Package: ants Version: 1.9.2+svn680.dfsg-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 35496 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.16, libstdc++6 (>= 4.4.0) 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-2~nd10.04+1_i386.deb Size: 11184532 SHA256: 1b6bae4558ae752264bcb832322e1233b0ebfa1b40f899ecc53ce57437f20fc5 SHA1: 444d64c38c7db084da62e4ddb108b37cf54d090e MD5sum: e21d2f5db7d550662ae8a5942495b6a6 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: arno-iptables-firewall Version: 1.9.2.k-3~lucid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~lucid.nd1_all.deb Size: 132470 SHA256: 2e22eebc483d94eeac7b8dede959f75add3268e432e7a878c5d39e61a129c58a SHA1: 51c20f3f9a968af47adc9bc6dff312a0ad1abd2a MD5sum: b24e68173b3ce290b28f85c017f3a7b6 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: autotools-dev Version: 20100122.1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 216 Depends: neurodebian-popularity-contest Enhances: cdbs, debhelper Homepage: http://savannah.gnu.org/projects/config/ Priority: optional Section: devel Filename: pool/main/a/autotools-dev/autotools-dev_20100122.1~nd10.04+1_all.deb Size: 72976 SHA256: 766a04a0c3afdee01758bfb82390e4b8dda93cc48112d6326bb5b221693a1efd SHA1: 5549c54091c9eb5526b080ca8368a98573da91a3 MD5sum: a91ae7c928212a4367d8b2d60ed7e7fc Description: Update infrastructure for config.{guess,sub} files This package installs an up-to-date version of config.guess and config.sub, used by the automake and libtool packages. It provides the canonical copy of those files for other packages as well. . It also documents in /usr/share/doc/autotools-dev/README.Debian.gz best practices and guidelines for using autoconf, automake and friends on Debian packages. This is a must-read for any developers packaging software that uses the GNU autotools, or GNU gettext. . Additionally this package provides seamless integration into Debhelper or CDBS, allowing maintainers to easily update config.{guess,sub} files in their packages. Package: biosig-tools Source: biosig4c++ Version: 0.96.3+svn2677-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 13714 SHA256: 1ac10d15e242bcc2f9d28a826f8fac2f14500e3031cc7b38b4a6c4c1349b9019 SHA1: bea873ca7147d3bc3cc45c10c6e183cad50e35a0 MD5sum: a9a756ec1a146f46baeb422cc34ab280 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: 5.6.4~dfsg.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19176 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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), libvtk5.2, 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_5.6.4~dfsg.1-1~nd10.04+1_i386.deb Size: 7482818 SHA256: b5fc63e6e8ef8ca18dec5e23587029bc6d4c82f891d6d7a0da89965f6ffb5b8e SHA1: a0fcf9dad66bd46f632683db9b68e48d9626566f MD5sum: 48eed87b401a88195943bd8ebab563c9 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: cgroup-bin Source: libcgroup Version: 0.37.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 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~nd10.04+1_i386.deb Size: 61060 SHA256: fe6a77fd3db65f39e4312d696a9299b2dc3845870920a95bce2d587016aaf19c SHA1: 5f9007571d16b2610406a0270e0f273d98a92a2b MD5sum: 41e04ca77196a1746e7a646dd2cca96b 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: 2.1.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9516 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), 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 (>= 3.6.22), libstdc++6 (>= 4.4.0), libtiff4, libx11-6, zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_2.1.0-1~nd10.04+1_i386.deb Size: 3434796 SHA256: 5534f19305ebae63e1bf6e3ec6bfaa492d4ccd74f8083db4a9693ad88ffc95d3 SHA1: 09d6cad794931f3050c6fde098f5bec0e5b84496 MD5sum: e3b2f14e157ca206ec96782f89758f1b 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: connectomeviewer Version: 2.0.0-1~nd10.04+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~nd10.04+1_all.deb Size: 1354972 SHA256: 495bd4c7bb518076a39296fabf659a5adb9fc8a3f86cf6cdb72af19eb4836724 SHA1: 6e9d2f882e02f03144c03a5bdd2e831d84034413 MD5sum: c557115d95b40a71c75cb0aaaa6e2db8 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: 3.3.4-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3612 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.21-1), libncurses5 (>= 5.6+20071006-3), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0) 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_3.3.4-1~nd10.04+1_i386.deb Size: 1368892 SHA256: 82a3bfd01410f8a6da7d32e3340cdd0cecbc163018b669daddba25b81bf6a4ff SHA1: 202a0942b7c0a68d5c5f65579c2e8f8019ce3cd8 MD5sum: 3187472986332babda9b5dcf45fa9093 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: 3.3.4-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1024 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.3.4-1~nd10.04+1_i386.deb Size: 235782 SHA256: fdc2d844c82030420cd88117638647805a104e91fea6ead93f398f0b639f5ae5 SHA1: 8c90caa120956d375bb516616ebcdc01c375942a MD5sum: 85a88ad1ec3e52bedb89810d87c3a189 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: 3.3.4-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2436 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_3.3.4-1~nd10.04+1_all.deb Size: 275204 SHA256: 5a966a6cb7bb11ba688733320f6029d7cb67f7e8689bdc04bb2d1d68d0850f04 SHA1: 849526e746ed9c90c1f58ca019d7f8063b2d321d MD5sum: 616c8724aad899d3caa147c3a210ab7f 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: cython Version: 0.13-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3512 Depends: python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3.6-6~) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd10.04+1_i386.deb Size: 759852 SHA256: c2752a731e141b65f84449be53523d1d6baf4cbea8cf0cdf72c25c313a26c6e9 SHA1: 6d35074108f6e17f84e2fe58794fec127542074a MD5sum: e25caa29d83594c924916bd1b696a6f0 Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3880 Depends: python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), cython (= 0.13-1~nd10.04+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd10.04+1_i386.deb Size: 1462760 SHA256: acfc50c4c8093bc8c94f0d5bbfe5120c5499bc4bd7cc01466bb1ef693f9cf525 SHA1: dab6a7a045d5ed2830dd1a7721d6b6df9c0a321e MD5sum: 288e021b3b6a518da81bf2e5d86fa004 Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.6 Package: debruijn Version: 1.5-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) 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~nd10.04+1_i386.deb Size: 33878 SHA256: 14aae39f65111f76923d95e03e55135e368ed071759f0aab350a84aa9a36f888 SHA1: e3822b4bf931a6ce8769d9d42be07609972b6b43 MD5sum: 4630bdca5771376b96ce6da5319d70fa Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: dh-autoreconf Version: 2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, perl, debhelper, autoconf, automake | automaken, libtool Recommends: autopoint Enhances: cdbs, debhelper Priority: optional Section: devel Filename: pool/main/d/dh-autoreconf/dh-autoreconf_2~nd10.04+1_all.deb Size: 11738 SHA256: c47050d04ce742d3c4e886daba983267582b31f5cac01cdd1081e2ecb1d1691f SHA1: 4411d982dbf0e6baf3f74f0522324e685b7b18cd MD5sum: 69a117df6db798378a5a6f6f5e071e18 Description: debhelper add-on to call autoreconf and clean up after the build dh-autoreconf provides a debhelper sequence addon named 'autoreconf' and two commands, dh_autoreconf and dh_autoreconf_clean. . The dh_autoreconf command creates a list of the files and their checksums, calls autoreconf and then creates a second list for the new files. . The dh_autoreconf_clean command compares these two lists and removes all files which have been added or changed (files may be excluded if needed). . For CDBS users, a rule is provided to call the dh-autoreconf programs at the right time. Package: dicomnifti Version: 2.29.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 448 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.4.0) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.29.1-1~nd10.04+1_i386.deb Size: 149198 SHA256: d8f6eb629d3de0935aa28437871ab9fe6b097234201557e3420e2073b86a6a3f SHA1: 9a8ff14ae9ea4d357ec50bb6bd41754fab204237 MD5sum: 46509f8539694c1c198079b3cdcb69c3 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: 1.2.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3672 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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_1.2.1-2~nd10.04+1_i386.deb Size: 1578790 SHA256: 44aa324add809d7806feb2d71bda4d0c088f1df08bc2e0b61d5c5d7410505b57 SHA1: e4dee686ced67ca7c024b1738fdf7b5c13ca4174 MD5sum: 4c3193a34e4e0ae3b2069bdfbd18044a 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-Windows 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: 1.2.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17572 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_1.2.1-2~nd10.04+1_i386.deb Size: 6166858 SHA256: 8eb4835e6e0db6dbfd35e5bd82a91e677cd7689c49480c082cf671eaa5bb1892 SHA1: 19ff47ecc2d3fe42c11d904cd17bde21c7048388 MD5sum: 9c287ea14f7f46a5c8eec37fc9fd4a4b 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-Windows applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: eatmydata Source: libeatmydata Version: 26-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3) Provides: libeatmydata Homepage: https://launchpad.net/libeatmydata Priority: optional Section: utils Filename: pool/main/libe/libeatmydata/eatmydata_26-2~nd10.04+1_i386.deb Size: 8002 SHA256: 140291df087c22958282fb37a5837ce095d5e9a66e200ffe679d47f216828165 SHA1: 1042cb57472da5b720dfbb4f59e132fe8dacb502 MD5sum: c2884d9a0655fba7273fc7faf06e7613 Description: library and utilities designed to disable fsync and friends This package contains a small LD_PRELOAD library (libeatmydata) and a couple of helper utilities designed to transparently disable fsync and friends (like open(O_SYNC)). This has two side-effects: making software that writes data safely to disk a lot quicker and making this software no longer crash safe. . You will find eatmydata useful if particular software calls fsync(), sync() etc. frequently but the data it stores is not that valuable to you and you may afford losing it in case of system crash. Data-to-disk synchronization calls are typically very slow on modern file systems and their extensive usage might slow down software significantly. It does not make sense to accept such a hit in performance if data being manipulated is not very important. . On the other hand, do not use eatmydata when you care about what software stores or it manipulates important components of your system. The library is called libEAT-MY-DATA for a reason. Package: fail2ban Version: 0.8.4+svn20110323-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 596 Depends: neurodebian-popularity-contest, python (>= 2.4), python-central (>= 0.6.11), lsb-base (>= 2.0-7) Recommends: iptables, whois Suggests: python-gamin, mailx Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.4+svn20110323-1~nd10.04+1_all.deb Size: 98012 SHA256: a1e677480e2dd8f4a3a24bad8e1584300ef0acf3bbd0409e583ba6bf9e6185c6 SHA1: 78cae39933f68b734a0398cfaf5946bce6eb0ffd MD5sum: 7f083d11956584ab43fe787a6bb72112 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: 1:0.0.1+20101211+2-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-demos, libfreenect-dev, libfreenect0.0 Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.0.1+20101211+2-2~nd10.04+1_i386.deb Size: 2544 SHA256: 2d0add342af0a250b62ccb18dc68f2f73658034d682df7de5ac3cd3bdcb26e30 SHA1: 0e08ffc5b12784cddab96e364dbf9c57f8d4ff6d MD5sum: a71de1ae6c5134da8754dc4bb6b0cd18 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: fslview Version: 3.1.8+4.1.9-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3816 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8-b), libqwt4c2, libstdc++6 (>= 4.4.0), libvtk5.2, libvtk5.2-qt3 Recommends: fslview-doc Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_3.1.8+4.1.9-1~nd10.04+1_i386.deb Size: 1495454 SHA256: 8c4de3e80e7b07a50e305837dccc4568fb85c298cabccf650e2c7eefeb69ee34 SHA1: c33a4e74c0d62e515522ee87149b7c4ec5be8464 MD5sum: 242f640e46640b50559628f875fcf0fc Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.9-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3124 Depends: neurodebian-popularity-contest, qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.9-1~nd10.04+1_all.deb Size: 2351308 SHA256: a8896792b468c141afb5dfa9538903150180d641f3ae20b40b88837d2d3517dd SHA1: 1c42309b2ec3ae804ca9b6385f68ddb6b4a1bcc1 MD5sum: 96dab64c6fed2cc2df837f9d14c45a85 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gdf-tools Source: libgdf Version: 0.1.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, libboost-filesystem1.40.0 (>= 1.40.0-1), libboost-program-options1.40.0 (>= 1.40.0-1), libboost-system1.40.0 (>= 1.40.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.1-1~nd10.04+1_i386.deb Size: 38588 SHA256: a18add5402350a680169b55510d00ed0076c7254db22631e01479dfd656e1ca2 SHA1: 9239f4e26d3e3d9ba44cf51b62a6949a38170d44 MD5sum: 05184a16e7c4a2fd361fadf7ef74f261 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: gifti-bin Source: gifticlib Version: 1.0.9-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 128 Depends: libc6 (>= 2.3.4), libexpat1 (>= 1.95.8), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-1~lucid.nd1_i386.deb Size: 28726 SHA256: 8810eebe967dc7e1ec48ba779a5478d5c582cb6f03f0fff37c486ad71863b3bd SHA1: 9c34ccec417e753168fdca17ee0def6111a22c26 MD5sum: 38692e05685cf00a190df559af49347b Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: glew-utils Source: glew Version: 1.6.0-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 336 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd10.04+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6 (>= 0), 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~nd10.04+1_i386.deb Size: 119256 SHA256: 3b026f799369e895cc3a6f71a305fe9b330783fee74cc6f5f2333aae40d628ff SHA1: abf7e473164cbb0a834607b1da4d0935df348a5d MD5sum: 6b5b27878905e0fbe361c4ce676ac447 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: 0.4.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, guacd (>= 0.4), guacd (<< 0.5) Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole_0.4.0-1~nd10.04+1_all.deb Size: 209116 SHA256: fe1ee439defc00688bbd9be69f29082a7409c76203660d58df2b359985d31e74 SHA1: 50103ba58d0b0b80638683ce7db62e33e80966f0 MD5sum: 90efeb0dc209a6be54ffb9734c6c4fdc Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to your desktop using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser; no plugins needed. The client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole Version: 0.4.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72 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_0.4.0-1~nd10.04+1_all.deb Size: 2370 SHA256: 33f5bfb3684acd278ae118555699f970c102297f873424bfd1a748a838f6e200 SHA1: fc96b18ef2b19828a0b82cb5bdff67ef64620d63 MD5sum: a2b29ed00ddb7a496acdd814c364af97 Description: Tomcat-based Guacamole install with VNC support This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Version: 0.4.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.4), libguac1 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacd/guacd_0.4.0-1~nd10.04+1_i386.deb Size: 8540 SHA256: bb4c927e57d7d29a9b290ce38ebcd49a1bbbadbb9a5d14ad9ebfc51741646007 SHA1: ba989901643d8d0b2aaaaa58885c39519c49a748 MD5sum: ae3df4327a5d969dc989583a482818e3 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: itksnap Version: 2.2.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8176 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.16, libstdc++6 (>= 4.4.0), libvtk5.2 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.2.0-1~nd10.04+1_i386.deb Size: 3645386 SHA256: 4ad7870160286045278f226c2b68888464348ac615fb492a58f9510c3208e778 SHA1: c335ef9a990fe5643181aece0d3168a4e12e52a6 MD5sum: c445066e4fec7c715651e91e38ab652e Description: semi-automatic segmentation of structures in 3D images SNAP provides semi-automatic segmentation of structures in medical images (e.g. magnetic resonance images of the brain) using active contour methods, as well as manual delineation and image navigation. Noteworthy features are: . * Linked cursor for seamless 3D navigation * Manual segmentation in three orthogonal planes at once * Support for many different 3D image formats, including NIfTI * Support for concurrent, linked viewing and segmentation of multiple images * Limited support for color images (e.g., diffusion tensor maps) * 3D cut-plane tool for fast post-processing of segmentation results Package: klustakwik Version: 2.0.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 20916 SHA256: d199cbaec5620860373bbcf4d3eee54b99b7a98fde748bc43506d2396a05a676 SHA1: 03021f65ab3ac1cd69cce144b71ac15cee349619 MD5sum: 8f96daf3d642758d4dfb7e9e0ef3c501 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1224 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd10.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd10.04+1_i386.deb Size: 376528 SHA256: 268225ba3a82e37df85f56fef49485f618a8e5de35c5b693b774713c1be0ba2f SHA1: 913f714e56cabd2ee8108422192706415440e4b5 MD5sum: 7edf17e6dfa27b28b44086b9e1047608 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 768 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~nd10.04+1_i386.deb Size: 298568 SHA256: 030a7c05b265ec42e66b7f4c54315ff7cca83703daa7e32d6565fc7ff7b4defb SHA1: 3400f6a18876871c502265bae6bf3e996029dc88 MD5sum: cb7809290e6e3de6a159bcd03274b943 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 188 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd10.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd10.04+1_i386.deb Size: 57490 SHA256: f07b5c42e66817eb98a7af98a32ef12b607dc3697e010be27e5ee79d96414f79 SHA1: 10059e1c2806a57ff60c3ee619c4ba4f2505c7df MD5sum: 789d694d217f3ac258d54460a37ae146 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd10.04+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd10.04+1_i386.deb Size: 17398 SHA256: aa8437ca648f7527d366c439f86f44ea5344494c8666b7595763cb023864c51c SHA1: 42b9e91e9ecf0a534619517cdec25a00f3312ac4 MD5sum: 144fd4e703e8b98cd2a149990837870b 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libc6 (>= 2.8) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd10.04+1_i386.deb Size: 34656 SHA256: 9b44ace9b73d32d0affefaac283f0bbbf97ed57084dc1d2cdcd0149cac120d47 SHA1: 49c664389164b4bf5874483466731a2eb65a357a MD5sum: 535c08b195ac4013a7eecd84264fb763 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: libdmtcpaware-dev Source: dmtcp Version: 1.2.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.1-2~nd10.04+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.1-2~nd10.04+1_i386.deb Size: 6614 SHA256: b5f0ebc1a96419da5f1ed05b2794c689f69e6185ce95dc302b58afaa44ae3d18 SHA1: 18e1f56baf37351f9142cf48e56887cffbd7ee80 MD5sum: 7157270aa5600783c39bf0ae6359b0e5 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-Windows 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: 1.2.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.1.3) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.1-2~nd10.04+1_i386.deb Size: 6342 SHA256: cf27c16475cf101e475596af87be5dde88aa88fadfa22fd8242d8ca929b03963 SHA1: 239f2c89011b4208834b6117f831e8f4401a75af MD5sum: f8c8d7c46a4590dc6b37f78a1dc27a50 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-Windows 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 192 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_1.0b-1~nd10.04+1_i386.deb Size: 44310 SHA256: 8bf5ac24d85b617988740cb2e504b3bd2e45fa96ec10a27468f0760995451bc1 SHA1: ce2185d50ea7cce8eb8ecc1699678133e8b75bd0 MD5sum: b122b86b7ebde8e3ce6bdebc7a53857c 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 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~nd10.04+1_i386.deb Size: 31214 SHA256: 68d435921f3a3e1b7ee0a6db58b6265b449351f85c7bb9b7f212f14f159cce8b SHA1: 1e8e9912296a8beefc69ccd25b62207ce04ff02d MD5sum: a54523348508855a738ee32b83f8e4bc 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_1.0b-1~nd10.04+1_i386.deb Size: 60032 SHA256: 2c1808d32318954d16cf8e8701e951a45e5b0f33797fe7af0f6f8b68c3a55487 SHA1: d652d0149df863acc9b0deab04d18609111d4c46 MD5sum: f6a5cf90f70f1a5377cd5e89f75e86e5 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: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd10.04+1_i386.deb Size: 509892 SHA256: 6c2b2ae0030c26c44ff7e2c10b8db659d5573287c9ec58de32cc64b6d2fd5fd5 SHA1: 1cfa3a8bce227017c87e5e339445a0eee7b542e7 MD5sum: 68feec9c4e47d2eeb003b3f41278763a 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9988 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~nd10.04+1_all.deb Size: 2632910 SHA256: b4ca1b3c7938570708c02a7fb16f0737442a604a6f2d93d8de4ec37e03471b25 SHA1: a3b656c8267765b087234f9cee223f60cd662b50 MD5sum: 852cdaca8907732d104366ff1cc2e2b4 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-demos Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.6-6~), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libsm6, libstdc++6 (>= 4.4.0), libusb-1.0-0 (>= 2:1.0.6), libx11-6, libxext6, libxi6, libxmu6, libglut3 Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+2-2~nd10.04+1_i386.deb Size: 24414 SHA256: 87daff4991fef69fbdaf60c9845907ee114eda63161c4b03b10bd681253340c2 SHA1: 2d5edb878e75b1b82b186afbc5e1920d950b8cf1 MD5sum: 61fb497dc2ee5596c94fe11ed8da6988 Description: library for accessing Kinect USB camera -- demonstrations libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package includes some example programs for kinect. All programs start with a freenec- prefix. Package: libfreenect-dev Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+2-2~nd10.04+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+2-2~nd10.04+1_i386.deb Size: 18020 SHA256: 1305277cf89cb5e5ac6a8b49dff551a1d3f2a690aba8d3dec4bc6b2981de55b7 SHA1: ff1afce6b5370ab6c0508b66e033cf066d6dfb2c MD5sum: 1d862332bce2a04027ec068ccbeecccb Description: library for accessing Kinect USB camera -- development files libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect0.0 Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.6), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+2-2~nd10.04+1_i386.deb Size: 26380 SHA256: 2b9edc9a3e72f737dd8fb88ccb8a824c8f801e4fa0ffabfaec9be074f15084e5 SHA1: 6dc5725e8b0ee11e94c53b7bb12cdb4718b2b4d9 MD5sum: 01432ea7b1a8f1b7b3beb2981bfb6f1e 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: libgdf-dev Source: libgdf Version: 0.1.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd10.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1-1~nd10.04+1_i386.deb Size: 18526 SHA256: 966ecaa36120d1b554cba7500d5e17a58db7282703623d5ddda4d7b1c49195f5 SHA1: 3e21ec2c551e1b9275ed8133669befde3eec58fa MD5sum: 9d5630c6ab01c6128f991ff5c75671b7 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: 0.1.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.1-1~nd10.04+1_i386.deb Size: 106630 SHA256: 9d9e158e28d0356b4e41262549acad47841d5449ca6d978465112fd7be6d7527 SHA1: fdb91c313c888e0395806b4ee47980efe5de9578 MD5sum: 0fd44d4dcda8660d39b856b15f7726c1 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: 0.1.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3588 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd10.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1-1~nd10.04+1_i386.deb Size: 1089768 SHA256: 5bf7fbb3739f985c7a1bcbda57d8098e6c6d414049b4420b80f954de483191ea SHA1: df2a028056bde2b36c6c9e19e39c3cb605c5c211 MD5sum: 9897f04a8878e115e39c685a1a57b87e Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 208 Depends: libgiftiio0 (= 1.0.9-1~lucid.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~lucid.nd1_i386.deb Size: 62658 SHA256: fed86f601c429a8a28f88aaed8e6c712fc5103d3d47aba04d8571ab2bd338986 SHA1: 50d9edf5936ec2a9b007e21fd1c4364877b6632b MD5sum: 93a626fe23328146841ffa44639757c5 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 180 Depends: libc6 (>= 2.4), libexpat1 (>= 1.95.8), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-1~lucid.nd1_i386.deb Size: 57436 SHA256: dfa37e83dd839851f53c608ec8d7ddeccd77a5db9cf4884bc835b4eff3cb5fd2 SHA1: 3b40a0b537ab614d66d7c4a799197ac0f93a62f9 MD5sum: 70a761d68eb1c98296554f441e4fcdd2 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libglew1.6 Source: glew Version: 1.6.0-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 376 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~nd10.04+1_i386.deb Size: 119158 SHA256: 88d9fe06efcee5b2486ae980a5062d05a88fbfad9893d1cc228c3f609de8ee4a SHA1: ff28c66a4595c8b30b98ac62760785b963e15f23 MD5sum: 470e0170109b68c8526ed70068bd56d4 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1332 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd10.04+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~nd10.04+1_i386.deb Size: 235474 SHA256: e86fd4144b4fd2ee98c00ab14fd661dc27c3981742d7f7aa88bbe11432a1e6f0 SHA1: 781e4829d347210baedb9158b41cffac36f8875b MD5sum: 71fb1775a9a404cf4aaa8de11fb8e420 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~nd10.04+1_i386.deb Size: 105642 SHA256: 6c2856c947b8c315c7584068384d9ebd4d80743550fab8bc4ed5d8d52cde78a3 SHA1: 2294f47887974aa7989b357d48382580d11a7d94 MD5sum: 8b3a5c5599b7de502b03cd3cd28ab9c4 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 380 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd10.04+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~nd10.04+1_i386.deb Size: 93304 SHA256: f02e6d0ac070f428c6998315bed080a86621a3572e0808f76cbb1ac11f0ecc8c SHA1: bed5579545e1222631139425670c2a0072d50af3 MD5sum: d5f27bdb52a2309b138a2a837e54c025 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: 0.4.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcairo2 (>= 1.6.0), libguac1, libvncserver0 Recommends: vnc4server Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac-client-vnc/libguac-client-vnc0_0.4.0-1~nd10.04+1_i386.deb Size: 9646 SHA256: 700db037f9fa6d5882db7526311f7892c16577fb444ca71d1c4e8b1a4028c633 SHA1: 94581bca92ff6f4d0f39ddb461c5f67237582943 MD5sum: 1c42b05f56862ba9119d089553dda97f Description: VNC client plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac1 Source: libguac Version: 0.4.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac1_0.4.0-1~nd10.04+1_i386.deb Size: 11952 SHA256: 0cd1e21d871faf5708b9afa5800dd0e47eea893f6a169454718f4f0ee8a443b2 SHA1: 0abd3486c7692da75addc8161a9ac01bca0d25f3 MD5sum: fa785df013aab95f658f0ebd3dc13a38 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libguac1 (= 0.4.0-1~nd10.04+1) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac1-dev_0.4.0-1~nd10.04+1_i386.deb Size: 17880 SHA256: 1ec01b801dede822f727366456187696db263361fced7f4721a6fea9c0bcb5ba SHA1: 82d6ad8598e67a79a1d29b79024939849daf58a1 MD5sum: b97663042ab03ad6f26e69ccdfbdef59 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: libnifti-dev Source: nifticlib Version: 2.0.0-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 464 Depends: libnifti2 (= 2.0.0-1~lucid.nd1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-1~lucid.nd1_i386.deb Size: 151538 SHA256: 88cdad9f224b4ba27f2acf08791c1a034e39ac1b2088b391a7c4df75b97ba93d SHA1: 48ab980aadb2479d14a5780d54ce95825d49c54f MD5sum: 8fa0bbffe17506bab71a628d482af628 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1896 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-1~lucid.nd1_all.deb Size: 245482 SHA256: 8532e280818991cfdd6fe8e883f0bb5b3d0ca9bb86360cd2fcb98a2750f01720 SHA1: 39744b584b030525f62bd876863ebfadcac7e9ff MD5sum: cb7b7605b2710de9700586340deca337 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 304 Depends: libc6 (>= 2.7), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-1~lucid.nd1_i386.deb Size: 107418 SHA256: e778b3bd3b89599aee041cff9872331bc4f800aba1a95d780c509742d173c28f SHA1: 6fc543bbc1e61ff3fb57254db869f3c628ffd0a6 MD5sum: 6f7354ee6b0164563e5a57b7878b8c0d Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libodin-dev Source: odin Version: 1.8.1-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 15604 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~lucid.nd1_i386.deb Size: 4028892 SHA256: 791e7030921a9caade805ea347dfbe98d5f9b51be92e4cfd2c3b6d356c510c1c SHA1: 59f7ebcc5aa2303465e3dad6936d512140c8293f MD5sum: bb57a6d33d3b143e184774d532a429c3 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 276 Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-2~lucid.nd1_i386.deb Size: 43854 SHA256: 703c7e67bff1a7419240313e5b90187fbb0c9a4f5bfda653ec1fa7318be19d50 SHA1: 247e856f877b8d29b1c51803c2d5e843d8141c73 MD5sum: 2017cb50f958dc3dcb866fe796cf8c39 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-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 824 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libmatio0, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-2~lucid.nd1_i386.deb Size: 230648 SHA256: 0b7c79c917c6315b14ff518ba73746ed8b6fdafee5c00003ccf2251ccfb59130 SHA1: 05ab3ef5666f30d479b6a476c053c324d89b9f81 MD5sum: ee01b8a7bbc28e49097d91793f847003 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: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd10.04+1_i386.deb Size: 7650 SHA256: 1c639ac4301b1d8bf953d34200f5bbf0591c0442f114a5ac82d25d5f5a6bd2c6 SHA1: d9c462c29bc0051f848bb5b592e3c8ce57cae383 MD5sum: 8b1d795a9b17891ce50896af2e343c3a 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-1~nd10.04+1_i386.deb Size: 12552 SHA256: 0142fc285e2ce28b4898c2f9d53f5d1f1cd6b70b15d58984b90b198fa8eb5eb3 SHA1: 1a89ad13e8c97ab1c7332614a25957d9a657be81 MD5sum: 25f1d860c6715a8f438cf2b123e6ac95 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-1~nd10.04+1_i386.deb Size: 26556 SHA256: 51912b1a7c9f3f1042f0d98868b4bb363da31ffa2edd0ed94d8e7424d5136363 SHA1: 3b9277e54d58de7d0fce700052ff8432b798eb67 MD5sum: d49de0fda72b5d5385dd907c891e53d6 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-1~nd10.04+1_i386.deb Size: 28134 SHA256: 68ca4e4bf6cbcc4b02b2b29018369a198ceed721794d0ef8056d492d32ce4185 SHA1: f939d9313f47821841678bf6b8ce56bc4127ba73 MD5sum: 34d25262015818e9a95b7d5e4143c372 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: libsvm-dev Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd10.04+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd10.04+1_i386.deb Size: 28198 SHA256: 5edc8eacdb456593eebb4016d8d1ca22e059230957802689aa8c040030fe3934 SHA1: 0c8c8b4102539b60b729ec23f7437277789bcc13 MD5sum: f8452a57ddfa47fb273373632b024828 Description: The LIBSVM header files These are the header files for LIBSVM, a machine-learning library. Package: libsvm-java Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libsvm3-java Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm-java_3.0-1~nd10.04+1_all.deb Size: 2070 SHA256: cd2a86db92cc66fbb16350a64ab624f2511dcc74206606d4f824709995a9f60c SHA1: 48795086f73056edc3a91a03dfa0a68c01d54ab6 MD5sum: 30257da2669fedaca525b0b2394ff957 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. . This package solely provides a symbolic link from svm.jar svm3.jar. Package: libsvm-tools Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python, gnuplot Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: devel Filename: pool/main/libs/libsvm/libsvm-tools_3.0-1~nd10.04+1_i386.deb Size: 112492 SHA256: 831ee1bb88cf2bda5d70228306fa8e35056d1ef4b9f4dbaafe16f3859725bdc0 SHA1: 3462bfaee6621eb30236390b9c062ce2fe8cf934 MD5sum: 09cb5245618baf76785495939de4df20 Description: The LIBSVM binary tools LIBSVM is an easy-to-use package for support vector classification, regression and one-class SVM. It supports multi-class classification, probability outputs, and parameter selection. LIBSVM homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm Package: libsvm3 Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libs Filename: pool/main/libs/libsvm/libsvm3_3.0-1~nd10.04+1_i386.deb Size: 43082 SHA256: 422c6c1572b5d528a8309c54c70fe2ff75daeca639f9366692992aeb322d5ba5 SHA1: b97111930d3c68f075c75c27fd62ae71118e408f MD5sum: 378b6a250383093ae3c713f4f710181e Description: library implementing support vector machines The LIBSVM library is used to calculate Support Vector Machine optimizations with a great variety of powerful options. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. It is primarily of interest to machine-learning researchers and artificial intelligence application developers. Package: libsvm3-java Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, gij | java-gcj-compat | java1-runtime | java2-runtime Suggests: java-virtual-machine Conflicts: libsvm2-java (<= 2.91-2) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm3-java_3.0-1~nd10.04+1_all.deb Size: 60476 SHA256: e764602df3fd3e56e22b684e094974116883ad0e0ba3fd85d6eb650a59ab33e9 SHA1: c4532f5c5c7defa06c81962d2bd23db9164b85de MD5sum: de7bd41053daf8de4d5bebb3578df435 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. Package: libxdffileio-dev Source: xdffileio Version: 0.2-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.2-1~nd10.04+1_i386.deb Size: 27726 SHA256: 3d67ebb45f0e2633e6270272b70509a6dd2e509f9d4bbd60103619254b36affa SHA1: f53bd182ffd628831bb49694d965613ae67bbe21 MD5sum: d3a0f7b0a1b99c3d8e4a3c350e65d069 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 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~nd10.04+1_i386.deb Size: 40898 SHA256: 4ad9ecc6f5ba0a5a921912d4b5e09214ce5ede993258a4c591f9f015ef3362a8 SHA1: bcaad13f08a891043f9e6ef5bc60fd1a488bc453 MD5sum: 6cdd452075e932f8ab5e1571ff1cd551 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd10.04+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.2-1~nd10.04+1_i386.deb Size: 58520 SHA256: bb4ccf083aaecc8f0ee88921c6d517ed3a91e8e3775d5e27328cc992c376d912 SHA1: 321a77cd23d32735dfa6e1bcd00dd9393771f40a MD5sum: 60525d8bc3116bfb9de7210451d4deb6 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: lipsia Version: 1.6.0-4~lucid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3620 Depends: libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti2, libqt3-mt (>= 3:3.3.8-b), libsm6, libstdc++6 (>= 4.4.0), libvia0, libx11-6, libxext6, zlib1g (>= 1:1.1.4), via-bin Recommends: dcmtk, lipsia-doc Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/l/lipsia/lipsia_1.6.0-4~lucid.nd1_i386.deb Size: 1275324 SHA256: b4ce1f08f3d5c7e535bdb95ece4f8df517b32b22cae05127790a052d46cf85f8 SHA1: 38d5698247747783e147ad72d72cda4f10de105d MD5sum: 605f02cf5b63c84f4c6221515aaecfb5 Description: analysis suite for MRI and fMRI data Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an efficient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development of LIPSIA was the efficiency of the software implementation. . LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported. Package: lipsia-doc Source: lipsia Version: 1.6.0-4~lucid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 7004 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/l/lipsia/lipsia-doc_1.6.0-4~lucid.nd1_all.deb Size: 5539278 SHA256: fe6e759a40698cc35033edebd496733ddbb082eeeda66fcddb091906f0f1238e SHA1: 435a391bce4fdc0bbb017bf0214f4f42e18bec55 MD5sum: 2dddb5c30d3c0cbdfaa56523cc87dd21 Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: matlab-support-dev Source: matlab-support Version: 0.0.17~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 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~nd10.04+1_all.deb Size: 6706 SHA256: daad9f0ff02f6f8155872db7bc98774c48b6a6e42087aef94f22634e46d7d4b5 SHA1: 3a958294e0ca892d2763042ab2ae11c677beb344 MD5sum: 70d7ab6d772e85787ddc552db7f5abf7 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: mitools Source: odin Version: 1.8.1-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 6184 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.11), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti2, liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.2, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-3~lucid.nd1_i386.deb Size: 2337796 SHA256: 8fcac83fd736a862ec21ca239b983681bd6bb8d1950d4adf425bbc6c394abd63 SHA1: 7c88f3430b4c2174f51d7cba6c39a8c191a85b24 MD5sum: 9ebcdc86e53f6e0a1b1b5884530dcab9 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mriconvert Version: 2.0.217-3~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2144 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_2.0.217-3~nd10.04+1_i386.deb Size: 771142 SHA256: 8ff24ccec58f08e435ef7b01ae471b116a60660905e0675c414db3045780e597 SHA1: 74b1a1dea38f4b65db7801e1d33032689c37f38c MD5sum: c9dfdbf719a754bdee1f8961fa4067a6 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: 0.20110812.1~dfsg.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10720 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.29.3), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.8.0), libpango1.0-0 (>= 1.14.0), libx11-6 (>= 0), 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_0.20110812.1~dfsg.1-1~nd10.04+1_i386.deb Size: 4078138 SHA256: 7526e4b9da7851e0361a40c1c3b61cbafac57c26f46d5f198e62227848abbae4 SHA1: 1f464e1724839841b66fadee5d5090d57979abb4 MD5sum: 445c3952d9af5a7822735409b324184d 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: 0.20110812.1~dfsg.1-1~nd10.04+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_0.20110812.1~dfsg.1-1~nd10.04+1_all.deb Size: 1666896 SHA256: e57e188b45b508acebf7c544188acad71caae469304a4235c08a7af503c6e54c SHA1: 3b024aa9c3aa4acc3c1bebc1ad99cc02f55230d9 MD5sum: 21485a4f507ca4dafa54ac4e6d7f6a35 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: 0.20110812.1~dfsg.1-1~nd10.04+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_0.20110812.1~dfsg.1-1~nd10.04+1_all.deb Size: 738358 SHA256: 52fab2564d7067a13fd7ae109ffb17f2f27252a11204968b2b1ec97fc9d6c3b3 SHA1: aab260467cfa93f1fa5a013b09ade02398c4929b MD5sum: 0cd67e99771c8cfb23e70ff89a39c3a5 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: 0.2.9-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6532 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.29.3), libc6 (>= 2.4), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.24.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.20.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.26.0), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.3), 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_0.2.9-1~nd10.04+1_i386.deb Size: 2293458 SHA256: c8700f5a319670465af77105e9af1798713a220ff33edd0b56ea49323400d744 SHA1: 926f5e5ea437da978c6babc2928f5a2c93262725 MD5sum: 8c5822011ab8285194553bc3394ec740 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: 0.2.9-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3312 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.9-1~nd10.04+1_all.deb Size: 2945972 SHA256: b7b7c9bda795b432e743671d846f1a40b9e4506de2d5b7a7fda31fa0d8fe5135 SHA1: 53bd891a187c91ce5b01f35827d2c1f73e9afa25 MD5sum: 1619e208ca754e13f7638201aa80febb 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 268 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~nd10.04+1_all.deb Size: 113580 SHA256: a62c25fdbb266037a7344a36ddcd3c516cf4adcf654f91b98b074a3de99a0f36 SHA1: d93eed7efbe87baa3c5d3386d49f48fe5d0ab763 MD5sum: be76d54b5f254582e7808f36288c1c1c 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5860 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~nd10.04+1_all.deb Size: 5087710 SHA256: 4b38e7827c90db1c8620916a95e78b9948b16d175fcedfd9aa16f27b31c84dab SHA1: a217437adfdb2b6a45d91490459bb9aa69fa499e MD5sum: 7967d3650247c0a9da6cd5c497c71ea6 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 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~nd10.04+1_all.deb Size: 13440 SHA256: 0355ff46d78e39d723e6ca81e9bd4424bc7cb304e46329a34eb1442d30688de4 SHA1: ae4f22db53d36ccc33c7f572a1567308639f3851 MD5sum: 6dfee53e74f4065175c3740b12d43af9 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.27~nd10.04+1_all.deb Size: 6394 SHA256: 3ae4abf11a6defebc713e83f53192d68cd45fdc75080a71cd882db1123657a28 SHA1: e13f0f020385e28c4accb879168dc32af678b8be MD5sum: 692cdcb20aab8e39465cddd0d2ba981d 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.27~nd10.04+1_all.deb Size: 5564 SHA256: 9b81f51af98025649c73cd0418db77be2ac70fb3a20b3011f34a0c6ebcabd4d0 SHA1: 2713979df42a605d5433942b779b50d6e1c0bdcd MD5sum: 16d5dfa803a4ea5b578fee070396b6fa Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti-bin Source: nifticlib Version: 2.0.0-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 200 Depends: libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-1~lucid.nd1_i386.deb Size: 59304 SHA256: 409ea1817447802a46a94084b2c278ceb197a934aece3262cc6e1c99806e3863 SHA1: 6bc623df2532ebda6606e264b7da98e6a37b0733 MD5sum: be175735d76d824c0719f942f13f6946 Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: 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: numdiff Version: 5.2.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 676 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.2.1-1~nd10.04+1_i386.deb Size: 446188 SHA256: 9f7a7b7f08d29a5c301a75623e370fbb93e9840eea16578816ffe01e02ad4bfb SHA1: 4e4def827f71cf1b12ac0e3bf6a192adaaceb715 MD5sum: e83f021875f4283eed5e6ce60f3daf91 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 60 Depends: neurodebian-popularity-contest, libbiosig0, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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 (>= 5.6+20071006-3), 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~nd10.04+1_i386.deb Size: 19066 SHA256: 579585f9ec68c9778900c50662c39360aba7f99c1597794cbff923c9b58ffd27 SHA1: b170b04447d57299b0d3da83aaa4d43547de431b MD5sum: c11f87ced87ef06ff930dc9f7c0de579 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: 0.1.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.3), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.1-1~nd10.04+1_i386.deb Size: 133732 SHA256: 5c7e6118befc26809d573056a3555a6ed92353416c81af60fdf3a40199c0a56f SHA1: dd423a4628832f8c0f2f530a3a49da59b9cadbbc MD5sum: 0a297c097595e11066e921f827e66c35 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+svn2380.dfsg1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2208 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.3), freeglut3, libasound2 (>> 1.0.22), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.6 (>= 1.6.0), 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), libraw1394-11, libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.6), 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+svn2380.dfsg1-1~nd10.04+1), psychtoolbox-3-lib (= 3.0.9+svn2380.dfsg1-1~nd10.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.9+svn2380.dfsg1-1~nd10.04+1_i386.deb Size: 714370 SHA256: 3228809a0317dadf59ec3c57f71ca774d79533e9454bee2f38d2467f1bbc98e1 SHA1: b334d1a0f9374b1e965ad221d55d8596bd7ec6a9 MD5sum: ef88296b694220adc3fb80e398f1e0c4 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: odin Version: 1.8.1-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 4016 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.2, mitools (= 1.8.1-3~lucid.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.1-3~lucid.nd1_i386.deb Size: 1548012 SHA256: 338fa901998f8aabeddee1c42439003ef873a48a25c1e55f9178fb804af2376e SHA1: c74539a99013b8f3c7619d89c5c015e32e82011b MD5sum: f524d75bea815548a4bb311d237be542 Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 556 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, 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-2~lucid.nd1_i386.deb Size: 152040 SHA256: adc851c42b9f6b3282eba80819b552f1dc1ab057004f99ff9869c8a3ede5288a SHA1: 2c030a165b5374f123f92406e392ed828b7e310f MD5sum: 490baf793bf7bd2be6ea1e58b657d785 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5000 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~nd10.04+1_all.deb Size: 2848364 SHA256: 96bcb11e50dd78f37dd819cca2ff345fc7e2f5f9e50b8d785746bee0833926bd SHA1: faf7c705ab3298ec4eed6f5cbf58d614b0653894 MD5sum: 4690698f13bf7f11c614ddda038075bb 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 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: 1.71.01.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5016 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_1.71.01.dfsg-1~nd10.04+1_all.deb Size: 2659136 SHA256: 3a1f6648621c82a4da30fd1d5e1a622e8bdcddf35e7c437a0cd86d0c3ade1f54 SHA1: 7de927b997c3b77a10cb2186b9d40bd7132e23a7 MD5sum: a47580fb0bf44da0e31aab424b028696 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 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2380.dfsg1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 54400 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2380.dfsg1-1~nd10.04+1_all.deb Size: 19698812 SHA256: fbb99335d242bb4caba4c579284a4911b137be7a0299689ce9d6f2655414701e SHA1: 49099c5f4336948988a5dc0c4330bef88fe9b26a MD5sum: fa15b29306a55f83b1106565c34a8f7c 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+svn2380.dfsg1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2280 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2380.dfsg1-1~nd10.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2380.dfsg1-1~nd10.04+1_i386.deb Size: 767046 SHA256: 01955a62f7069ff18eb024f0551e9bec5188f9caed7de42bef507e1fc866c7de SHA1: 45444a2724b9a259a0e18ad2a35a2b75b3958009 MD5sum: 386db6fb9d66604bed2d8075ee674ce3 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+svn2380.dfsg1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) 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+svn2380.dfsg1-1~nd10.04+1_i386.deb Size: 61782 SHA256: 5aafa43d0bdbdc55e40ae5501aca769586d31f61e8a337db768d02a2a0c16a1a SHA1: 060c00768ec045d0ada5ff748029de338d6a40ee MD5sum: 040fa8b3ef4bc4bd0762a987e06608e1 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 204 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 51536 SHA256: 95c5a93ee2abf0405a0adf2aca0cf3f4e8109b8e19c96d0eb228600c7967df9b SHA1: 8a18c8280d7d686a0e8a8a2ac91289e6152acaf8 MD5sum: a64a6296bb582d40883f8eb5de556fcd 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2096 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.1-1~nd10.04+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.1-1~nd10.04+1_all.deb Size: 393400 SHA256: aa6e609216f8f2a7c50554f75f32704655ca53d3a80b0593cb55a44b2f093405 SHA1: b97c0fb335728c2ab4a8b2e49821ed10707ecc52 MD5sum: b361e06bc8278dbed5cb8278c32a9ddd 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6112 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~nd10.04+1_all.deb Size: 1973510 SHA256: 298f08710667ece8633f8929c5642c54372a201f580e37f08a7043b643e5956c SHA1: 3e4fb7f1a3225b48bc0ac847ed5bc9015fa243c7 MD5sum: f029df770baab03e65f179c36104d290 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 52596 SHA256: 5976d3b2f85bb14d68f2b43d8289c110b35976168a326dd834fd2d3c463e7e45 SHA1: e8a43ec7dabeba28d340f666d693aae57620a068 MD5sum: 03330bce11a5d8c714522b40c745e995 Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-dicom Source: pydicom Version: 0.9.5~rc1-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1864 Depends: python (>= 2.5), python-support (>= 0.90.0) 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_0.9.5~rc1-1~lucid.nd1_all.deb Size: 372938 SHA256: f69403f36f3840a1b00833c53b9d5423ad12355073192a8245781a34954569bd SHA1: bda525b6678d316b2c50a3f9d3de8517ab999de9 MD5sum: 0c83a634b771ca0cc6de5bf844aabec6 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2068 Depends: neurodebian-popularity-contest, python-support (>= 0.90.0), python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-2~nd10.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.6-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-2~nd10.04+1_all.deb Size: 1457518 SHA256: 7fe4f7ef487a9cf892f70978c8fbc3bde19cc1a5f979306bbf81e0391fe9b987 SHA1: 8dca44990c99df102fb855fdfcdbbd18132a47f5 MD5sum: ee2188f0ac6b2448c4228004157b78dc 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 Package: python-dipy-doc Source: dipy Version: 0.5.0-2~nd10.04+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~nd10.04+1_all.deb Size: 1943692 SHA256: 5354f09992126fa4c31ca068a1403a08e593b67181db0093595d595b7f8212db SHA1: a363fd3d92797010bab795fc79d9f729241369d7 MD5sum: 92c310d11f5a79031b1e1916288c5e5d 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 552 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.4) Provides: python2.6-dipy-lib Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-2~nd10.04+1_i386.deb Size: 186138 SHA256: 5b9440e7dc964c2da964b01443dae25954661731116191030db37bc61e163686 SHA1: b08f44834cf884a1f55cedfc7ccca832f66b0fef MD5sum: 72570f66d623a8cf5099c50cf3b42a54 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 Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreenect0.0, libusb-1.0-0 (>= 2:1.0.6) Suggests: python-numpy, python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+2-2~nd10.04+1_i386.deb Size: 27764 SHA256: b31b62984c3bf4a64db143d11152d5cc64d076cf4b2d66d536cc39ab22fa35b2 SHA1: 0eccf70494ed1885d99f41853b49f70dda9f86c2 MD5sum: de0ce340ed0398229194e9025a4d303d Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.6.0~b3-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 248 Depends: neurodebian-popularity-contest, 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_0.6.0~b3-1~nd10.04+1_all.deb Size: 50382 SHA256: e6be8ed6c835c5fd20b860fee86470faefc2e22d6525a4674b10dae97fa2ca0b SHA1: 091577149997a04809eb16ef347ff1cf5bef88d8 MD5sum: b3362d1ec4c094bf073dbee4c642dce7 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-libsvm Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd10.04+1), python-support (>= 0.90.0) Provides: python2.6-libsvm Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: python Filename: pool/main/libs/libsvm/python-libsvm_3.0-1~nd10.04+1_i386.deb Size: 7610 SHA256: 22ae8a50250d592283719779bdf25e9d09774883ab6df4f628a95dda65f4748a SHA1: b522df6f64dbeb91a4aa0e747a30ebbe8d2e2f29 MD5sum: 762130f8ebec76d175ab3c3724501f37 Description: Python interface for support vector machine library Python interface for the LIBSVM library using ctypes. This new python interface is provided since 2.91, and it is incompatible with the old one. Package: python-mdp Source: mdp Version: 3.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1812 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-scikits-learn, python-joblib Suggests: python-pp, python-py Enhances: python-mvpa Conflicts: python-libsvm (<< 3.0) Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.1-1~nd10.04+1_all.deb Size: 455344 SHA256: 68e9b7743913d17c3b36d874fca116b77c3e4592eb86230aa89ae88625458f38 SHA1: 5e2631cf41e9c5bdb930241f1a1dfa6f3c8864ad MD5sum: b775af885242127b6344898fd48db3e8 Description: Modular toolkit for Data Processing Python data processing framework. 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-mlpy Source: mlpy Version: 2.2.0~dfsg1-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 424 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mlpy-lib (>= 2.2.0~dfsg1-1~lucid.nd1) Suggests: python-mvpa Provides: python2.6-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy_2.2.0~dfsg1-1~lucid.nd1_all.deb Size: 55840 SHA256: baccc7f46670565245f2d9aa65acaea015872d8bb7bf398642a714a9fea52a2f SHA1: 38f57e733f49c401922c25d85a89b5044e68181b MD5sum: cd3699a47eb5ad404aa7864cf95d69ea Description: high-performance Python package for predictive modeling mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . mlpy includes: SVM (Support Vector Machine), KNN (K Nearest Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression, Penalized, Diagonal Linear Discriminant Analysis) for classification and feature weighting, I-RELIEF, DWT and FSSun for feature weighting, *RFE (Recursive Feature Elimination) and RFS (Recursive Forward Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated, Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time Warping), Hierarchical Clustering, k-medoids, Resampling Methods, Metric Functions, Canberra indicators. Python-Version: 2.6 Package: python-mlpy-doc Source: mlpy Version: 2.2.0~dfsg1-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1132 Depends: libjs-jquery Suggests: python-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: doc Filename: pool/main/m/mlpy/python-mlpy-doc_2.2.0~dfsg1-1~lucid.nd1_all.deb Size: 478768 SHA256: 57a934ed3182a9624128bea20def7710fd79b49a10356d8a04a243aeb6ca6a7c SHA1: d9e6be19ce66c9a83358c704eed4daa666588a1d MD5sum: 24528b12939bcd8156611770fc0162e7 Description: documention and examples for mlpy mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . This package provides user documentation for mlpy in various formats (HTML, PDF). Package: python-mlpy-lib Source: mlpy Version: 2.2.0~dfsg1-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 292 Depends: libc6 (>= 2.3.6-6~), libgsl0ldbl (>= 1.9), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-mlpy-lib Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy-lib_2.2.0~dfsg1-1~lucid.nd1_i386.deb Size: 61894 SHA256: 6964974dad0516bc5e5238a3cd08e905c393664f41a846bc7611351690bba9e7 SHA1: f53b38aec69597ed93c23aa1ccf0dd6fb3ac4914 MD5sum: 87184a9e1df82a989bd247c839eeebd3 Description: low-level implementations and bindings for mlpy This is an add-on package for the mlpy providing compiled core functionality. Python-Version: 2.6 Package: python-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 992 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.3, python (<< 2.7), python (>= 2.6), 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~nd10.04+1_i386.deb Size: 277200 SHA256: b2859b263b7ba63bc86bf42363520106cb33c9a4e2805d5c7e23b9f43e32f60d SHA1: 850934dc17a7376715f0549e8df6b19c5f2c7ae9 MD5sum: c9f514b1d1a5259b6511291f70d03c8e 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1364 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd10.04+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~nd10.04+1_i386.deb Size: 509736 SHA256: 52b27cead00055e097fce5b4369673b9c4a0e9cff1c993adc1705243a3c3f0c0 SHA1: fa3c3f0e47252fd6e796c9e72eb4d403f23ee1ef MD5sum: 4965f55d51c098ad48abb168163d3f72 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~nd10.04+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~nd10.04+1_all.deb Size: 54816 SHA256: a55e11c01ac8a5e1ca5bc442a860a919acb05e57760750bc31aa3f20f1a381c7 SHA1: da3e4a0c0f25b2fcb30fbb885f64d8bce56f3309 MD5sum: 70814f5b07427ccc2a1bb8977894688b 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4064 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-2~nd10.04+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-2~nd10.04+1_all.deb Size: 2188628 SHA256: 9bb8e22d1bcfb871333a6d84cdd7cdb8269daa96d80508c713f1f6a9384164b1 SHA1: 47e9f2a83bd4fd6e50cfc4847677384512a19ae9 MD5sum: 18ab359d3bee4ed61746171ba52047fd 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: 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41136 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~nd10.04+1_all.deb Size: 8747974 SHA256: b99b5a1eeab2b7fab2565dd302f0dc81526eb3c0329ace32f8e533ce0ab99711 SHA1: 3963085c92d873ec46ce65f6d503c773750d17ce MD5sum: 6c22290af0275d4684a139e24cfafdd6 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: 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~nd10.04+1_i386.deb Size: 34658 SHA256: a67466cb504d88b8e20e655a34fc5ec45624bbe41bbc2ba0b8fde3dc8999f0f6 SHA1: 904b094b76b8f125ecf6f4b45a66f4bf3301636e MD5sum: 4b22052da9eead25b130fbf87d287b11 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.6 Package: python-mvpa2 Source: pymvpa2 Version: 2.0.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4624 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0-1~nd10.04+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 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.0.0-1~nd10.04+1_all.deb Size: 2319740 SHA256: f3a30dd2788bd12467d37c5bb806d2e047fc0600af886a39262a1906b3cfea09 SHA1: cc895b38b38fbc194d729407aff6bf18faf983dc MD5sum: 1d49ce3c205fd079d097c4b81ba29a87 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 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.0.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24344 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_2.0.0-1~nd10.04+1_all.deb Size: 4616278 SHA256: bbd6ef2d2067604586b585fb6de3db4afda477953006e813d81b66f5a3e12b0c SHA1: b29b4fb8302e7b562a8c92ef6c53dff7e0ad1870 MD5sum: a672f8d747ed84955d4546c5323131fa 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: 2.0.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.0.0-1~nd10.04+1_i386.deb Size: 44134 SHA256: cebed2c6d4b29fd5e334a61b96611eb27edbbd7e49e3b775234ff25c0593bd0d SHA1: 5d1ffed3f7286bc617eda0152524be45821b6139 MD5sum: b64d439c2eef2272d89427967538eb54 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 Package: python-networkx Version: 1.1-2~lucid.nd1 Architecture: all Maintainer: Debian Python Modules Team Installed-Size: 2628 Depends: python (>= 2.5), 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_1.1-2~lucid.nd1_all.deb Size: 679700 SHA256: 3b794d495a6f1402468c60983b75a41ace947be4219d2708c30469d700ae4f86 SHA1: e3e60ed53545f966ce1b2bef6b05b7cbb35d65b7 MD5sum: b12742ab70af33463e848ecf7cf0d6b4 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 we mean a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network we usually mean 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-nibabel Source: nibabel Version: 1.1.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3612 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.1.0-1~nd10.04+1_all.deb Size: 1674934 SHA256: 5888a4d75b0bc537538d00af3273b037afaf0738c6008802299e73c52e23b859 SHA1: bed927d17ea1946bdd2448a700e16619dd8c16d2 MD5sum: 30f0c88b902b20a7243c72244ed7d29a 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 Package: python-nibabel-doc Source: nibabel Version: 1.1.0-1~nd10.04+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~nd10.04+1_all.deb Size: 411702 SHA256: 2f54534c91f596c1896a8fb2f5898732b5d34992dda368c4698818e4bafc44eb SHA1: 6a61b70d7c3ce7068de8c3116c7b0729216268f1 MD5sum: 7b06b123dbb41b286dd2bf9cff7e25e1 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1088 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libnifti2, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python2.6, python-numpy, libjs-jquery Provides: python2.6-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-4~nd10.04+1_i386.deb Size: 280036 SHA256: 5443631460d36c1071d69aa150054c3749b1663e785d412c8cbeeac49ec9f467 SHA1: 72f12e4770d16c8cc0e1d18b145ec8ab5da9b6f7 MD5sum: 86c9d8747147cd56b8df5f70b3718db3 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 Package: python-nipy Source: nipy Version: 0.1.999-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3684 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-numpy (>= 1.2), python-nibabel, python-nipy-lib (>= 0.1.999-1~nd10.04+1) Recommends: python-matplotlib, mayavi2 Suggests: python-mvpa Provides: python2.6-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.999-1~nd10.04+1_all.deb Size: 743332 SHA256: 063e8a911ab1d8d7d7333390c5b4f1e21b5bb71a0b4b2a13b40fd870ebce570c SHA1: 44b3af104871d3a3dec2a6daf3d2e962c073754c MD5sum: 4580468a402223e5ea02b8d7a5fd5fed 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 Package: python-nipy-lib Source: nipy Version: 0.1.999-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1236 Depends: neurodebian-popularity-contest, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.4), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0) Provides: python2.6-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.1.999-1~nd10.04+1_i386.deb Size: 443596 SHA256: 98ab939955654896ca0321d91b3886b4ccb0e9510a20449647c8b616bde737fa SHA1: 119101598ae17123dabb137a0150247bb143eb99 MD5sum: ab3c8a61e6351e5ba3724ba6a023d3e0 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 Package: python-nipype Source: nipype Version: 0.3.3-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1752 Depends: python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits Recommends: python-nifti, ipython, python-nose, python-networkx Suggests: fsl, afni, lipsia, python-nipy Provides: python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.3-1~lucid.nd1_all.deb Size: 277548 SHA256: e4a925dc3e2675271763c1b8a4248d73a2d38b238961a111ed182bd3c5d84020 SHA1: fec3ab250c45a1d74b28bb0a37cd7908d2224faa MD5sum: 0a4bee8815bdcc05d9c60d7739b81b9e 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: 0.3.3-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3640 Depends: libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.3-1~lucid.nd1_all.deb Size: 840644 SHA256: 465c043ca61af61479dbdd011fd350442d20a2a8b08212bf7c8adc709756dad3 SHA1: eba0a4d1ca01aab7eb6d0aed1161df8d86c6ed2d MD5sum: a283b2cea992bd74f4c8017b7b23b62d 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~nd10.04+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~nd10.04+1_all.deb Size: 3902374 SHA256: 15686f8aa80b599fa75dbe95c5d4c2a8de8662fe8d977d8c6ea01f7d4e423340 SHA1: 4ceef176ffd63c51745b681988a0f72dadac9eec MD5sum: 7a63610f687f24eb1b9ae18379479a44 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6956 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~nd10.04+1_all.deb Size: 5222070 SHA256: 3bf84612b8e4d5116c2fbbba5cdc4062430e05a7d158efc1bd3d7951b301636e SHA1: a0361ed611a594da8b560ba754ae3a2f4ce3d09a MD5sum: 223089327f79706718b3e0f9fcc68fb7 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-openmeeg Source: openmeeg Version: 2.0.0.dfsg-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 560 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, 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-2~lucid.nd1_i386.deb Size: 148704 SHA256: c8a75bb8c80b5a2ded29980a7a8c0811ee9479d4269fc7f63876511a54df3833 SHA1: d66632405a838295ecd9ce0cd99fd7cfd4cb80d2 MD5sum: a6075cfdac7e0f8fd364232abec716d6 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~nd10.04+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 Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.34+svn1146-1~nd10.04+1_all.deb Size: 206496 SHA256: 462c4b9f7334746cdfdbde91980cd67ae4c8efd5f7f35337f0890c5b20807099 SHA1: e01bb908ecc4ebc62dc3350f9e79704e9d37cbd1 MD5sum: c8ad32618657e5329114e7cafb4afbf9 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 Package: python-openpyxl Source: openpyxl Version: 1.5.6-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 476 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~nd10.04+1_all.deb Size: 67054 SHA256: 2e9e3a5b0573730f89da0c323879db4bf9f9009896fb5dd13b6a2fc1eb567a1b SHA1: a14b4a61db5f815a0b592eaf761aecf6ee49031b MD5sum: 3181aa977e83132e5cbc56df7976df72 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-pyepl Source: pyepl Version: 1.1.0-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1584 Depends: python (<< 2.7), python (>= 2.6), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~lucid.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.22), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0, libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.6-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0-3~lucid.nd1_i386.deb Size: 349202 SHA256: b3579b21da0f1c7b85c2c4ba49e63fc62c6555021415eb3b3b6729d9393c43a8 SHA1: 67a655fc650d9e241c1850a0e95f56f8a0d8e7a6 MD5sum: 18ea3054702878c7580600a21463f98e Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Python-Version: 2.6 Package: python-pyepl-common Source: pyepl Version: 1.1.0-3~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 852 Depends: python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0-3~lucid.nd1_all.deb Size: 817818 SHA256: 774bf05fe607359b31db378294947bcb52fcc9389f4401c967a172845766d9b3 SHA1: b50b0ce486acdaa088a42413d55ea9b1fbe99cb2 MD5sum: 4f523a841595f99e74aad775107bfbc7 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4356 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd10.04+1_all.deb Size: 972204 SHA256: c0a0710fc32967b41456e40df7770178d8442555aaa2037bab4a3f437d5da8f7 SHA1: d6b2bc7d9dc785cc5f9cef1c258ea48249921728 MD5sum: 4bf7272cae665691f702fa30fc9b9f79 Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-pynn Source: pynn Version: 0.7.0-1~pre1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1020 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.0-1~pre1~nd10.04+1_all.deb Size: 187334 SHA256: fa49550748a1c9071f1b4fb6b82b07a2aa7a20dc89d936e9bed78984cf034313 SHA1: f2af1366a8b41a86c9681735ee312ca551a6169f MD5sum: 6329589ccb640ae0152f5dea5091cddb Description: simulator-independent specification of neuronal network models PyNN allows to code for 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-pyoptical Source: pyoptical Version: 0.2-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~lucid.nd1_all.deb Size: 6938 SHA256: 19de2c227b5d42bf669a9f17fe2b57a673389f897f5cfc38c36c5561f4a8d688 SHA1: 3a8e1f8a435a5f8c8c73e694284096d4df474f02 MD5sum: 72a4517f5c3bc2eb5154b247fc4e12c2 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.6 Package: python-pypsignifit Source: psignifit Version: 3.0~beta.20111109.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1460 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.7), 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~nd10.04+1_i386.deb Size: 398980 SHA256: cef5196ef77972de17547ab860bfba4f1354215e131d79d8a9f2bfd0c8a50868 SHA1: 7429534ed4c376cae8182eef909941fcd4cc8a79 MD5sum: ee762ec715bfa21236ee823557142114 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-scikits-learn Source: scikit-learn Version: 0.10.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 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~nd10.04+1_all.deb Size: 19850 SHA256: 150edb896277f2ad8b61f502ca2851f28f8ce015c98a35e3eac80eef3658229c SHA1: 73e53dc89456535c0dbef9b313f376fecd2875b4 MD5sum: bcc291e544f2468c66cdaf78053f4b72 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-learn-doc Source: scikit-learn Version: 0.8.1.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14632 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-scikits-learn-doc_0.8.1.dfsg-1~nd10.04+1_all.deb Size: 9040926 SHA256: 8acadf6f7a85f611feea89d96100ba9df632a8bac94d52efa048230ee8ad37e7 SHA1: 1c1b1d49730569284ec509ffd6271fcae25bec4c MD5sum: 2bd88fc395825a19bbc20732fb3b1db9 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikits-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.8.1.dfsg-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1228 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.8.1.dfsg-1~nd10.04+1_i386.deb Size: 442182 SHA256: 6b7ea25c82f53712aee14aae279fe81a5b4a429b95efef59bac88ddf567fa05e SHA1: 287b438714b8bd3a152b496764dc578d60cf4256 MD5sum: 2afad4899eeaea9dc1259c227014dc83 Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.6 Package: python-simplegeneric Source: simplegeneric Version: 0.7-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python-support (>= 0.90.0) Provides: python2.6-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd10.04+1_all.deb Size: 9800 SHA256: 81ac573529d39f13c8353343c3014c7309c27e96741cf363fdc902e1571fba10 SHA1: 589f89fb49c626d87bd9563133e0c81bf7e25e42 MD5sum: 1c4a0dd7a403973cd769e56638661fb8 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2792 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.10.0-1~nd10.04+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 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.10.0-1~nd10.04+1_all.deb Size: 833486 SHA256: 63e570d2cdaf46c51542f0c7a793a27df6d164c336445581a5f4ab5f71338a81 SHA1: c8f6623546e961350cdc59e55f8e9d2801f3656b MD5sum: cd7e18afc6143bfcbbac0fa1bc602aac 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 Package: python-sklearn-doc Source: scikit-learn Version: 0.10.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22720 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~nd10.04+1_all.deb Size: 12277934 SHA256: cdd8fae47d62526f2d5a92abd48294c75be56a7f059926f4e0235e09c778a675 SHA1: 73aa3bb9eaf4d87345ace5057c07487e10e6ef42 MD5sum: 603d6f2a463baf298f7b782355adce9a 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1616 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.6-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~nd10.04+1_i386.deb Size: 589850 SHA256: 5bbf878bb734a296bb9819d2791cef22ac7b1b665cfdf695de8086c5fc771fe7 SHA1: 5ac046d32c63bf48a6cd084d7b1fe67a3fd7162d MD5sum: 1047ad3473c4424522e0815943bff7cd 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 Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd10.04+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~nd10.04+1_all.deb Size: 1260344 SHA256: ed112ff459ddd78efa87cb949cfbae5459a3412165fa8b4973e8a76ab824173f SHA1: 6511865f2ce2d04b056d4fa5f6ac05e5eb60b26f MD5sum: d083a49b7b98dab935fd7d603aa548af 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 484 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 219982 SHA256: 2df6907b665ab6eb3f090b193f4b10c7281a1309c257c3f17f5320a268590414 SHA1: 90739599e47df380b4e54a57ff6c816e59cc7b40 MD5sum: c744600ec5fa1c52ff455d35498ec7f3 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~nd10.04+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~nd10.04+1_all.deb Size: 21912 SHA256: 9e6b537975e009e6f51c1e4c1d8bda03e1abc6dfb5d882aa96570a5cb425c510 SHA1: 6ee05378e616f9095096c82e5e5d1d2a2f01bfeb MD5sum: 6cc286f98886dc14f34da8b8256ed7d9 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 Package: python-sympy Source: sympy Version: 0.6.7-1.1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9268 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-imaging, python-ctypes, ipython Homepage: http://code.google.com/p/sympy/ Priority: optional Section: python Filename: pool/main/s/sympy/python-sympy_0.6.7-1.1~nd10.04+1_all.deb Size: 1696380 SHA256: 998b38bfe45696bbeced69358a5620c9dde141bdd5be2640797b384bff6ddd2f SHA1: 53543ef42b225f2b190593f7df8a5b869933069a MD5sum: 68e7f81588ef209c34224974fd3f1c63 Description: Computer Algebra System (CAS) in Python SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. Package: python-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd10.04+1 Architecture: i386 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 2096 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd10.04+1_i386.deb Size: 335300 SHA256: 08ab44b92b97d629eca5fd8319944870e8a76b58c9056b9416bcd3d16fc1e36b SHA1: 4ef19eeab68c2d80d9f01a58e05f6d8050f5feed MD5sum: b93a8deca74893aba036491e24e25a26 Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python-tz Version: 2011h-0.1~nd10.04+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~nd10.04+1_all.deb Size: 46938 SHA256: 02f842ad03c8d36d092a8d2c7b28223c6074e9e8ebcf9a9a55671e85c8c21d18 SHA1: 0739fa38e0c9d3083bd725f0dcd2986f8e0130b0 MD5sum: ba590dc44e82add71268c53c4c947101 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: sigviewer Version: 0.5.1+svn556-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 984 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-1~nd10.04+1_i386.deb Size: 427686 SHA256: 8a1ac62a89dd24bb5ab8fb635c62df00a0086d3c55247f979b32f5ca1d04bcdf SHA1: 539ef609dee6a7cd26f333501406325b09a9f0b3 MD5sum: a315f24c338f8e8cde1f1b672dac0dad 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: 8.4290~dfsg.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22192 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4290~dfsg.1-1~nd10.04+1_all.deb Size: 10547194 SHA256: f18f23f0abe10bf6c13f61e4d60384c321bc963a4d0efbfdce8ee47f9278bfe3 SHA1: 894b6211bcf7b67314bb20b3c873d8298c3dbe97 MD5sum: 7baf99d5e7146364423c4771dd34c50f 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: 8.4290~dfsg.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73084 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4290~dfsg.1-1~nd10.04+1_all.deb Size: 52167554 SHA256: 79e3d1ad60fd2d0811fce23d4246f59db3524cf201f4c3e7fed5eeb8c47d54bf SHA1: 513ea73f022386fad61ac34f53e03ee0684cecd3 MD5sum: a52c7f39dae418add0cac9caaebce2de 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: 8.4290~dfsg.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9380 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4290~dfsg.1-1~nd10.04+1_all.deb Size: 8648788 SHA256: f8148c6b19e097a636accf7b96c3172b678534a23cc42379d1b0be34f874313c SHA1: 42cb1e41616be497c7e245b29417faa7bc9d39fd MD5sum: a168cbb12493d9d044647dc430c07751 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~nd10.04+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~nd10.04+1_all.deb Size: 28604 SHA256: 4d251a4678e2a4c7ec88672af589758ced935da77cf6244eb4b618413619e1b5 SHA1: 05a90c55b61b9aa66dd4ce6705ba7bf6056d4722 MD5sum: 7b649a9c33487822262d41f8e69a33c1 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 Package: stimfit Version: 0.10.18-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2000 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 751562 SHA256: 9e4513baa880769217436f25ca22267d44abbfe1e1730e7eaf411a44d429610a SHA1: eeee4230f7016a05ff7b3d57602cd9c6b36f9186 MD5sum: c131e49aac8b3ea0c3e50a305e6d4ad9 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13116 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~nd10.04+1_i386.deb Size: 5030734 SHA256: fe5250d6531493de4a4f83d596c7fbeeb2c3b31c81fcad246fb8778eca98565f SHA1: 56bd7e5ce258e8d5cf849aef4ea672eb5d96cbcb MD5sum: 48ab6e9b1198cb263e490ebb89bff04d 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: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: voxbo Version: 1.8.5~svn1246-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9868 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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~nd10.04+1_i386.deb Size: 3702056 SHA256: 584b21757af4af75c4c2535f319380a36eb1fab0edb368f52a3d3b9008b13ac7 SHA1: b02308e75f4f8c7e54bbee700838eac3820191f1 MD5sum: b032b8a251a1ac33a460613832948216 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.