python-support (>= 0.90.0) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.10.0-1~nd70+1_all.deb Size: 19824 SHA256: c3466228c1907bca34df516ca183bef5d51db5b41bd4f621cddecc8a34d3f1e2 SHA1: ec4bb50bd5e80d4cebe1ce7e26522f0a29699e10 MD5sum: 8a2acc02e768af8752031989ca4541f1 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scikits.statsmodels Source: statsmodels Version: 0.3.1-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12296 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Conflicts: python-scikits-statsmodels Replaces: python-scikits-statsmodels Provides: python2.6-scikits.statsmodels, python2.7-scikits.statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.3.1-3~nd70+1_all.deb Size: 3106420 SHA256: 7480e3e5362de3a8523dbbd08fda86a33cc80428412ef1446840443487384f1b SHA1: 89e9664d49788bf052d1478b3f9c9724b81af09a MD5sum: 827083dbe08065741e0e774f7558c3de Description: classes and functions for the estimation of statistical models scikits.statsmodels is a pure Python package that provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Python-Version: 2.6, 2.7 Package: python-scikits.statsmodels-doc Source: statsmodels Version: 0.3.1-3~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11855 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits.statsmodels Conflicts: python-scikits-statsmodels-doc Replaces: python-scikits-statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-scikits.statsmodels-doc_0.3.1-3~nd70+1_all.deb Size: 1727698 SHA256: 893648f2cac9628448d626e0c8f7f853aad2832b1eb515e4ac680af5cce8dbf4 SHA1: 8681233483945bb985752f0c470ac5bbc3e5c835 MD5sum: 37a764b71fba9f9ceb8e8984ee9126f4 Description: documentation and examples for python-scikits.statsmodels This package contains HTML documentation and example scripts for python-scikits.statsmodels. Package: python-simplegeneric Source: simplegeneric Version: 0.7-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Provides: python2.6-simplegeneric, python2.7-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd70+1_all.deb Size: 9810 SHA256: c0bf53d256b2a9520f7c40efd3af9d01c92802949256bdc3ddcbe6f8c809ba45 SHA1: b9a5abab569c8269207372b91c7e89a7230efc84 MD5sum: 46e1c70528d4fd5c5636ec720f54787f Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-sklearn Source: scikit-learn Version: 0.10.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2235 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.10.0-1~nd70+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.6-sklearn, python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.10.0-1~nd70+1_all.deb Size: 832884 SHA256: 84b1c4447a4733341c27c46aeff02cae09b1766650872a6faadaf49125075298 SHA1: dafcbe7162c4486304d3b28133f253a2a7838088 MD5sum: 7d8ef4acccb019f23c848e63fc2f3331 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) Python-Version: 2.6, 2.7 Package: python-sklearn-doc Source: scikit-learn Version: 0.10.0-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20751 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.10.0-1~nd70+1_all.deb Size: 13379028 SHA256: 2ff19133ea098ee8ab7846dc9c101cc455eec35874c100986738921c3014f35d SHA1: 3181bb8bbbf4baec56a63c6c283c9f68b51e7eef MD5sum: ead209ab71dfd6b4f409f5cf7b853f84 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: 0.10.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3242 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.6-sklearn-lib, python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.10.0-1~nd70+1_amd64.deb Size: 1240392 SHA256: 09bc0403abd94d48dd06dd3c807ba67f19b665ab8f32424e97b13a8c48f974ae SHA1: a1e85f59c5b42043da435517acc30727371a2baa MD5sum: dd71afe395de836e46107e243c53b369 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. Python-Version: 2.6, 2.7 Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4188 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-docutils (>= 0.5), python-pygments (>= 0.8), python-jinja2 (>= 2.2), libjs-jquery Recommends: python (>= 2.6) | python-simplejson, python-imaging Suggests: jsmath Homepage: http://sphinx.pocoo.org/ Priority: optional Section: python Filename: pool/main/s/sphinx/python-sphinx_1.0.7-2~nd70+1_all.deb Size: 1260232 SHA256: 648244da9a934daaee709edb7cd2d109551e93e215ebd43730a5a0bff017a035 SHA1: a878bb9a26d7085fd2ec3e02fa606ae3a44a9528 MD5sum: 9be86574fc484fd49d5be81bd6deba03 Description: tool for producing documentation for Python projects Sphinx is a tool for producing documentation for Python projects, using reStructuredText as markup language. . Sphinx features: * HTML, CHM, LaTeX output, * Cross-referencing source code, * Automatic indices, * Code highlighting, using Pygments, * Extensibility. Existing extensions: - automatic testing of code snippets, - including doctrings from Python modules. Package: python-stfio Source: stimfit Version: 0.10.18-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 516 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python-numpy Recommends: python-matplotlib, python-scipy Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.10.18-1~nd70+1_amd64.deb Size: 231246 SHA256: 185e7feda40ca1651e35e959ea4741c94a2269366dafd164982c9e022ddd6ca1 SHA1: c485f4bcca3fa24c3c95e6de9a49d8b1d4b80d7c MD5sum: 940344e705f5821b0a32692b799047d3 Description: A 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: 0.1+git21-g55debc4-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 124 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.1+git21-g55debc4-1~nd70+1_all.deb Size: 21888 SHA256: def514d65a4a3e29bdfc15593a490d79cade1a32197d99c892e400f905175a39 SHA1: 7b1f48845565efd55bd8e604ef68405ed5fe3842 MD5sum: d8769be59b6cdcda586a4ffb9c3366b4 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.6, 2.7 Package: python-tornado Version: 2.1.0-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, python2.6 | python2.7, python (>= 2.6.6-7~), python (<< 2.8), python-pycurl, ca-certificates Recommends: python-mysqldb Homepage: http://www.tornadoweb.org/ Priority: optional Section: python Filename: pool/main/p/python-tornado/python-tornado_2.1.0-1~nd70+1_amd64.deb Size: 223278 SHA256: 9062ef84ccd1c826e50113258d5a09ab715beb06e7e2300fb9db501d5c98b824 SHA1: 26ef56d367e2c3cd3faf2346df6e6d57e8231eb6 MD5sum: 362566030893f1c38e209b2abd9ad48b Description: scalable, non-blocking web server and tools Tornado is an open source version of the scalable, non-blocking web server and tools that power FriendFeed. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the underlying non-blocking infrastructure. Package: python-tz Version: 2011h-0.1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, tzdata, python, python-central (>= 0.6.11) Homepage: http://pypi.python.org/pypi/pytz/ Priority: optional Section: python Filename: pool/main/p/python-tz/python-tz_2011h-0.1~nd70+1_all.deb Size: 46920 SHA256: 575647f2a6f3d786f1794125961fd85dfb2490e8634093826891249252f46fde SHA1: 9a93132bae12a0329c788ca2a228d260c6cab54b MD5sum: 4b01de8116816e9eb270c79c97aa85e5 Description: Python version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). Python-Version: all Package: python-vtk Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29686 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libopenmpi1.3, libpq5, libpython2.7 (>= 2.7), libstdc++6 (>= 4.2.1), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libvtk5.8, libx11-6, tcl-vtk, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc, mayavi2 Homepage: http://www.vtk.org/ Priority: optional Section: python Filename: pool/main/v/vtk/python-vtk_5.8.0-7+b0~nd70+1_amd64.deb Size: 7300084 SHA256: 79cccf123b81910b7404da2470228da7f730901303fce6e8f1df9d8142398e79 SHA1: 670e7945161349fb336d6eeb74a71065dbaa92d2 MD5sum: 2c6b5f97194d746ffe6b6df8abf74895 Description: Python bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries that enable one to use VTK from Python scripts. You will need Python and vtk installed to use this. Some useful information may be available in /usr/share/doc/python-vtk/. Python-Version: 2.7 Package: python-workqueue Source: cctools Version: 3.4.2-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 423 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: python Filename: pool/main/c/cctools/python-workqueue_3.4.2-1~nd70+1_amd64.deb Size: 135890 SHA256: 15167347dea5799e30bf991316e6bdb5f4a670a3c82be15c2e60c9d75f7fdbd7 SHA1: c28021009479d583b02107bd3aeea1171a22709d MD5sum: 3d7f7820c55367c46d2858966d0a731c Description: cooperative computing tools work queue Python bindings CCTools's Work Queue is a system and API for building master-worker style programs that scale up to thousands of processors. This package provides bindings to access this system from Python. Package: sigviewer Version: 0.5.1+svn556-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 992 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.5) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-1~nd70+1_amd64.deb Size: 423954 SHA256: 73f66e6f5dc963f72671eb0807c52b9163643e6f50ca587bd4ab53b860f6d180 SHA1: 2baf707e4177e4d2efc7a3017d0bf8c53b214c4c MD5sum: a9b362ed51ad9f2ad059c70409156a39 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: spm8-common Source: spm8 Version: 8.4667~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 18467 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4667~dfsg.1-1~nd70+1_all.deb Size: 10573708 SHA256: b9d73e662aada20c16796e8e6ba41137f515583735b1363d39f34ead0d3a5d58 SHA1: 88b9a7d192e0f3f63ece738c0b48deac138af2e6 MD5sum: a2572180dac0762b3745f327b9f0cf6a 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: 8.4667~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4667~dfsg.1-1~nd70+1_all.deb Size: 52167704 SHA256: 9e26016d3833efc3b8b0c669ffc7c4c59a0986f5662a60ea2cf3bf6c6ca1cc53 SHA1: 44e14a239856e82d4a4d5aeff8afe585a0dab35e MD5sum: ba5e3d120390f42444b44ee24f277a62 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: 8.4667~dfsg.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9370 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4667~dfsg.1-1~nd70+1_all.deb Size: 8648906 SHA256: d6825506112d61cde6903ce21e5d0d880a714cab6eeed4c160d73c49259a16d8 SHA1: 394d1c423ad8ad1d1f55864a5979248c6a3c65ee MD5sum: ebf90c05e8ed3fd1b7389d0320f2f946 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: stabilitycalc Version: 0.1-1~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd70+1_all.deb Size: 28600 SHA256: d06a1ee5b6de6404f66db07820f084ca9699bfcef21015bb34c9cd64e1900e74 SHA1: 6515b207f33e7ef2ea59d0db40bb2b35d39355b8 MD5sum: 365f3a53daff4820e153393bb90a269c Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.6, 2.7 Package: stimfit Version: 0.10.18-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2076 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1), python-wxgtk2.8 (>= 2.8.9), python-numpy, python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.10.18-1~nd70+1_amd64.deb Size: 754200 SHA256: ba7504cc0e9d76b7469f717c2347ac5b51995fe36e1bd2d5c3789868ab25b9e2 SHA1: dfb68b89b418c238371cabafa1e06d329038d090 MD5sum: 7cd4bc0caefe4a7c99c6aaff96442b58 Description: A 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: 0.10.18-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24724 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_0.10.18-1~nd70+1_amd64.deb Size: 8262934 SHA256: 8d2fe5e3b4fddce3e690fae8c40baa114b387d39f66bd153e95b5ab935640a79 SHA1: 7589969778ecd9775af1e0427cfc9f283427dc88 MD5sum: 4e4e7a8ac5b93fcc593d1e66c14769ad 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. Package: tcl-vtk Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16157 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd70+1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libx11-6, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc Replaces: vtk, vtk-tcl Homepage: http://www.vtk.org/ Priority: optional Section: interpreters Filename: pool/main/v/vtk/tcl-vtk_5.8.0-7+b0~nd70+1_amd64.deb Size: 5322644 SHA256: 2f787363443fa6563ed9ad98b9e2e570a354106c758c5652b4ebf23aca8e4fec SHA1: eec67a1fadd025ba3069f8bf73fb323f5c466bd0 MD5sum: 93c1f13de7e12e1be1c105180edbd3d5 Description: Tcl bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries and executable that enable one to use VTK from Tcl/Tk scripts. You will need Tcl/Tk and vtk installed to use this. Package: ubuntu-keyring Version: 2010.+09.30~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd70+1_all.deb Size: 11794 SHA256: c326d77f59c53ce386ed48a4f622087920af9c2d0a9b826e734680500b0cd3a0 SHA1: a46c68a0539f105919576423f0daeb6709e6a10a MD5sum: 8bed9b239d848186981a2e04eec03bb1 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: via-bin Source: via Version: 2.0.4-2~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 628 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia2, libx11-6, libxext6, libxmu6, libxt6 Recommends: libvia-doc Conflicts: via, via-utils Replaces: via-utils Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/v/via/via-bin_2.0.4-2~nd70+1_amd64.deb Size: 180770 SHA256: 24267304fa1bc850db435571d21e5a6377fc6a46fc2ab6651aea60829f51f6a1 SHA1: 4d805d92442f6d4bc1596aacd2565e1eb4171e5d MD5sum: b11732d6d0c3028be0668f041559164a Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: voxbo Version: 1.8.5~svn1246-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10232 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti, matlab-spm8 Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1246-1~nd70+1_amd64.deb Size: 3755282 SHA256: 6bdf208f5be29c38d1a289781dc115bd8ced8ccca4666749bee93844550f6005 SHA1: 72dec9297a356f210fdea023341c40156a40fa0c MD5sum: da38303fc1cedf6c540fa94536d1a418 Description: processing, statistical analysis, and display of brain imaging data This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others. Package: vtk-doc Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 342007 Depends: neurodebian-popularity-contest, doc-base Suggests: libvtk5-dev, vtk-examples, vtkdata Homepage: http://www.vtk.org/ Priority: optional Section: doc Filename: pool/main/v/vtk/vtk-doc_5.8.0-7+b0~nd70+1_all.deb Size: 66709864 SHA256: 1a71117b4f7574428e9da98482fb0c2cb41581e0ca6d2e931ea639a5da51263c SHA1: 74a40de489c5a44161b4aa468547d356da0bf911 MD5sum: 4c9a59935cca888f4c608d56f7eb3213 Description: VTK class reference documentation The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains exhaustive HTML documentation for the all the documented VTK C++ classes. The documentation was generated using doxygen and some excellent perl scripts from Sebastien Barre et. al. Please read the README.docs in /usr/share/doc/vtk-doc/ for details. The documentation is available under /usr/share/doc/vtk/html. Package: vtk-examples Source: vtk Version: 5.8.0-7+b0~nd70+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2521 Depends: neurodebian-popularity-contest Suggests: libvtk5-dev, tcl-vtk, python-vtk, vtk-doc, python, tclsh, libqt4-dev Homepage: http://www.vtk.org/ Priority: optional Section: graphics Filename: pool/main/v/vtk/vtk-examples_5.8.0-7+b0~nd70+1_all.deb Size: 578898 SHA256: d070189a36ffd5bed00de02b3c794d0fa8f8bb2765fbc36f0f99c1634cda5ac7 SHA1: 132096d02c71c2f969d9baff0842e4afcdbb501c MD5sum: c018d4c1cace1b218dec239a1cf5e39e Description: C++, Tcl and Python example programs/scripts for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains examples from the VTK source. To compile the C++ examples you will need to install the vtk-dev package as well. Some of them require the libqt4-dev package. . The Python and Tcl examples can be run with the corresponding packages (python-vtk, tcl-vtk). Package: xppaut Version: 6.11b+1.dfsg-1~nd70+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5809 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libx11-6 Homepage: http://www.math.pitt.edu/~bard/xpp/xpp.html Priority: optional Section: science Filename: pool/main/x/xppaut/xppaut_6.11b+1.dfsg-1~nd70+1_amd64.deb Size: 4187354 SHA256: 5fc94705f843f8719cc00b08626bfe7800b55fd64b26d944313e5a09984da942 SHA1: 2b7c0b88eab5942584ce1c79755424e71b8363fb MD5sum: f5b23e13b63b29d071c016e1176a554c Description: Phase Plane Plus Auto: Solves many kinds of equations XPPAUT is a tool for solving * differential equations, * difference equations, * delay equations, * functional equations, * boundary value problems, and * stochastic equations. . The code brings together a number of useful algorithms and is extremely portable. All the graphics and interface are written completely in Xlib which explains the somewhat idiosyncratic and primitive widgets interface.