Package: ants Version: 1.9.2+svn680.dfsg-2~nd10.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38292 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_amd64.deb Size: 11474348 SHA256: 4ea6fd3fe8f6bed09c78c0525a112caa34fa935cb809931caee206c28d2e655f SHA1: cacda9d987615458bc20585b2e4d305a3f39fba4 MD5sum: ac897711d72abaa94b1ac9cf95ec44b0 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: amd64 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_amd64.deb Size: 13916 SHA256: e74dc845f13dd613bf14f700d8ffc17c642ae0a43ea9ab3b97b6f86bfc9978e9 SHA1: 38a6dd1bc1b93822e23a8b1a1df1f9ae1c7e3b57 MD5sum: b61443a4e6b3adea1eae3628af4c4c57 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19616 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_amd64.deb Size: 7560710 SHA256: f3ef45962d9680c785f9bbdd91b82647c3267c4b36c4157f10c8d44a0e89fabc SHA1: aae26ec89bc9c001a4aa0e03891121afca1fc59a MD5sum: 0d8591e6d5dd1675c685ef47bd9d174e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 288 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_amd64.deb Size: 66564 SHA256: daca64e9765b94e07e8ad4f892c780625beeee0169405e90125296c74d754f89 SHA1: bc9eded034f99e81a494bc1714781257c3e9fe1e MD5sum: b15a9664e770d818f73f472e9b9b4191 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10068 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_amd64.deb Size: 3520450 SHA256: 3ebedfaffd240a3a440d67e93dcde63d3a4b9948e8bd5be8f7cede88d9d15578 SHA1: 5e74ab6911358fe5b349bbf10affcb7fccf26b4e MD5sum: 4ba4b9726d6086a1371a4d790b0db63d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3644 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_amd64.deb Size: 1451964 SHA256: f25aaf1261984942209973fbb16cdd49ca6f5884739ba6eaf8ab1056b68651f7 SHA1: 89799a10442395a27a055f8c561076abfa25da13 MD5sum: a97fd541deabe74e3f8017c9ab7b7470 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1180 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_amd64.deb Size: 247114 SHA256: 41f492c8b84ac0d542db6896d857e8d75c68a860f8d6dadb9f6ac67a45ba648b SHA1: 1ac200ed9a63d3c6f2f2dded21689e1907a141c9 MD5sum: 94ad6f03bb75747b118aff5c9586a114 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3684 Depends: python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd10.04+1_amd64.deb Size: 866936 SHA256: aa00f08c2a1fa909529d5d46f8b3cc31c73c1a593565fb445c0dbc7a16568247 SHA1: b9c103f6398143c11c6d020f5a5534f70fc4f104 MD5sum: d81d5e6398e53a8c67d5aa976f659b45 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5324 Depends: python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.3), 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_amd64.deb Size: 1713010 SHA256: cc5b8c1a0b8bd1a50a76d4bc87872b8dd790b2a8baefbb23dc3b0eab1138bf53 SHA1: 36a3184c96b97382b9d883a9736e52a644c764ef MD5sum: 72cc71be36199bb7768913e8be390681 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 76 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_amd64.deb Size: 35124 SHA256: e20b248defbd86b6f40036137685b9663516faeb2be494dde7ed650b6b4825c9 SHA1: 6ee18858ed810d2246bced1588a853c1d83f90c8 MD5sum: cc38c8ed53c58e371270e93cfe9fe69e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 484 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_amd64.deb Size: 160054 SHA256: 92968666074d73a688596096336fc58b0393910da6e3c51b1ce00c0ca48c5ad1 SHA1: 1b619e4d17cddec463bc275754d4c3efc975daa6 MD5sum: 225ea9e4b0dae26653e51fc0155c8ed5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3680 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_amd64.deb Size: 1630042 SHA256: 1d8d3470fb609c1bfaac12289191e9b0b8dcca2b41ee8557c25c1aac5390933a SHA1: c7340e9aa481fd0cab993bc8675afda6eed9186b MD5sum: ec8ecba333ffd319e459fd46666075eb 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 21180 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_amd64.deb Size: 6356496 SHA256: 35973b498894c79dd16f35cbdf997056a7c08833f0109a9740edf75cc11e861c SHA1: fd4987458ea6e33fde805f0ff1548a914265a614 MD5sum: cb10d3f342ffde8a36dc706297c8b8ac 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5) Provides: libeatmydata Homepage: https://launchpad.net/libeatmydata Priority: optional Section: utils Filename: pool/main/libe/libeatmydata/eatmydata_26-2~nd10.04+1_amd64.deb Size: 8236 SHA256: 7bb4b75f2f4b707b3e5dc2404d901f7a1112d653e6be16c475ebf5b47ae9ee01 SHA1: e5ffd4ded6a243d280fd2547e6aca7eb8afb0f31 MD5sum: c8293722fedd06683f33e7d3c9f67879 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: amd64 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_amd64.deb Size: 2544 SHA256: a8d160be5b9b7a290a72483e4c5a1ac8f207aa9d871f30bfbab30c859ee9c3d8 SHA1: 116b5bbdd77e0064b647a3983c966d3909190c19 MD5sum: 09054c87fd1e121fc3c834483158ed68 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4116 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_amd64.deb Size: 1524560 SHA256: 768c1e96d21dc00a7d407ff3dc3ea530690c883056a7ea077ffc9c5c40a70382 SHA1: 1a4efd707c933ced1c56927c193d1f7ff7c79e40 MD5sum: 3942062f9cd4bb4d570e7e86167bb0dc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 116 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_amd64.deb Size: 39108 SHA256: dd0ab16263cd8c5b9ae17ffd4fefe3a6307577e1b72d612a205a8858397766fe SHA1: 253239c2ee92819e7911d00e23521b41c8b32f5d MD5sum: 7742bae901530c6e59c1503d5ceb6937 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: amd64 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_amd64.deb Size: 29244 SHA256: 46bf711ca88f18e5ad2d2e175bb3cec6925c901aeb45eca7243a84c2820921d1 SHA1: 76d719b5e81cdd6aeba7fafc4762209f1e9a7daa MD5sum: 939e433013601359b181258a85041993 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 400 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_amd64.deb Size: 122802 SHA256: e16b3cd78f55a929a168399e8d6165f84f4f1e7b97e18e58e59dc4a4c5b132db SHA1: 2afc3b853d9c970460be0e775901403aeb9fb5b0 MD5sum: 9b1f53e877aa3aacda227e580d665f66 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: amd64 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_amd64.deb Size: 8928 SHA256: 7463484391a5138bec207ee24de046719b752fad024bf132842f27c1354215f7 SHA1: ba4100e2adbfdc8f3a339b425928884001b53da7 MD5sum: 9e9d86876d407561b43bddfccf4748f2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8544 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_amd64.deb Size: 3687612 SHA256: 10067727020df357efcd40d34f1f34359fe7bb2bc0fab160bcd2973d50a12cac SHA1: d74ad9fbff5711341e6ba1ce23fb48ff205758f1 MD5sum: 96bcef03500c35c33d6451d26d360318 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: amd64 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_amd64.deb Size: 21664 SHA256: 4718a0087359f1c3e0257324c87e4f3fe5910ba0874ba1b812497c123b1f9356 SHA1: 8caaca4f530c37608b5e0a6500e14bdcc67234ff MD5sum: d9323ce887c669b14c78753e98063eb6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1608 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_amd64.deb Size: 389512 SHA256: 88599c96ed3ca3f3f97a307a2d4b370ec2d610f606c64bfab15f953872eb7558 SHA1: ef183ffbebe53629f2115d5a4b1cebc6fe1877a4 MD5sum: 76d2303c5675b789b29a17bee73de183 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 892 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_amd64.deb Size: 313398 SHA256: ce2d8fec6f56aa22ba3b7d00acec2cedcf733dae69f45ec09fe0ee3c4c49cbb0 SHA1: bbfef3bd15a9c7a2149950b82c9621dfb76b0087 MD5sum: 4b6e722de9ed9bad9f37bec050af12ca 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 220 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_amd64.deb Size: 57574 SHA256: d55d8acedd41b18886c891e8149311737a5f4d6abadb99782f45779f7eded4d4 SHA1: 7a3dd8aa38cfc8a282c4934a41471e58d794fec8 MD5sum: 633ab9cb07f8479d27c14f955d6c8451 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: amd64 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_amd64.deb Size: 17402 SHA256: 2205626bacdb7037519e9295f67209d895791a1e95c68256a611bc60afd08cbd SHA1: fc11314770d31afe0d43d478443ba387f868d9da MD5sum: f2600a9832a5b4767ffc4212d0e045ec 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 96 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_amd64.deb Size: 38626 SHA256: aa214f306757a599c9d3ccde29f381fea2f9a5cd8d5f25e9d122b82000445959 SHA1: 9a927da4ea390d8ad5596d4880d60df7e41a401d MD5sum: 906089cb0b0f0ce5819aeadf8d6f8e55 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: amd64 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_amd64.deb Size: 6566 SHA256: 68b091db0e724f2f774283f5fde21271e86a111a62e1dff491e3274aba0bb4a0 SHA1: 45086eaa80e4e395bc70e56164ec61fba3051b90 MD5sum: 7c0b0b5090b7544ffdf01093f1ca11e3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.2.5) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.1-2~nd10.04+1_amd64.deb Size: 6442 SHA256: c9811d98a1fe054affcc312ac12377c5f7a64e190d67aac63dd2345bd0daafc3 SHA1: 60279db0a8bad4e7382d5488375546f627ffd96e MD5sum: 66260a43d15253715b3f9f6336f3c75f 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: amd64 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_amd64.deb Size: 44312 SHA256: f24a2e646b986777ae5855911e9d297381d5714e0a110672befcb02b54b73dc9 SHA1: 4dc87cb0f57016758d510d55ddb32a0d4f87fdf9 MD5sum: 4fb100531a558425c6fe7d40cebe7eae 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 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_amd64.deb Size: 32932 SHA256: db96026d49cfb4d0b8215bd30799036d684d88d5b598485faa85bbcaed80adcf SHA1: 92ebd866059f5115b1406166acfcc6d5317bb460 MD5sum: 12273f17c0eeb51a6dae1135ab3f6b91 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 144 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_amd64.deb Size: 60856 SHA256: b42c4006da00be78ece07bbc4d085988d7ea2c262b045ed7541523703f32f081 SHA1: 642b722f0977439ac141ac82577a445b8cd7310a MD5sum: 07ce448df230d874cc2de4d21ac20e07 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd10.04+1_amd64.deb Size: 509898 SHA256: e17f8905e5109f284bbf39f21a55fb4948c7fc7530f45e009ed6354d6602b76f SHA1: c8e1835f2e4512d93727be8ae55a5e49d1d2b63a MD5sum: a131050148d03dd67db72752301cabda 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.4), 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_amd64.deb Size: 26132 SHA256: 1528f9ffda390cbb8024a98f160b70f3494e3f40ed8c8bca56562b885f2a817c SHA1: a6df8bec0e84ce24d6349063a7db59b3a296b86c MD5sum: 4119f5f8313e3cf2797fffc531e05c74 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 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_amd64.deb Size: 18448 SHA256: bb8243edfbc574f9cabf9dd19951330ea2adc3308e31c803e167da5e267f9a66 SHA1: f49982c5ccca5a1712425097c3efae0a5220e29d MD5sum: ae70c6592b2c15171c9a5392f14bcf25 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 96 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_amd64.deb Size: 28088 SHA256: af489dd2051301ab38be88029e52f6a080e980927a51ab29a412a8760a55c33b SHA1: 87beb74084bd9f14225dc110bac6b3d5886b595f MD5sum: e4ca06b3f0855f59d22ebfe81ac1e1d1 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: amd64 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_amd64.deb Size: 18530 SHA256: 7910d2fb7fa40dc3fa0cc04f24ecf77128201f51f36e94e9e556745d84684bc2 SHA1: e016e5819e17cf88ca7b6bc6ef4b7d7deab0bcee MD5sum: d81fa92746a41861d3d7cfd99b07b0fa 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 336 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_amd64.deb Size: 106316 SHA256: 7572dc2b086111452b82c09a27e8d5771863ad2d5caa2db9bd0f31972b4396bb SHA1: 73855cf6b3244466b05969a60c55041cefb5e562 MD5sum: ff0c202c3a2e689d4b89ee2abe86dfc6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4100 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_amd64.deb Size: 1117258 SHA256: c952188577033d63b9ac1f819bb27b67fc715580d43aa3d5d272ab466649b905 SHA1: 88ab8bf3b5b338b8359548f306d75dd57813cd41 MD5sum: 1dc2aca738ef569f8e4b2dcc12e7fb50 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 256 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_amd64.deb Size: 64998 SHA256: 45f0db22721e17782f2d36f92ffd6b9ffd20a0f9613d56f0c2aaa846c4ca343f SHA1: 195febb32e6113c88617a7d78e8694e4881f7341 MD5sum: ae42e1bb953ebbe14e59986566635243 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: amd64 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_amd64.deb Size: 57594 SHA256: f8b85858f70219645839d9e3109129208ad79a9a1546eb1a1e7f875845109718 SHA1: 00e59c2b2422da35b1a8c8e35e9714285deb93c0 MD5sum: 0ed5c2dde1ffd75079078e4c82424eac 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 444 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.6_1.6.0-2~nd10.04+1_amd64.deb Size: 120638 SHA256: dcf1cd492a5a890188ef5bc779381ebe7645a286c5637217d5304bfeded38354 SHA1: d0b13e63b9cdc4ca5340bf0c398893c8a41c3320 MD5sum: dd7e52d1b00fc714a550e25d20df888e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1492 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_amd64.deb Size: 238400 SHA256: 6ba6a7c838bb1e5d5cc6c8a7c704e0e348dba78bac6acd8d52c04efefe009b92 SHA1: d5209b39d332391546f2ec351162bda302e55808 MD5sum: ccf3f54ba76eac96d1e8184d37fcbf1b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 392 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd10.04+1_amd64.deb Size: 106980 SHA256: b0a7fc23cbb9b87decdac953992120ed6ccb086e65a13c3e392523e70ce45179 SHA1: d1f2d26b7c2b6a097102e98b228a8f8767da8c77 MD5sum: 5780d2f38d30d7f25a6da990e82b2cbd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 512 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_amd64.deb Size: 96674 SHA256: 9c19b9cd3623dd650866b51f90853dcf61aebfb31224f6226e61c7c0e4622420 SHA1: 83752ed8303814ba83f8aa8677ca68a29f901e54 MD5sum: ee7e048bda09f2414c7d4ccd5b3d5047 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 9818 SHA256: 9a8b2fbc74da10a0629f163436dde03aba8b391a746ace1c33ff1b544dbe53fa SHA1: 414c809c0418e6c90cdcb5034c74946536732ffc MD5sum: 44fce493b27781ba37d7804535c98bc7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 76 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_amd64.deb Size: 12078 SHA256: 5f828227032af2d7eaeb1a0ef72534041ae16fcce7e7b677af9aa1cca08368d3 SHA1: 117b3c3eb5656b3ce88711a1b22328778747257e MD5sum: 612b80054b6c9380c23709c0de492de1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 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_amd64.deb Size: 19220 SHA256: 609cf5ea2504f1a8997340bca3e414048b0045edbe8a5468d4953248853bec19 SHA1: bad8fde85a922cbdaa14f97348a209ef2dfe9586 MD5sum: 4f9af0e22f2dfd3069e9352553ec9d87 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 624 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_amd64.deb Size: 171290 SHA256: 113ba42ad361ebf6f7b7b2c429c02857738472be1f23bbcb2232b18cfc334d74 SHA1: 0d49b66ca760523e35331ceafa85d046a0d8d5d3 MD5sum: 9823b6daab84532d63e7dd88020e1a5a 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 336 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_amd64.deb Size: 123024 SHA256: ba53d9dd6ebe7abd552f39127d2bc06896d367be47525ec0e29867fc833b54b0 SHA1: 33b02302b67518c8136e29fb7a52c677f78514ff MD5sum: 010aa718f728757323244a44e422706c 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 21020 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~lucid.nd1_amd64.deb Size: 4200000 SHA256: 4d0d631eaa5d7de777cd874a0eecc53b9ec6eaaad7780e6edd1920ca0ae9f423 SHA1: 95586553e269981ec43c4d5d8023425ce3a75209 MD5sum: 0f18c7171b948f54416b1a66f594a64e 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: amd64 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_amd64.deb Size: 43856 SHA256: b0f360865c523d9912f14db82537e8202c02a4b64387b5e14f30231ce05f242d SHA1: 232d51205a9618c0020027427b543e87dfb1eeea MD5sum: f4b6ec1254a767e780bf41c692522849 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 960 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_amd64.deb Size: 252508 SHA256: 9b38eae709217b949c4fb23666f10060d501153b4bd3e46fa79a8bb577a9c6a8 SHA1: dd48a79df4a904587ae6609d51b4761d8bc9f648 MD5sum: 94b5eb327f14882834730ceb33299fe0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd10.04+1_amd64.deb Size: 7778 SHA256: b9c4f0947e4a53e98e3b960809846ba0267219b4624d85db48a49e8458a25a8c SHA1: 66e59fb7c5c5f71430812645615bf25319e52b12 MD5sum: b675a20e85999faed8835bf3a6dc1f2d 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: amd64 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_amd64.deb Size: 12558 SHA256: 7df5d32ccd5e6b6781d8ff20a028a39cba67e82fa313bccadaa2a82de7fac231 SHA1: 84df96369f5b0a7bc98a499e3a926a31a2586869 MD5sum: 34b4b65025ffda9a74163bdf30ee002e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 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_amd64.deb Size: 31372 SHA256: 685395698be963b2343de91335b3ddf9542e0ebe8300bd12d9477f1849d8799b SHA1: dd54f2bccdf36d3bf4d2eeebbf1c77539f224cfe MD5sum: 903940552d41fcabc321a2c6cd6838ab 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 104 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_amd64.deb Size: 30968 SHA256: 8b081287b9cf9112656787073b4982c71f3ef2a1401b546fae2a4ed9bc55edfb SHA1: e68e18e9f896919ceb8908e3326aa57ad21d9233 MD5sum: 4953e5fa4d47de48454be7277470233c 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: amd64 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_amd64.deb Size: 28204 SHA256: 953855956a95ce124cc864adb37306e0608321cb4cf6eef5704f6d043e70db4f SHA1: b64dd54d8aedda6a1d03f291842a843ea065607e MD5sum: 534d104b9b4a6fa1433e9ae34d98eff0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 344 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_amd64.deb Size: 120204 SHA256: 464671f5c09dc8a7e137ecfaf788f173fa84bcaa6d4290abc12fca1af8b7ef2a SHA1: fb0ea223a6243b609fa0cd3135664037ca55f5f8 MD5sum: 255992a55d4f12a17d5211c264593817 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 132 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_amd64.deb Size: 46550 SHA256: f72d0f8057bc018f8e696bd38c8eb42477bf5da34a2e40fb55cf15dc0f339b4c SHA1: d47a59cf387be789999cbd10fda712704f5cee47 MD5sum: 7c92282c7ebd15008a7019183aecf58f 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: lipsia Version: 1.6.0-4~lucid.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 3940 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_amd64.deb Size: 1350678 SHA256: e58b7a05472046790c2f66fc0f171f874baeee44138732e2afd4660f7a6e29ce SHA1: 2dcd43247f3fb012a68ea1a66d4d324608ceba1a MD5sum: f8464286082303e2b11f90212c5321bc 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 6980 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_amd64.deb Size: 2453670 SHA256: 40cc6bc31ecb80983c8f89860d92a63c083f18450efe48242565ed7d157bc9ec SHA1: c3c5a30d5978224bba135229ed48cf0cfa2cb8c5 MD5sum: 88ca85cfc6dcd978837f1d025b8851a8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2180 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_amd64.deb Size: 771400 SHA256: 804bfeaa6c1975daabee08da80ade758b3a7dc3714dd3162bdd46db81801eae4 SHA1: d7ba39eb6a317bdca196c817a7b9adb1f4d266c4 MD5sum: 75282441c98c04e2d814b1ddca1bf9ec 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15636 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.29.3), libc6 (>= 2.2.5), 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_amd64.deb Size: 4905564 SHA256: c2160870b4e71d1a976495743c2a092c514460df31693b4b31456d5992f660e5 SHA1: be42eabd3c6d7bb1501189aed23ad25eae8779f6 MD5sum: 724c60ef8624433198f77c28be88a6d6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7252 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_amd64.deb Size: 2298422 SHA256: bdb59c991ddf2bef50a013411ef452f7d1ea4d5739beb5f05a19fd0690d34245 SHA1: c9b6128d9ac6ed4d0a69f2574583156c9b52ea90 MD5sum: a6df4ee9c04a8afcf6a15566046ae107 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: amd64 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_amd64.deb Size: 62296 SHA256: 1355d318a693371abf40cf3a424a4e9a2040e5ef66c7993f0597bc3506d4991b SHA1: dfcc4f30646e93220e188ad57c8831b397e15e23 MD5sum: e611321eba41d61af7443e9c1c9cc3db 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 684 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_amd64.deb Size: 451012 SHA256: dd5b0b3d1c7334df79c638a5675c264e986633d6ae70396aadb774b9a1be1b61 SHA1: e6598a79689f67732c81d4ee35c952a673bdf8e4 MD5sum: bb92152f6fb3165f1bfc5fefc3ab2164 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: amd64 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_amd64.deb Size: 18446 SHA256: 96b99b5a30cac38724b1211cc38adfb022ecddc36c643dc9d7eabf0dd883be13 SHA1: 8f617444c3699663a9c7b93bb369c348e2c77dda MD5sum: de71244d670c762253b573490c52e71a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 336 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_amd64.deb Size: 133990 SHA256: ccb2b3670b177318186cf904de1cebf93757bd40b58ecb8bff433e45981ea924 SHA1: c4b3a083337a9110e080ac889bdeea582999df0d MD5sum: 00c76e30e00d2a47ebaba177a57f3e31 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2416 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.3), freeglut3, libasound2 (>> 1.0.22), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, 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_amd64.deb Size: 775136 SHA256: 3ec06589dba164ee3e4aec24ad3c379d75132cee7d5f43e30d8b7adcea9d5c76 SHA1: 9aa642c89fb71d09bc3270ebb4cd2012a4eb3cd1 MD5sum: 19e972d69844c69dff97f9563e1a25f1 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 4136 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_amd64.deb Size: 1573324 SHA256: 657bd81a759b23fe5890886d4752f8c7d446a4abccd8e8f3afd599988ed28099 SHA1: 4e538aeab5bbb3d132027c534ccf057ec2fd4650 MD5sum: 674745b2fece68298da5f034ff8fc191 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 600 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_amd64.deb Size: 162662 SHA256: fce9ef3c245aceea7d087c0bd02346b105ecfea7dfc9501076d3d46841f38916 SHA1: cbf5ec9b4f3dac5718b946b6631eb5980a49da6d MD5sum: f13cd918f20ef00389618b13b43585f1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2456 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_amd64.deb Size: 767678 SHA256: e9031a6d953af2d5037fc24e110b3e27f6b0a061e488e4fb377cf58925fb6c33 SHA1: ee85689561670a2f6b6281608858c7287a184f04 MD5sum: c66f53cc0469e9cb185a8e566e2ac7a2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 212 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) 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_amd64.deb Size: 62752 SHA256: d1761a7cd931cf1717d4aed09bb31cb245b673a6555dd35459b3d364e6753b38 SHA1: b90247844fca3f3b5094df6b41408abcf53cf7f7 MD5sum: 61458cc3273df6c0a604d1114f26d9a6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 220 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_amd64.deb Size: 52390 SHA256: a649434f323cce2aaea3865b2578af84ee50f8fdeb12be788228ef28a01f76ce SHA1: a7701d53c8e49228e443b7d8b662df09d62ca151 MD5sum: 50f8cf37e10ecdda97dba985cf906690 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: 1.3.0-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1692 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.0-2~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_1.3.0-2~nd10.04+1_all.deb Size: 314088 SHA256: 8756452a9b4dad5d88a90dd1bdded2d45e94efb676a981a5b5b2e78c439e195e SHA1: 92753e2d567e57225c93e50bf25d1a71cfff2837 MD5sum: b21350e8d23a3bd93dd61feb9ee153f3 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: 1.3.0-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5324 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_1.3.0-2~nd10.04+1_all.deb Size: 1654274 SHA256: 05564b254affcb1ba38b965410ffeb1872f720ac491272a7a245ab2b3fb39f0e SHA1: f5bd6350f88120ee817362a44fd7f97f2e483009 MD5sum: c41eb2a186ad896542315fa890d6e811 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: 1.3.0-2~nd10.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 160 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_1.3.0-2~nd10.04+1_amd64.deb Size: 55096 SHA256: 9184f3697316a8989b3ece41dd12b63552ab3e72c47ec3cf359438fe4c63501d SHA1: 2edb46ddbfe881fefd85dd3061a1c0a6819fc168 MD5sum: eef9b9c0066dc304c9ac540e41656863 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 592 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_amd64.deb Size: 222906 SHA256: 6d05dfb21abec13350f1f99a7d410005eed032cd4e73ad6d460d2dacd5a8e7a9 SHA1: 63978e226b62bd0b8169f5fc610ce76d8f83b2ab MD5sum: 62c6d38c413cf921b0970a860e1483f3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 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_amd64.deb Size: 33718 SHA256: 42797a63d0de189e7a6429b8fc117d817b249fa642fdc7f89cb81eaa84c65cbf SHA1: c9e98cba5551a77826c68de78c1439ac7e338f8a MD5sum: e9596f03d9f0d3ecbbe251428d0f561d 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: 0.5.4-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 228 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_0.5.4-1~nd10.04+1_all.deb Size: 44430 SHA256: fc515b462f68ead33426f2dca6bfc3c6d121c8793f1c53d8d64d5cef1258a526 SHA1: f853078c8d4962d79662ed6a027ed0cad1386b15 MD5sum: bea7b2d8a85c18c18c6ad8ec00845146 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: amd64 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_amd64.deb Size: 7606 SHA256: 0829f6b39b71a98b7ec5aafb97df942099e53786220c863c61ec43fde70109d7 SHA1: 4e8fc49364c84f3e22066858f5cb43947c1a5f10 MD5sum: 4ba71f768c2600517bd6310e6e9d8ed8 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 312 Depends: libc6 (>= 2.3.4), 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_amd64.deb Size: 70842 SHA256: 973a999bedf71bf13119caaef348bdf5156967d0a792c02d8171d6f691fa4397 SHA1: 551d017b25a89cc23feafca4e43a941a513ad880 MD5sum: f2cbf5b76110123e0b15aaaac0b94e1d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1164 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_amd64.deb Size: 377582 SHA256: 4aee966694b5096097ff9db7e683f09e5e3c13548560eeffc2659f634314b372 SHA1: 37e47b259b2697f7d75c5886e5856cba96a8e218 MD5sum: e9acbe30cf2a9fc98751da7694e65c7e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2068 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_amd64.deb Size: 563164 SHA256: 41234cd3273a826528e82728a448c9c644c647bed6990fb19ea086673f0608e6 SHA1: f6cb6a279edcad2d40fcb991d8804314f5200d86 MD5sum: 296ce3cb8771617774c4ac87d50dc8b5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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_amd64.deb Size: 35532 SHA256: ddf2b4c14fd383bb0e054acb0d2a31e4f26d072321db2e18348a16680ef27edc SHA1: ffb6c5ecde4dc6f75762754dcb790f83f427b1e7 MD5sum: 1696d4b298147d4b4785cfe199a4d83f 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-mvpa-snapshot Source: pymvpa-snapshot Version: 0.6.0~rc4-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4596 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa-snapshot-lib (>= 0.6.0~rc4-1~nd10.04+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa-doc, python-scikits-learn Conflicts: python-mvpa Provides: python2.6-mvpa-snapshot Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot_0.6.0~rc4-1~nd10.04+1_all.deb Size: 2314484 SHA256: f843f3bb7c14f2c44ad652d42f0f4c42ed245b6d380a896e817278918aeabd5c SHA1: f9cae5f7c2ad445daa6ea2e5b871feaee46b5c63 MD5sum: 90c052b49d6d129456bf938c87f918fe Description: multivariate pattern analysis with Python PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, 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 a development snapshot. The latest released version is provided by the python-mvpa package. Python-Version: 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.6.0~rc4-1~nd10.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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 Conflicts: python-mvpa-lib Provides: python2.6-mvpa-snapshot-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot-lib_0.6.0~rc4-1~nd10.04+1_amd64.deb Size: 44056 SHA256: 38c4495627468efe558497a53cc456d5d4096d09707fb7297fafd4cae1e282c0 SHA1: fdd9c7cb0b382d56f669fcb3cc7626cc9dd249fc MD5sum: ee820520c9d11f475acb6c69a33eb225 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. . 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-mvpa2 Source: pymvpa2 Version: 2.0.0~rc5-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4588 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0~rc5-1~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~rc5-1~nd10.04+1_all.deb Size: 2309416 SHA256: 0fe34cffb68dc5f050af8833604486f7aa3676c1699b61b5c62f45bfea8dc12b SHA1: a2ab36b96d3753c7839eb7ee425b75e2ee569278 MD5sum: 2070afbb5f6cd23f3003a8ab2c864eb0 Description: multivariate pattern analysis with Python PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, 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-lib Source: pymvpa2 Version: 2.0.0~rc5-1~nd10.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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 Conflicts: python-mvpa-lib 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~rc5-1~nd10.04+1_amd64.deb Size: 44450 SHA256: 2475861fd0da852eeeb35683c485246ebd873ea4b7f9aea467ed121ae75bcdd3 SHA1: cf544a17fcb50f4eacb09a651d462f8e7176a72e MD5sum: 500eb3237cc3cf4d6e311940a53172f1 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. . 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1136 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_amd64.deb Size: 291558 SHA256: 9c338d1003e25d7fc9a5f315dc0ac0a807ce08e42d1898205590e4a835a00171 SHA1: 35103183bacce50e1e57a302ddd4fc23c14b8b53 MD5sum: 45d9ab1d648e2986fb4c473af315ec6a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1432 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_amd64.deb Size: 542784 SHA256: 5319ce2dde29782415487341b8f0d768581767514ed444631c868e41869ac98c SHA1: 74437760655c7baa6593de795c374635afe36c47 MD5sum: aa2977d612382f33b8b234b9ef9cef75 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 600 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_amd64.deb Size: 157588 SHA256: 5d21094ca71038b88adacdff2df3805515f25627746e7e84d841de003ed14ef5 SHA1: 209bc128ce2ca80e74506bff570acb4d3e9cd5cc MD5sum: 03abf5e8ea6fe312c37d33b3a2b1fe55 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 1696 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_amd64.deb Size: 381458 SHA256: 4addcaafc82fe9d2405811a06fde30266fdf9fbf4c785353b56cbb6d7d1d59dc SHA1: e97c7a1c5e1e4ab1dccbe6ade4a221c85742fc9f MD5sum: ce299feeb3dec63353cb835e3e526e97 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1576 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_amd64.deb Size: 410828 SHA256: aa033b3f3d4df64389aae1a7b507af3e1f0503c128a5dd8fdb788f57fecbfb2e SHA1: 334ff9739f4d17f839a31b9be99b93a8bf9ff620 MD5sum: 2b67b8cf285c0c24d48710b5facd9cd7 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: 0.9.0.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.9.0.dfsg-1~nd10.04+1_all.deb Size: 17106 SHA256: d261e65888882f11f15982e4e12ef363c02f5255a0a867edc49206f388ed1dd2 SHA1: 24ae23139b18ee54c950c24eacca31a684f1e69d MD5sum: 4fbb4894857edb5f8bc3ea0d0bae4a1a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1408 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_amd64.deb Size: 528214 SHA256: a54dbbf486ff288ba9c4a70a3c47908abbf3c3e1ee5e0e29dc62c2d94b5bb2c9 SHA1: 6b062b7cb8e14ec13315b378683eb99873dac08d MD5sum: b2ee7b1f004915279efacb7f279c3376 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: 0.9.0.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2452 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.9.0.dfsg-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_0.9.0.dfsg-1~nd10.04+1_all.deb Size: 770544 SHA256: 3846ed4d6929c49e1a4e5c07078e572977efc40ce6faad3e980762ab9ce15bad SHA1: 15cbb90de2b3d2b1efc23541f408897cd926fbbe MD5sum: 7239e7b766edc71f87397a2f12434dbf 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: 0.9.0.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21572 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_0.9.0.dfsg-1~nd10.04+1_all.deb Size: 12841644 SHA256: da50bfb5dc1d726d0c1405dc46967537e09dc7a78a4abc8f3d9eca15db7730a2 SHA1: e1bec7eec941549e2cb2c0b5352967c5b6cffeab MD5sum: a98b441f23b0ba3d3e92b058141aa099 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: 0.9.0.dfsg-1~nd10.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1528 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_0.9.0.dfsg-1~nd10.04+1_amd64.deb Size: 562156 SHA256: 40afbc3e506a1c0abb9fff586be93975b37b7bccf05bd7324368a58360b4f012 SHA1: 62b7d66e0dbb394c060fc40f8835bcdf14c59596 MD5sum: 878e43cddcfe2ae774ecff30a48f7556 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 488 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_amd64.deb Size: 221592 SHA256: 858494a22f6b2b89979f7fdb78825b7cb6c958b0465cbe308d38400aa3f809b9 SHA1: 74c6fbdc699d1cb4987ea250da11b3834b9aafff MD5sum: 41b1e11b691b3b939213df5fffc4b913 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: amd64 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 2124 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_amd64.deb Size: 342472 SHA256: a12edd1070b3139da170d92ee2dd04534404f548eb12c2091b474059d6c25e5f SHA1: d8536482d321cc499608ca48a917335211490937 MD5sum: 0905df22a166e0f6b6c1b95bd90f8de9 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1040 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_amd64.deb Size: 436222 SHA256: a441cfa94ab355800ffa2776a6de3c42a51e1694c0f6a9fa07a39029510c10ad SHA1: 21cbd30360811a75619ab1709f0860c7afae0b8b MD5sum: cea7709962e97125a32be8c931506774 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2128 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_amd64.deb Size: 771908 SHA256: 6db5c7eb73cc68320992774727ec2eda169421e5ed92cb323dde7b78905f7c86 SHA1: 01742a5b30fbb621d860eec9c2ededab7d78077c MD5sum: c0d6084b01c3394a27d6b4215d612b72 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15256 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_amd64.deb Size: 5152540 SHA256: 6f7f38df756b992f1eede4e279d5a073cf7b05e6cdd82eef5cd4952b54b24103 SHA1: 6a69d88078ff9e6027565481f935a76695dca39a MD5sum: 3f90e617edd65216bcb0779918022c6e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10292 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_amd64.deb Size: 3755792 SHA256: 6416312fc85af42d3067f4dface068c3068cc41855b03f76134a4b1577077643 SHA1: d2e75c31cd22de17b695cad7d0b74fece55e9487 MD5sum: dd75772f73c088902dea4b14abac8064 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.