Package: aghermann Version: 0.5.1.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1640 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libfftw3-3, libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.16.0), libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.0.0), libitpp7, libpango1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.6) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_0.5.1.1-1~nd+1_i386.deb Size: 415438 SHA256: 64b4a16e3fe4e4fe31f2bb1eafa890fe71460b43fc59b92dfd5623e7e06f818c SHA1: 227cdcd6175a2a929fddc536b89e5e9ee784fa45 MD5sum: e1e033af7def90857542b9a40bc6fde2 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility, EEG power spectrum and power course visualization, and Process S simulation following Achermann et al, 1993. Package: ants Version: 1.9.2+svn680.dfsg-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 40147 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.20, libstdc++6 (>= 4.6) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-2~nd+1_i386.deb Size: 12782274 SHA256: 3eca44422719dea5262cf423457adbf99307c4cf604c1539e8c5bbdb488d35c0 SHA1: c9dc5d0103015eb7499d9c0719dea3ac4c5565f3 MD5sum: e6c4f5da6b45fd2c6e40a5fe84b3e4cd 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~sid.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~sid.nd1_all.deb Size: 132466 SHA256: f27127b8c1dc917c0286a9387f8fa457376ded10b07a5908485636c27a2a14ff SHA1: 696de58c79bec6fd3efa3cf7dbbeecaa18d1ea8e MD5sum: da7a5641d17921fad83cbb534f2ebb22 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~nd+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~nd+1_all.deb Size: 72956 SHA256: 7666bac3385b0b20640e015f8a83c4b553caf47a13f951f9b4f9c81dbbb74b76 SHA1: b565f24c8d243d0f1eb9aad3b5a2398ddbfab598 MD5sum: 12baf584e618512906617ea2a38972fb 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.0), 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~nd+1_i386.deb Size: 13554 SHA256: f801acf93d2f9c7738011dd546e6db94e5ea0e01b613b7a1923c1a2888a8ecfc SHA1: 71f68e919bd9ca0ab019fd7be20a802325865f64 MD5sum: fe2ae0d4ae6e4d53173c3905192cd904 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18536 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.6, 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~nd+1_i386.deb Size: 7448766 SHA256: cc0dd07e2e32e1555d9530d90411212a69a78e1460b0aac806158bb76004d7c8 SHA1: a11c718c8f8f9f0928b8a3533d7a5106938eeeea MD5sum: 837a1267e3253910ba881cc136969512 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 137 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~nd+1_i386.deb Size: 63578 SHA256: a1b7537de1aefbeab25d571bcac974ba9ff947f23bf54c6c786069b8b123ca02 SHA1: 38a354374bffa7541ccec3a3617c92fd935e5da5 MD5sum: d3c65a8e5cdf28dd482fe0a751e548f9 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: 2.1.1-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18036 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libcharls1, libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libmxml1, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), libtiff4, zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_2.1.1-2~nd+1_i386.deb Size: 5364972 SHA256: 7a40c90a854028cff5dbc79c84e62b5eb0e0cfb1e065e9caa652f3e635941248 SHA1: 087aa9ed0154c458a39d0d51895ac46118c02e8f MD5sum: 5c35c0b3dfd66e31432baafa457a0ae9 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: condor Version: 7.7.4-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 11705 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.7), libcgroup1 (>= 0.37~), libclassad2, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 1.95.8), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 2), libglobus-common0 (>= 14), libglobus-ftp-control1 (>= 4), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 5), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 8), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 9), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libpcre3 (>= 8.10), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), perl, adduser, libdate-manip-perl Recommends: dmtcp Priority: extra Section: science Filename: pool/main/c/condor/condor_7.7.4-2~nd+1_i386.deb Size: 4187874 SHA256: b855ff6ecd70aef8f0b837cf0794a51e7f3de7ef83bb6ed2f886921117220893 SHA1: e87c1c9e6317ea0e127f79eb11e4fd625119d269 MD5sum: e9d9f5e0e6532fc56661d83eec3b048f Description: workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . The Debian package uses Debconf to determine an appropriate initial configuration for a machine that shall join an existing Condor pool, and moreover, allows creating a "Personal" (single machine) Condor pool automatically. Package: condor-dbg Source: condor Version: 7.7.4-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 29911 Depends: neurodebian-popularity-contest, condor (= 7.7.4-2~nd+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.7.4-2~nd+1_i386.deb Size: 11360550 SHA256: 9caa6f16a18a3a34680e12651124ba544ab492003bcf45d383555bbef3380e21 SHA1: f39fb061e9d307ae442763613129a3ff07355a57 MD5sum: add30b8479a8cdf1c99ccedb6e8e235d Description: debugging symbols for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-dev Source: condor Version: 7.7.4-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1423 Depends: neurodebian-popularity-contest Priority: extra Section: devel Filename: pool/main/c/condor/condor-dev_7.7.4-2~nd+1_i386.deb Size: 384428 SHA256: 1fd643af5720c39669e6278d5a3fd522e8ade927004eee3a95bf2f4e1032a467 SHA1: 84c5b4ffff9e1d82318197f5aae40feea52c3d89 MD5sum: d37335be2da5b37f24a6423e139d1d8a Description: development files for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of Condor add-ons. Package: condor-doc Source: condor Version: 7.7.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5151 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.7.4-2~nd+1_all.deb Size: 1276116 SHA256: 34ca952313a50ddad3198bc3ebc2f526d0fad6b132e0aa225ab0d11ddbdc1d99 SHA1: 983710ec2889f92d0fe7a8bd5be2903bd3bdeea5 MD5sum: ae5a2e9addca12f818d25ae2e4052163 Description: documentation for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: connectomeviewer Version: 2.0.0-1~nd+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~nd+1_all.deb Size: 1354950 SHA256: 36960adc0c56e8798124efdf026ba51c4673cf464b69e9c7404285a9df42f12f SHA1: 3aa6c01a036ee4588d906f50a50469acb8ad46e0 MD5sum: 5034eba0d1532377993780f51a8a17fd Description: Interactive Analysis and Visualization for MR Connectomics The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics. . Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit. Package: coop-computing-tools Source: cctools Version: 3.4.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3575 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), libncurses5 (>= 5.5-5~), libopenmpi1.3, libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), libtinfo5, zlib1g (>= 1:1.1.4), python Suggests: coop-computing-tools-doc, condor, gridengine-client Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.4.0-1~nd+1_i386.deb Size: 1291156 SHA256: 53c58fd1f4f58235f6ed7eb45e4941d594ba2738c188bbbbae3a6f28c9938915 SHA1: 0b18abbb07a90665ceea083648276cb3ea8bf52e MD5sum: 5592e973719f9adbc6a6791891d854b3 Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.4.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 671 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.4.0-1~nd+1_i386.deb Size: 180308 SHA256: ba935f990d08f25d54ddf27e3702380201a278182172772ba709473d0c9a82b2 SHA1: 8f28c55137ab5c7ddeaec766f4e73382e7ec7bcc MD5sum: e2e8b38aae67af1e452920a0dc46ecdc Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2212 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.4.0-1~nd+1_all.deb Size: 301560 SHA256: ca659561b8f2db8153b5a6be0eb21ec462dff737fe300f9d0fdafc3fe87e6b33 SHA1: 9305d4fa12b752f10206bccef61f927917a89baa MD5sum: 671d5abcd18d24aae9db6fbbe588b65e 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4580 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3.6-6~) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd+1_i386.deb Size: 1117360 SHA256: 3294cdfa3975fccc7c036c7f682655415b097e72c912995137848e91e64a78f4 SHA1: f4cd5aaf276b9511d09d88326b9874d5c688180c MD5sum: ec697d214932e45fc788e7cc387f630c 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: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7672 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), cython (= 0.13-1~nd+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd+1_i386.deb Size: 2920060 SHA256: 2c4bc665bc543f0d9d7d675f37bf01376f7c725bb659c7bbb168bbfff1b52e64 SHA1: 6ac68b40d2d6858134a3559a7d567b1e59b894c1 MD5sum: b2621ac9fe5da867aed58d8dcb9aa69f Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.5, 2.6 Package: debruijn Version: 1.5-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfftw3-3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.5-1~nd+1_i386.deb Size: 36926 SHA256: fca5391d6b4d983071b8a9c78aab3c1b7489b73383c62e75c9d9c0392cec2855 SHA1: 9d01da0f50f222ba6409fb67cbb135a68eb4d3ab MD5sum: 721f75486541af8aca01ba3fa8eca9fa Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: dicomnifti Version: 2.29.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 522 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.6) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.29.1-1~nd+1_i386.deb Size: 170890 SHA256: 54b85d9b327587ba26fb63f3336fc83de3ea0eedb9fead604a1faaca2ccf4547 SHA1: 9f4d0b9da4c36eb3a468fb57719c98b7df0e2321 MD5sum: 9a0b6d9ca7896a8bab748e7249b65164 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3628 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_1.2.1-2~nd+1_i386.deb Size: 1564612 SHA256: a568c2a11a35611efd5ef037b5bef5f511c782bb7bb2183beac12ded1599d7b0 SHA1: 964b7bf9cfdd3750fa1c342fd25573d473bd51f3 MD5sum: 66a88bfdaff3f533d2552db7cc2463eb 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21148 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~nd+1_i386.deb Size: 7438014 SHA256: ac3b78db185ef7455a070cbcb159414565613a9083d900304633767fef47f1e3 SHA1: e625fe0368698409fe100797d63bb23407e5b804 MD5sum: 5b27f011ccc4837ee4662343a146fe9b 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: eegdev-plugins-free Source: eegdev Version: 0.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 42 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd+1), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libusb-1.0-0 (>= 2:1.0.8), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/eegdev-plugins-free_0.1-1~nd+1_i386.deb Size: 18456 SHA256: 3f48f281d2f939aa194962c9ffac1211f4d36919b56f8a1a66835fba8c2eedd6 SHA1: 6b99298f143a2bddc337cef8a8ec4112810f43b6 MD5sum: 48cf16a9bd0ca2a49d1823d44f247fdb Description: Biosignal acquisition device library (free plugins) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the devices plugins that depends only on free components. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1_all.deb Size: 7224686 SHA256: 54ff518513962d0d5f50f6194edc9210fd1280ccb3dd2d277aee94711522513f SHA1: 0f8e5ec99bfea7724ce386136c4733c175063e78 MD5sum: 489d2beaf9e6e7e581abbfb6cebbef44 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.8.4+svn20110323-1~nd+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~nd+1_all.deb Size: 97950 SHA256: e0e1262227ba72bda4d223e33349c278d34846b0da6c96e6671618b1f59edb61 SHA1: 50440e1dc1aa832bba1845b7d1521e1d652fe7db MD5sum: 1a0aad91cbf67c3706f4665ca04701ea 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+2-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7 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+2-3~nd+1_i386.deb Size: 5490 SHA256: 2c3a47041a83eab68e782a44b3e655eb989b69ba80c614c8e93623761dd8afb2 SHA1: f360bad333b4019852714ca9a9a9dc3151064312 MD5sum: 44f8204d4fdd70ddcaa4aa8933f71d8e 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: gdf-tools Source: libgdf Version: 0.1.1~svn62-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-program-options1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libc6 (>= 2.3.6-6~), 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~svn62-1~nd+1_i386.deb Size: 38728 SHA256: add21c71de1a8836f6142c2499c05c095245b9b21103781879a93b7bfd7110d8 SHA1: c8116e795eca276be90ab7a49847a6afd084495c MD5sum: c4717922d0f4817cb37e71713a932a03 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: glew-utils Source: glew Version: 1.6.0-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd+1), libc6 (>= 2.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Replaces: libglew1.4 (<< 1.5) Homepage: http://glew.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.6.0-2~nd+1_i386.deb Size: 123146 SHA256: 1a1ffa5b5ebb9a8b75b4a308e7c02a6b0c551827ea378ed4121765d905cc0486 SHA1: 0d53a023b0b0ba69078291cc09e42ad8f9c98f53 MD5sum: 3a97c58a3e3b19ce1036b1a5fe3b54f3 Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew1.6-dev package. . This package contains the utilities which can be used to query the supported openGL extensions. Package: guacamole Version: 0.5.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 255 Depends: neurodebian-popularity-contest, guacd (>= 0.5), guacd (<< 0.6) Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole_0.5.0-1~nd+1_all.deb Size: 234294 SHA256: 6a357345fc53069e85cb7bb5d16ec8471d7d0fc4677146232c61fafb4716b974 SHA1: b9d144992909e3d40e97e85175eea825b17e1675 MD5sum: f8fbff752174477df2989c46d6e71455 Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole Version: 0.5.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole-tomcat_0.5.0-1~nd+1_all.deb Size: 4926 SHA256: f2ab8644e0514bec01f9ed78c71c9fbf92b8d23542b34981163354ced255449b SHA1: 9bc41824b3d1108b5e14fa3fed518d2480ad51cc MD5sum: 90c4d812ac66f52d061aa5d9c960fc19 Description: Tomcat-based Guacamole install with VNC support Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. . This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Version: 0.5.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.3.6-6~), libguac2 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacd/guacd_0.5.0-1~nd+1_i386.deb Size: 10872 SHA256: 0931ac6a24ad43bb70fda64df2ad8a6b38afbc4c7a0f63dad81f6212f815a12c SHA1: e103290b2132cc4ee86803b95456c74fcb31d031 MD5sum: 02a76691200d8d68dcb82937f78979c0 Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: ipython01x Version: 0.12-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3463 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-zmq, python-matplotlib Suggests: ipython01x-doc, ipython01x-parallel, ipython01x-qtconsole, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.12-1~nd+1_all.deb Size: 941152 SHA256: 194d12bc754fa4b420633fc13a66b952afe53276d7688cf46cbdee73f0781308 SHA1: d9d5775c63ac2e23833fc7e244d92ee2fc3cd3e9 MD5sum: 8f17f034c81d946a8487f0a3468c77ac Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.12-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12424 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.12-1~nd+1_all.deb Size: 4309292 SHA256: 0493d7ccf16974d19112bafdd3f897bc29298943bbf3d0e718ba7a627e3bc74b SHA1: 34c041aa1cd973127b0025797fa23eabac3a7c44 MD5sum: 5f6ae586b160c3a51f7484c9cb19890e Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-parallel Source: ipython01x Version: 0.12-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 508 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~nd+1), python-zmq (>= 2.1.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-parallel_0.12-1~nd+1_all.deb Size: 116184 SHA256: f18da753f9fc61718bbd1b240875cefcc91c145141390f2a62d3a9c5290e3a1f SHA1: 0ddaee200aa0ee768a13fbbc042310e4890ec341 MD5sum: eb301d5d3d239457f13a497f3fc7d305 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the parallel processing facilities. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-qtconsole Source: ipython01x Version: 0.12-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 339 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~nd+1), python-pygments, python-qt4, python-zmq (>= 2.0.10.1), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.12-1~nd+1_all.deb Size: 80524 SHA256: fb0ed1762f0287ec858ceccc584bec3b2bf34abc4b738212ebf845e3bb82b2d4 SHA1: ae66b8b73c168edbddc864db3d62969f9e77e328 MD5sum: 1e82d48f7c88d0599fa463a6dce78222 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the qt console. Package: itksnap Version: 2.2.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8384 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.20, libmysqlclient16 (>= 5.1.21-1), libstdc++6 (>= 4.6), libvtk5.6 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.2.0-1~nd+1_i386.deb Size: 3713202 SHA256: ee8d431ea4b156bd68cbac4d62664dd28a4f6fdd43a6b051ba5612289b3ea5bb SHA1: 4522306714a170d99586d46e0ba4c6d3e3521cdd MD5sum: 9a076861dd476f430ab046505dd96665 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~nd+1_i386.deb Size: 22222 SHA256: 3a8a7c9a6cbfabe70beb2a4890a10351841638b063901f246cd46f884e9ba4a2 SHA1: ab91c634e1089a5dfff7d7fe9898191500cd4f0c MD5sum: 8871c4844a656a33a798f48911627775 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1248 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd+1_i386.deb Size: 380420 SHA256: 43f3b5f7dfdd1993d4f5e97963e6ec6e9c08d4aaaa2d9dacef1c7518a0c8c74b SHA1: 239e9805276081ed07623c458a260f400343b95e MD5sum: b7e7b743fc76315e9f52dcb593345c23 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 776 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~nd+1_i386.deb Size: 301252 SHA256: 1657159f71c1337709546f563347261367950bbc481ee6b1d8697e71d87a40bb SHA1: 2407957bf7a6bc6d743238a335fa56fcb127659d MD5sum: 2c5959d480dabf2332928cff8517afa5 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 196 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd+1_i386.deb Size: 60066 SHA256: 7871e12f2226ef13201d5922eea715a227918c07bebf3b45c1e8d97ccb83b6af SHA1: 4512394b7874c1479ff4c91adb288e338ecd8fc9 MD5sum: b2a9a95d8ec7d1b42a2f0d9aad4d3cfe 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd+1_i386.deb Size: 17388 SHA256: 696afb9d21de3d90521d1f662bfefc3c55f8a9cac5523406e902d2481ba786e3 SHA1: 2b40fad1168ba0ed796cf3c77c794dccecde416a MD5sum: 7c8b35c7ee72a6f053db55a1c7aa6a81 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 75 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd+1_i386.deb Size: 37302 SHA256: 61cb5cbe90a3a12434bfbff96a06c2a13648f4d2c4346022ef3e9fe552309020 SHA1: fc14bc084e8be117398dd3bb251f4d9e774e1134 MD5sum: 5c9d5855e3f81f29acd65f71d03b0502 Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libclassad-dev Source: condor Version: 7.7.4-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2139 Depends: neurodebian-popularity-contest, libclassad2 (= 7.7.4-2~nd+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_7.7.4-2~nd+1_i386.deb Size: 469790 SHA256: 3ec4397888bb7dffed008cdeb2cf0325f0450db746ebc021ac08d07c7ba1d1f4 SHA1: c6e9617be5af69f28220085725317fc4422a34b8 MD5sum: 5294232d56f060c600b9bb8f447d5e59 Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad2 Source: condor Version: 7.7.4-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 793 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Priority: extra Section: science Filename: pool/main/c/condor/libclassad2_7.7.4-2~nd+1_i386.deb Size: 265146 SHA256: 871a297d32932553841b12627e4f7a81ff355aba1b09fffae721c919c4b4ffd3 SHA1: 508238ec324a2202f69cf4d07a216bb05bf7e812 MD5sum: cd8897491bc16a43b4f6a684ab67b1a0 Description: library for Condor's classads expression language A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the runtime library. Package: libdmtcpaware-dev Source: dmtcp Version: 1.2.1-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.1-2~nd+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.1-2~nd+1_i386.deb Size: 6760 SHA256: 9bac5bbc7ce7af0fce691fda56c66a4c3d2caca9b2470ce3f948a2540eb180f4 SHA1: 2ef6fdcc0faced67315ac4ba2bb56bb5cd4e5dae MD5sum: 4065b7707354319c3ae8a2d166793eff 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.1.3) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.1-2~nd+1_i386.deb Size: 6478 SHA256: ee6c85f1b8bbb987787416b3a494ed5a2c7f89a445cdd57b517862b094beea4f SHA1: ce755bc38ecc9aee88039eab1a5c58511c0f789d MD5sum: ea6936cce604cab6071dd5cd16547d97 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 57 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_1.0b-1~nd+1_i386.deb Size: 44302 SHA256: 2896084d9a8ab9545bb6a770621ef629cc4fc58030722cdd71e975d735530a42 SHA1: 89b27cb108abdf2b4800a2f5a2977c5887997e93 MD5sum: e94616eae2a2acb1cf4b9878c3832ef9 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 59 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~nd+1_i386.deb Size: 33332 SHA256: 46f0a9f8cf88aa3e97718ba2e731fd905d8c7aa4276b96cdc2871b7c3bf813c2 SHA1: 61b3e3367674ab0caf1bc9221515a082ee338643 MD5sum: c02cb6c50ebe5192121f50e8a9e24a79 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_1.0b-1~nd+1_i386.deb Size: 60710 SHA256: 29ac6935d06714fcf33f1997ba8bbc6754a7c27cfe44485b148fca14b2497e6d SHA1: dcee6907954a90a1720b9ba528be9daa4d1fb7b2 MD5sum: e9fd7481ac336be90b45505b138ffcab Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL which allow us fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Package: libeegdev-dev Source: eegdev Version: 0.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd+1) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libdevel Filename: pool/main/e/eegdev/libeegdev-dev_0.1-1~nd+1_i386.deb Size: 25320 SHA256: d27835a70cd7dfc5b5b4f17cb037106a54d1e97efece7c2aa98e8650c9605f28 SHA1: db631dd6d0303a37f4872f6a272297b9cac74e9b MD5sum: 689c541bf32965a1e18e1770addb1829 Description: Biosignal acquisition device library (Developement files) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the files needed to compile and link programs which use eegdev. Its provides also the headers neeeded to develop new device plugins. The manpages and examples are shipped in this package. Package: libeegdev0 Source: eegdev Version: 0.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~) Suggests: eegdev-plugins-free Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/libeegdev0_0.1-1~nd+1_i386.deb Size: 28508 SHA256: ccc08a2cd994a9194784f112c63625a9bcde13d69c42b63d73177d27f49edcab SHA1: 382d6154b35cae831e680983c260947ba1fe2255 MD5sum: b7d729529735c904ff524c52f4c47ab2 Description: Biosignal acquisition device library eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the core library Package: libeegdev0-dbg Source: eegdev Version: 0.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 117 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.1-1~nd+1) Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: debug Filename: pool/main/e/eegdev/libeegdev0-dbg_0.1-1~nd+1_i386.deb Size: 51978 SHA256: 3f94911419e7fcf6b2f6bed471881dfffbf986382d799d4bd5f2feeae07c6cba SHA1: 4f3a1c6e72b6c7af37efb786d01b0134f23dfa23 MD5sum: 98dcb9805aa67ca28fd448c594cae840 Description: Biosignal acquisition device library (Debugging symbols) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package provides the debugging symbols for the library. Package: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd+1_i386.deb Size: 509858 SHA256: 909e1043ad2416db965f55c97e50ab2684a23e884798720469f31e764802ffe0 SHA1: 43d8557b93fccacca3276a6b6d07302d6de348a1 MD5sum: f3d2f35ad0abdd843e12f2aba86c78e6 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10344 Depends: neurodebian-popularity-contest, ttf-freefont, libjs-jquery Suggests: libeigen3-dev Homepage: http://eigen.tuxfamily.org Priority: extra Section: doc Filename: pool/main/e/eigen3/libeigen3-doc_3.0.1-1.1~nd+1_all.deb Size: 2377404 SHA256: c6e5364649cf5f6b1db3f3ae2ba998964c4fe8f2eb419b325c156d12f699ebba SHA1: 43b49a1ec0f5cb0655454679d1d1655729ff6721 MD5sum: bd7d512332aa9a1e81f26066dcd42be1 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+2-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.6-6~), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libsm6, libstdc++6 (>= 4.4.0), libusb-1.0-0 (>= 2:1.0.8), libx11-6, libxext6, libxi6, libxmu6 Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+2-3~nd+1_i386.deb Size: 27018 SHA256: f6592034ad8be4b5aee39adb14a1ff235f75791a7dabad0669e16700332773c3 SHA1: 7fdea8ec36cbd9f6dac2da07b801cb276d6bdd9c MD5sum: f36a894f3b58f27ea21002ca0bda1508 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+2-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 53 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+2-3~nd+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+2-3~nd+1_i386.deb Size: 24262 SHA256: 9ceb028c7cf2f0b5f1dab1307295664fe388e43774532a91fa56bccd6f3e09af SHA1: 309d1873ffcb2e539fa751e433abf717c5d0da92 MD5sum: 3ef7ee1421bccb6ecb868bf8aab6de87 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+2-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 53 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+2-3~nd+1_i386.deb Size: 28326 SHA256: 88c2f0458376b6c7c89306d5f1bce512049bd52b00b08ef9790254976b152cea SHA1: b45576c622b3f89596989956f4d9fd8817fca062 MD5sum: 077312030ccc299b05a5a4b3825db1dd 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~svn62-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1~svn62-1~nd+1_i386.deb Size: 17992 SHA256: 6114e79af7e3d45dc0a6f1fca45f591ee9411f472d0a10eee354ced251fd035c SHA1: 53e7fbbd5c3303e002983cd04fb520e55bd07bc9 MD5sum: f051f8d61e5794bc3eb7c91b50ca17b7 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~svn62-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 336 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~svn62-1~nd+1_i386.deb Size: 104456 SHA256: d9698e7fb77518f4038cea9db7d43dcf5ab2f9cab4d13b15ab5d7234255b5eef SHA1: 145c7504c206fba744f1b438ba1aa71b6a352d41 MD5sum: 964a557e3b0dd4744fadf6cde828b841 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~svn62-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3652 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1~svn62-1~nd+1_i386.deb Size: 1081642 SHA256: 5f7208377a2c8de75430b9e716c8c73e00b08b17d508dc2aeed983713d669be0 SHA1: 41ea92b8dcb169bac4a650e60275599be8c5a58e MD5sum: fddf796bfb56779286c3bfe2520bb4ef Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libglew1.6 Source: glew Version: 1.6.0-2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 392 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.6_1.6.0-2~nd+1_i386.deb Size: 124948 SHA256: b5c38a1fc37b5c89914279f639f904d01191d89c688fe9be9b5ecc70b8e0748c SHA1: cc83f68f07135220d6cb6d7a01c788f9fe7c12ea MD5sum: fac83a15cbda703f27f86b9f8306619c 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1352 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd+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~nd+1_i386.deb Size: 242360 SHA256: 3348a4c57bde72fb137308467f9ac6c5c0eebe85ced4b32fa8af3adc5db9fc43 SHA1: 8348eeedce69c4f7e6f52f69fca3e261b294766a MD5sum: efe7526877b82ac11f527d548633b149 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 356 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd+1_i386.deb Size: 111264 SHA256: 267da2b1ae040171f41b0cf50c9ff244cf18de2f9969ca56664e2cbfbf6be2ce SHA1: cd6981af73291595f59d0e62948d55ca2f95a0a6 MD5sum: f8047a36cc7041c9e4ffde49e4ff004e 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 396 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd+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~nd+1_i386.deb Size: 98448 SHA256: eba45211faabc612c2e6677e25f48d305318eb888c08d4cb6d02124420df2fdc SHA1: 6781cac3c04e412befe3d919d14ab19c858fd3d2 MD5sum: fcb4e28e11df5ea2e73be09b50b63ceb Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development libraries compiled with GLEW_MX Package: libguac-client-vnc0 Source: libguac-client-vnc Version: 0.5.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcairo2 (>= 1.6.0), libguac2, libvncserver0 Recommends: vnc4server Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac-client-vnc/libguac-client-vnc0_0.5.0-1~nd+1_i386.deb Size: 11040 SHA256: 1436dd9b6faecb53a6c3843e4a30e8a5cc186047b28c39ba1d1f4040c4798dc9 SHA1: 9d9db33b2245ef1ef462ab653ce6e14792cdc95a MD5sum: fbb9b78f7069f1201b756177d7a5d377 Description: VNC client plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: libguac Version: 0.5.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 77 Depends: neurodebian-popularity-contest, libguac2 (= 0.5.0-1~nd+1) Conflicts: libguac1-dev Replaces: libguac1-dev Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac-dev_0.5.0-1~nd+1_i386.deb Size: 21138 SHA256: 900b67b2d023dabb08a918d4214675aef80eb6de3f622b07d9a13948abfd466f SHA1: 774668ffb4d10da46c79f261cf528251612146f8 MD5sum: 5f604fa875a77e3e1812b094d736b27b Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac1 Source: libguac Version: 0.4.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac1_0.4.0-1~nd+1_i386.deb Size: 13616 SHA256: 8ccc83893d344001a88063f6e75dc8a8f46751146274371c1ee2964b5c9a5ea6 SHA1: f0992fd12e74c2e7cfb3ac6e6834e6250c3f1664 MD5sum: 1db6dba36ef7c6be7e39a6353dc68767 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 99 Depends: neurodebian-popularity-contest, libguac1 (= 0.4.0-1~nd+1) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac1-dev_0.4.0-1~nd+1_i386.deb Size: 19086 SHA256: 4ae684f8dfad38b71145bd707d89f0925c072a4ce93afa2afd1579ba66f8f28f SHA1: 75b057094295c930e8ab5f717dabd36fa10591df MD5sum: 7e8aa3ae29a4d59d2cb3d57050734fd3 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac2 Source: libguac Version: 0.5.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac2_0.5.0-1~nd+1_i386.deb Size: 13822 SHA256: 2d36e2b19f3346ad028f6ce0eb6861a89f74bd87e49789396dcd6162cf2ce77b SHA1: b9ed9f772ac9d03fa9f0577ba885a3d88e7da7dc MD5sum: 6caba292347c51970bece0341eedb902 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: libjs-jquery Version: 1.2.6-1~apsy.0 Architecture: all Recommends: javascript-common Conflicts: jquery Replaces: jquery Installed-Size: 240 Maintainer: Debian Javascript Maintainers Source: jquery Priority: optional Section: web Filename: pool/main/j/jquery/libjs-jquery_1.2.6-1~apsy.0_all.deb Size: 65238 SHA256: fa858cf809b1885439cfb0d6e8ba64021a732b2e9b8493027f5d767973268d22 SHA1: 19177bbdd00962ac018ffa081149840aa7bbc469 MD5sum: 6dc346b0c5ffacbdf0e63f00d1f18485 Description: JavaScript library for dynamic web applications jQuery is a fast, concise, JavaScript Library that simplifies how you traverse HTML documents, handle events, perform animations, and add Ajax interactions to your web pages. jQuery is designed to change the way that you write JavaScript. Package: libodin-dev Source: odin Version: 1.8.1-2~sid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 15604 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-2~sid.nd1_i386.deb Size: 4027074 SHA256: 9b41cf08529574c0b8ccaaf01e533fecace14b7b73021149dcfbb8509453c33e SHA1: 25ead357fdfb304a2a31703fb25bc6d6e613a43d MD5sum: 050db6b0c2e2c58494ca7cb8fa42ad96 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-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 252 Depends: neurodebian-popularity-contest Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-3~nd+1_i386.deb Size: 45656 SHA256: 13cd3ad792ab72aa31b183a1ca2c1e06d3a088d1f6a31f583d99a84391fdcb1f SHA1: 0e1899eea9c2c692c6e9e8cac3be025b02f7f819 MD5sum: b2af1c5ab2620560fba20c1a52c66bc5 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 864 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.6) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-3~nd+1_i386.deb Size: 253052 SHA256: eda8d0037f5af8d8dc3a9eb6723822d6d906e5e5f4553f4c4b2c167a7f421733 SHA1: 010a56ab4360d32d653f4a1eab635e7b8f1e0322 MD5sum: 8877cc728a50cfe7c3459c390e51aa8b Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. Package: libopenwalnut1 Source: openwalnut Version: 1.2.5-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4936 Depends: neurodebian-popularity-contest, ttf-liberation (>= 1.0.0), libboost-date-time1.46.1 (>= 1.46.1-1), libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-signals1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph80, libopenthreads14, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.2.5-1~nd+1_i386.deb Size: 1557266 SHA256: 711c3f3b95a8b4f956d206f38a437934175d0fa45e20d54f2f2a57169a1ebb34 SHA1: 1710a81e861e443981be89c080e101bb37e06704 MD5sum: 8be50f6749ccec3ed0c8f23e5682a1f2 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.2.5-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2092 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.2.5-1~nd+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 2.8.1), libopenthreads-dev (>= 2.8.1), libboost-dev (>= 1.42.0), libboost-program-options-dev (>= 1.42.0), libboost-thread-dev (>= 1.42.0), libboost-filesystem-dev (>= 1.42.0), libboost-date-time-dev (>= 1.42.0), libboost-system-dev (>= 1.42.0), libboost-signals-dev (>= 1.42.0), libboost-regex-dev (>= 1.42.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.2.5-1~nd+1_i386.deb Size: 262288 SHA256: 5db90968b450773b4c97b4526090796469b3787b5c258a9f63bcc77ce8ab4112 SHA1: 7f37c0c580f768cd1e11a5fbbbb428565a0348f3 MD5sum: 88807aacae5c7da27cd5ecbd57480f56 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.2.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41724 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.2.5-1~nd+1_all.deb Size: 4302986 SHA256: 122dfa0792e4baf92b4fd2a24015ff5bcfe31c05b6b2805ba6780cf568a88279 SHA1: bae11b358b0ded97ff03c8a6b90f5e6c8287f00c MD5sum: a1e1c4dc4e2885d44958a22f86b8cabd Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd+1_i386.deb Size: 7764 SHA256: aa3e470d40896dc4f82b1dfbc583fda768a79fc3668ff4fe31256d1170c25e68 SHA1: 38d3117afc9e66e1895aa879bf457e13bb481b64 MD5sum: 87c6e98c0be079dff1d38a60b0f9266a 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-1~nd+1_i386.deb Size: 12546 SHA256: 8f800c775cb2f78870f4cd811cbf8d800103e716f498d0e2e8a491215c03133a SHA1: c0f29b6aa1b2da17e108a1634e80a60efccdc005 MD5sum: 65d487dd41a8c46b465dc80f6eec3097 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libc6 (>= 2.2) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-1~nd+1_i386.deb Size: 27948 SHA256: 156b2c18351e2721f7b46771545c0014eccc593c13cfe367f3fa37929899e8d9 SHA1: 97fe96bbbe1b4119aa524227d4e10d86d40b3e75 MD5sum: 53987a148bda57c1a37a8bd1d3075151 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 86 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-1~nd+1_i386.deb Size: 32068 SHA256: d190dc6b6f0c75a056fc75947918182be423be1cc0a8c216b682a52814842a23 SHA1: 1fbe300b8f0440fe2e9b7d6eed5944cb4f080ffa MD5sum: 341a309a10b9f7612c105f9bd3a99e08 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd+1_i386.deb Size: 39860 SHA256: 3555022a1cac2b2922c85aafefe8bf6c0c1eb084bbf06ab954c997266b1c96ce SHA1: fe4c636fc25bb3b2e61ad73a5dcc4ac57924bb22 MD5sum: 768a805bea03722476e0550ce9c52692 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~nd+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~nd+1_all.deb Size: 13482 SHA256: 1492b2687984b9a78136924b2b39e6e61aa7cce3db838336fee65922035b3ee0 SHA1: 13a26757ee98ac492d11734e3a474b294266c9f2 MD5sum: 98d98d2c95a2b57a1d0f0fd2ccbf5e27 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, libc6 (>= 2.1), 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~nd+1_i386.deb Size: 112556 SHA256: 84747ab920dc8d4588e2ef2fd65879ddd0a82cc401405ac7d5e4bdaf2ebd2a11 SHA1: 0c68a8680d5e5d790b67eb774781952c9b8918c4 MD5sum: 2fdb84b3e8fb4244ff7feb655508af27 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), 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~nd+1_i386.deb Size: 42908 SHA256: 37acb94c6d0ebd4a7a89b8aab38ea9199030b9340e1feba2351b36c512222d3a SHA1: 0c6693a195f772057e4f645105a2999829f4f507 MD5sum: 5cae72a0496476aabfdae9488d11552c 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~nd+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~nd+1_all.deb Size: 60478 SHA256: 801debe37d8eb71cf96cc8acb1f192c1ff8b0a237ff08c17575a3294f5f65b68 SHA1: e237f6806ac39e2fccaca7e875b4a02449cb425a MD5sum: 5f50baac283e77ea67d18c68132f91b8 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. Package: libxdffileio-dev Source: xdffileio Version: 0.2-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.2-1~nd+1_i386.deb Size: 27726 SHA256: c8ea573e79935406581b87c5fb4c28747e958523f208cadc018ea26aaba0a269 SHA1: 7e7f9f178170df4ced6cc2aec749fa9cd4d85f0c MD5sum: ed16d4dc1ead226ec4850b89b9997792 Description: Library to read/write EEG data file formats (development files) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package contains the files needed to compile and link programs which use xdffileio. Package: libxdffileio0 Source: xdffileio Version: 0.2-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libs Filename: pool/main/x/xdffileio/libxdffileio0_0.2-1~nd+1_i386.deb Size: 43572 SHA256: f37d0c8b30ff7782146325954e1dbd22a1a44f4ecb9790d3e3a8f6b09a7665d3 SHA1: 25313236ea2a9d96ef3f1fd08ec1cfc483c55f65 MD5sum: b6ee6d44c4afeedf93be0c04f3eef136 Description: Library to read/write EEG data file formats xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead of the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. Package: libxdffileio0-dbg Source: xdffileio Version: 0.2-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.2-1~nd+1_i386.deb Size: 61770 SHA256: 3b3f06635d029e4c7cff910b59ee1a1f1f75cabde86b7ded68a2eff3ae42a010 SHA1: 14a6732f7f2a936477d4b6d4e2579933af2fe7cb MD5sum: e6f57633c9fbe9949beafd253d3e495d Description: Library to read/write EEG data file formats (debugging symbols) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package provides the debugging symbols of the library. Package: matlab-support-dev Source: matlab-support Version: 0.0.17~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.17~nd+1_all.deb Size: 6702 SHA256: 1202ca31cbc506b4e028a967da3f94a2df613e0fc838aa2ec5dc70a6075eaced SHA1: 70d3ab7d83bece18f1247f25d37575cb2b76950e MD5sum: 9fdbf5168a13764aadb2189053e245fc 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: 1.8.1-2~sid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 6240 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.3.6-6~), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti1 (>> 1.1.0-2), 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, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-2~sid.nd1_i386.deb Size: 2378956 SHA256: b1b3d6c40a319d5e65d2dc57c3a6c2b0760832a1f4b55c238a1221756e62e805 SHA1: 51dbeb78c59b390e6a5a5e999b359f1e147e5fde MD5sum: 493efff613cc2f0ad44be7de1f7f2e50 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1962 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~nd+1_i386.deb Size: 736340 SHA256: dbcfdbd832f2605e93dc5b1579718fe24c007e988732c9711e050968f9990aa6 SHA1: 26b1eaaf6cc3c6dc16d1ab215e037b7673e32ac7 MD5sum: e0ddde20da342cccf75a5d04ba549077 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 14268 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20110413.1~dfsg.1-1~nd+1_i386.deb Size: 5498444 SHA256: 8ac92f7b6f7acbb74606f1d14f8bfd9e2e026a4dd7b8aaf6fa61fd2044d63b9c SHA1: 90943ad218d6ec0f4d0f5027223f1965ee43a31c MD5sum: e1b5724f3fbee0aa67d0ce53ecdd2e3a Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1808 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20110413.1~dfsg.1-1~nd+1_all.deb Size: 1666546 SHA256: 584a18d0aceacf730b1fa4f792a4f9fb6456b6e8b9bc96e8ca7b899c5711fdc8 SHA1: 1b1c7a0f9d562b955dc7c6a7225094bb5de72933 MD5sum: 92fe3b8a72176d0d4247156799763be0 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1180 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20110413.1~dfsg.1-1~nd+1_all.deb Size: 738184 SHA256: 5640e7c0541b9b1725043419d2b51b57a034fe8525ef0868349fe5c50f92641f SHA1: 3f42265352fe9e32a486954e7c1a74780ae8a0a2 MD5sum: f618965068d7ec5d12d74ad5825feab0 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6876 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.28.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.27.1), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.6), libx11-6, libxmu6, libxt6 Suggests: mrtrix-doc Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.9-1~nd+1_i386.deb Size: 2376752 SHA256: 5093fb6c14ff9b62d0e79f45a4a7df4ad3a0a9e64c5b599cbbd7577a7b00cf9b SHA1: 83246bf836bae919e64dd23386fb67984d58194a MD5sum: f50d49ff0fd0a97b3c935822f726f922 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~nd+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~nd+1_all.deb Size: 2945954 SHA256: cb293bf21b3645e88ce598c9b73ea007e0c183f7692ba82e731c64b487e8b27c SHA1: 645d0146eb7149beb92fe84fa6357a23ba472b70 MD5sum: 4e62b15dcac0476207b6dc26146257ff 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 141 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.27~nd+1_all.deb Size: 113932 SHA256: 1df3902e4bb0e81668f2a5f628a3ab903e2a65e986d2c61df658616661f326f0 SHA1: b3a572747fc1c8468cd25f2fdef50f4fae508388 MD5sum: 16720b90a972fd1ec8d4f8cf5c964083 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5450 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.27~nd+1_all.deb Size: 5087696 SHA256: b3e8e2b1c5c2abdb9d141f7cbc7286750c3eff52c612cd8c94771d476188b5c8 SHA1: dceee095fd4c0bdb819d1a9acf8cb8fe9ae9a01f MD5sum: 58e35ea9d23ec807c38dbd49c6f252ca 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 105 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.27~nd+1_all.deb Size: 13430 SHA256: 113e7334a884fc456114f21491e286a566c26fdf59c8c7cbba04f74b3da94e94 SHA1: 90a78a11912b4241e5914e602316be1473160a1c MD5sum: 664eda422a6d2a1593af98e4bc8c7b5d 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.27~nd+1_all.deb Size: 6380 SHA256: 1af496b1ca6f1475b66b8abebfd8e96fb4e276dc9dce5ffe32e4e33b6a00c1d5 SHA1: b84622029040927ee62f4da67aa92dbb01580ce0 MD5sum: f89309d9d202addebfd2081257fc46c2 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.27~nd+1_all.deb Size: 5550 SHA256: e395f6f8a8c1119869b52756ae73811dcb56fcc60616c9607b5e518d8da25941 SHA1: 3cf3abf781ae9331b1c9e51fcdc512767fc788a7 MD5sum: c8749487c3a64660122cf811d46e2806 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: nuitka Version: 0.3.19.1+ds-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1196 Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1) | g++-4.5, scons (>= 2.0.0), python-dev (>= 2.6.6-2), python (>= 2.6.6-7~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6) Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.3.19.1+ds-1~nd+1_all.deb Size: 241466 SHA256: b3607bb4ca90766d9dfd30c4380804ea77dc05a8527f53c2563dcec58185fa4f SHA1: d6ceb8348f8bc7f4a4f649434748c88183fd4804 MD5sum: a91134cdba049ff35444aa4506e3fe06 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class to pure Python objects at all. Package: numdiff Version: 5.2.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 644 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.2.1-1~nd+1_i386.deb Size: 441078 SHA256: e598f0967a5cba3ee172a17bfa0fc97c4f8e46beda223eac91954127fc8c5698 SHA1: fb3842877f5bb1c03b596e583244fccb5bb261a3 MD5sum: 71dd47d6eb9e7dad673351cc41f3fb73 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, libbiosig0, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.1.3), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.5-5~), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.96.3+svn2677-1~nd+1_i386.deb Size: 17430 SHA256: 98c7efb00ec91208a910967b6f71abdfc7b4f31e7097b6e7427001def73466df SHA1: a2ecf8a768a555cc586e7d984a0fd6cf0cd0ecb5 MD5sum: 78872936169d478771c1b126045d86ee 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~svn62-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.1.3), 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~svn62-1~nd+1_i386.deb Size: 130464 SHA256: 78902b55219d878fe9f1ff4256c9be92eae1ce2c824c6cca817b9c713d36b4e2 SHA1: 69d8baea5eb543e68ce656d6213744a2249d92f9 MD5sum: 4e2e47fd3539772a3d2c9a60e4303de3 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. . HIGHLY EXPERIMENTAL -- USE AT YOUR OWN RISK. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.9+svn2380.dfsg1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2290 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), freeglut3, libasound2 (>> 1.0.24.1), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.6 (>= 1.6.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libopenal1, libpciaccess0 (>= 0.8.0+git20071002), libraw1394-11, libusb-1.0-0 (>= 2:1.0.8), libx11-6 (>= 2:1.2.99.901), libxext6, libxi6 (>= 2:1.2.99.4), libxml2 (>= 2.6.27), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2380.dfsg1-1~nd+1), psychtoolbox-3-lib (= 3.0.9+svn2380.dfsg1-1~nd+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~nd+1_i386.deb Size: 757582 SHA256: 37450108a432317aee73626709cceaa1cef2b968b9c4efd6603477d800e6d26a SHA1: 3c1976f733878c7186da1c74dc2e11f6d30b0f53 MD5sum: 08e27baf71b859f38d29aca20e8cd7d6 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: 1.8.1-2~sid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 4000 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.4, mitools (= 1.8.1-2~sid.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_1.8.1-2~sid.nd1_i386.deb Size: 1546836 SHA256: 9bc35c3dac3508ced6428d06d8171d3210be155c43ca9bd6ff377e890f554d50 SHA1: bcfdda136f8f346d12213be3ce4136f08d6e966b MD5sum: 802fde227e04a77e6a5f5e510e1d7a35 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: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~sid.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~sid.nd1_all.deb Size: 34360 SHA256: 15e2e7aefc8b1af85c120f648897950db56fb71fe5999c5a3ca51b1c70bc0fb4 SHA1: 84e8c88b4d56f44c987808ba5c54b1799a0403ee MD5sum: 0eaf72ffeedd568782315315e95b4dfe Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 488 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-3~nd+1_i386.deb Size: 153356 SHA256: 666a60b1b7616961a2fbd1b7e67140dbab9ee50a29817db5b2c57b8db423c0c8 SHA1: 1a321485810847f5d731e62f54825931dbc4730d MD5sum: e538a9b1f7924b73cd2044fdb033afc2 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4142 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2 Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.25-1~nd+1_all.deb Size: 2844670 SHA256: 91d0e2ce2c479c6db500d96328ded7d72d19da3507586128ca35c6447d2bc7fa SHA1: 2bf95ff67d44d3df8e6072a79b98f8009fd5ad7a MD5sum: 32274c07dc96ca9e6a93a572f6f82703 Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Python-Version: 2.6, 2.7 Package: openwalnut-modules Source: openwalnut Version: 1.2.5-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13556 Depends: neurodebian-popularity-contest, libbiosig0, libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-signals1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph80, libopenthreads14, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.2.5-1~nd+1_i386.deb Size: 4625068 SHA256: d1bb804f5a79780a36385356fc96a2fe0f2a4e1a4aec7cd786b496d76bc31461 SHA1: 5fd5cbd97494f2b48629a64ff444401cd8dff72c MD5sum: 7ae20629969d4bb331389eef75e26e81 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.2.5-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1696 Depends: neurodebian-popularity-contest, libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-program-options1.46.1 (>= 1.46.1-1), libboost-regex1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libopenscenegraph80, libopenthreads14, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.0), libqtwebkit4, libstdc++6 (>= 4.6) Recommends: openwalnut-modules (= 1.2.5-1~nd+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.2.5-1~nd+1_i386.deb Size: 584422 SHA256: a8221ec81840737d3cd05c5e1909d66d0f05c9b5c345136d4bd1c4b71222d2e5 SHA1: e466fdfd1066e936ea359a5c48fb72c00b484a98 MD5sum: aa1dbcf1272016771c77381a6c2c05c5 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: packaging-tutorial Version: 0.2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 836 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.2~nd+1_all.deb Size: 680180 SHA256: 4f1c39bc3f108a98284df69fc1734c3eb97957be6e441928596ccbf1ba0d1292 SHA1: 1117c3ff4a15d620a0d8fc62edcc1bfcf45e6329 MD5sum: a3c8023d51d265c6a801496c98620528 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: psychopy Version: 1.73.03+git2-g04717ae.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4446 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.73.03+git2-g04717ae.dfsg-1~nd+1_all.deb Size: 2682548 SHA256: f001217759363f3c872d798e25f12088c5da2f03e0ee7a2d027f40cdebb56303 SHA1: df9a677f1b66c746fba79ef207dc60097bde600c MD5sum: 5c38118fac6cdfe80c96ce4dc9c78daa Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.6, 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2380.dfsg1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47873 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~nd+1_all.deb Size: 19698220 SHA256: 94cdb81b30020a6f9562d13f8e070ce1f9da7632a7e08f75d7f861b07e7871a5 SHA1: 8aee92b72470d20dd45b1a6d121a5c81d105209e MD5sum: 8d8896b08b096c734f0cb4a3fa68005a 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2149 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2380.dfsg1-1~nd+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2380.dfsg1-1~nd+1_i386.deb Size: 748888 SHA256: bf81458e621c67b443769dc86205e8cc74448ad7e838b33e114fee8b663bdcd7 SHA1: 97a534cefeb8d3b6076861d0c070d449a5133fcb MD5sum: ea74d6a31f35fabb0bc0b56da162c5bc 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 177 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good Suggests: gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.9+svn2380.dfsg1-1~nd+1_i386.deb Size: 62632 SHA256: ae4a317ec5d8a9554574481aa6566218a51c34fe10f1a5d752591127374ebef0 SHA1: b9d677730cf185eb1201ddda4177beb68ba0c814 MD5sum: e044bde3c126b953ded8772e56dab0a1 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.1.3), 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~nd+1_i386.deb Size: 52646 SHA256: de4c790ff6a9501fec691d719de6af41886bdf2bab79d2085cb82242bc3d2442 SHA1: adf2c8f2d27108b6a1b02b298bad9998a54f4711 MD5sum: da5195767b28fe98356befae287dceda Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.3.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1597 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.1-1~nd+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.1-1~nd+1_all.deb Size: 393368 SHA256: 8dc7ddd9374fd939aa74f6753323755cb762372a4fbf1e9178bdc08ae8ca4784 SHA1: b61a04b061c0de717536cd4bded68636008f56dd MD5sum: cd2bc3a56554a5a9c7cd9bf77a300636 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.3.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5259 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.3.1-1~nd+1_all.deb Size: 1969060 SHA256: ef67a9df49061d24abd98fcdc8ee5d9213c6ffd89914aabd30abc7300fb7c16a SHA1: 9fc3c1ff2baba67c6a8589586df3ab035f3a44a0 MD5sum: 1e91c86d71ffa061cde1397e6b54b7c1 Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.3.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 238 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.1-1~nd+1_i386.deb Size: 96250 SHA256: b31a5e5c9655213ed8f729b51ce7642ecf21cdbdf8719c48840823f39828d173 SHA1: 1fd7b748819e1d5d3838526a2f8a27db6a3e048c MD5sum: 8ed220bddf3885d57ac5f032c46b31d7 Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-cfflib Source: cfflib Version: 2.0.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 768 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-numpy, python-networkx (>= 1.4), python-nibabel (>= 1.1.0) Recommends: python-nose, python-sphinx, python-tables, python-h5py Provides: python2.6-cfflib, python2.7-cfflib Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd+1_all.deb Size: 217692 SHA256: 4da2bdfd6e65beb307156093efe58c8242305e225741677f043c95133dd02928 SHA1: f5afff0937ac80443da91ebd51b53ce9c454f296 MD5sum: e6da3383a7a7a89da2d0d5b33f4910b5 Description: Multi-modal connectome and metadata management and integration The Connectome File Format Library (cfflib) is a Python module for multi-modal neuroimaging connectome data and metadata management and integration. . It enables single subject and multi-subject data integration for a variety of modalities, such as networks, surfaces, volumes, fiber tracks, timeseries, scripts, arbitrary data objects such as homogeneous arrays or CSV/JSON files. It relies on existing Python modules and the standard library for basic data I/O, and adds a layer of metadata annotation as tags or with structured properties to individual data objects. Package: python-dicom Source: pydicom Version: 0.9.6-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1692 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.6-1~nd+1_all.deb Size: 390016 SHA256: ae4c746c9619f4e080fb99f31bd55406078c3f57c4545f1990f5b42dfde4778f SHA1: ecf5a399b782b379131bb43fce2e47e5d28574b3 MD5sum: 8ccc5b99529f05122006546bcac65058 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2072 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-2~nd+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.6-dipy, python2.7-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-2~nd+1_all.deb Size: 1457818 SHA256: 323789ea5ee8ebb75a28d1675588fb290655d76f72683b2838aca87690c42123 SHA1: 2d7ee18a7455996f8a75285752d35f276257568e MD5sum: e80a5be4815e47e59c2eac9160d470cb Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.6, 2.7 Package: python-dipy-doc Source: dipy Version: 0.5.0-2~nd+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~nd+1_all.deb Size: 1943442 SHA256: 9df190e7b58cc543f3af4b41335f28d06309f4744a5fac41ce2d7325ff1d30f3 SHA1: ea569a468681ca526a2706d1e8d2002468fd095c MD5sum: 7889e1cf53faa8642f32839c5b9fa791 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1024 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~) Provides: python2.6-dipy-lib, python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-2~nd+1_i386.deb Size: 348152 SHA256: 48be5bbcfcca5cf786371613d95d2346accbc56a92373e6159a05f1c1ec00343 SHA1: 60fe511e66c10d7e5efe5e23428f88f31e757135 MD5sum: be872b6bde54344fd29457b5c143b3ed Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.6, 2.7 Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+2-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libc6 (>= 2.4), libfreenect0.0, libusb-1.0-0 (>= 2:1.0.8), python-numpy Suggests: python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+2-3~nd+1_i386.deb Size: 31724 SHA256: 67ee683811ab8de79be38f08393b0e2037be22a6977ca5cd4e12585b3fe56bc7 SHA1: e1baef420a471c54ae02bb47413174c15006009c MD5sum: 2e34b980e109f2f41bc69adc088abcd1 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-griddata Source: griddata Version: 0.1.2-1~sid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 244 Depends: libc6 (>= 2.7-1), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext Recommends: python-matplotlib Provides: python2.4-griddata, python2.5-griddata Homepage: http://code.google.com/p/griddata-python/ Priority: optional Section: python Filename: pool/main/g/griddata/python-griddata_0.1.2-1~sid.apsy1_i386.deb Size: 61154 SHA256: 53efc2b4c9adf4ccdd35cb0266fd453f448119d952eebe85c0090d1b41d1fc29 SHA1: b335fe367c1a0233b495688df9af1a223520df30 MD5sum: dfad0b1ccba3fec9283ffa52e83cc495 Description: Python function to interpolate irregularly spaced data to a grid This module provides a single function, 'griddata', that fits a surface to nonuniformly spaced data points. It behaves basically like its equivalent in Matlab. Python-Version: 2.4, 2.5 Package: python-joblib Source: joblib Version: 0.6.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.6.1-1~nd+1_all.deb Size: 51020 SHA256: 678ca396bca4cd7956bab885772cab6cf38db58174ca52170a543c2c0dfd464d SHA1: 8c437c96204718c5748b15f7bbbc6d8528853273 MD5sum: 0ddf7e4c65340d97a136ffab2cd27ab1 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1), python, python-support (>= 0.90.0) Provides: python2.5-libsvm, 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~nd+1_i386.deb Size: 14306 SHA256: a3c45755d052a42111514db5b1a96d54719f9faf66e4bbc45b664c70b83f9e2d SHA1: 2b54e855092375e8792d239ca86fc6d018b2f960 MD5sum: b78d53594ff4bd591ac65d28d7316f43 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: 3.2+git28-g4243e9c-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1525 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-joblib, python-scikits-learn, python-pp Suggests: python-py Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.2+git28-g4243e9c-1~nd+1_all.deb Size: 480674 SHA256: 8155b7d99456ca650e354912187ff6127256312c641876b5d8efafd8061d91c4 SHA1: 3798f0836be94cd9498444ed69e66bf8db1ef596 MD5sum: 7b625b946264d1125652bdc9e76980cb Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. Package: python-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1884 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libopenmpi1.3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~pre1~nd+1_i386.deb Size: 543424 SHA256: 7da72fc3dc2ab80920ee36f01fc6e4514756fef5f6b4ff5a66d7a96417a05bae SHA1: b7ff87a08ee7a324d4cc8e203e6afdc38be56fa1 MD5sum: c99bf883bd80637c7aa75d24ec33e00a 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3964 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd+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~nd+1_i386.deb Size: 1322794 SHA256: e10537363644589483987c7a728969c34a91d101656eee6e33b76e48babc3aef SHA1: de0cb2598abb29d88e6d307c957cb3c3a655745a MD5sum: 722a49ab21c13309de29bd0825d2e144 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~nd+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~nd+1_all.deb Size: 54800 SHA256: 460ff10609587804fee11ca68c72611942677a0c4a52db6535f3dfbdc3880bb2 SHA1: 1f36ea0d57e0b6739f8e4402dab389ca6d8ca6f2 MD5sum: 0cce2dc50f0aadac8e7e3a2b8419a4da 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4076 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-2~nd+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-2~nd+1_all.deb Size: 2196832 SHA256: a379f925bfa7389d343f0600c32fb23202cf872f8834c183650d6cffeba5c413 SHA1: 578ffee5e361d0d8a1d12114b24feb61196fe08f MD5sum: 527bde7c26408cf02a004d51fa97c20a Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41220 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.7-2~nd+1_all.deb Size: 8775790 SHA256: c130b467c72ae91fc269802a637854d858dc8d15911af50c894650031d4b2924 SHA1: 45e56bc5af81e6f6b52581a0d12841ed44b42aa0 MD5sum: 9dae676ab99d39c1afc97a4aa5b1ac1e 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 212 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.7-2~nd+1_i386.deb Size: 70714 SHA256: 4ffbc07213778842479ad70acf2b34ff98317ae71298edce308fa9266dda94d0 SHA1: 70dd12257fbc32ecf7d014de28c9c4acb9c279b6 MD5sum: e4d9f402e055c91bff9660fbd21e1dcf Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa2 Source: pymvpa2 Version: 2.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3978 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0-1~nd+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py, python-psutil Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa2-doc, python-sklearn Provides: python2.6-mvpa2, python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.0.0-1~nd+1_all.deb Size: 2319678 SHA256: 1d58a13d8fc6fedb322e7a277fbb6e72222c5623b17bcc3f08ba07cf72886656 SHA1: 771090e46c66d3fb2c9fb33b24883634a86ee7bf MD5sum: 8ad7fbc18b2a36a74538ff84c6b06be3 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.6, 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14976 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.0.0-1~nd+1_all.deb Size: 4549318 SHA256: eda578d7023ce67dba4467b6a6395d7e771ca39cdef0dd37c5eca89fa2499e94 SHA1: 89d56d40875e69358df4e798bac109b733c5a10b MD5sum: 395e8f678192ffb974499a692656d427 Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.) as well as example scripts. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.0.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 173 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-mvpa2-lib, python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.0.0-1~nd+1_i386.deb Size: 72078 SHA256: f729a85f33cd4ab595da02b364b4b7581444b18e08812400e784968e7264efc7 SHA1: 8ce2f14ee7de6ff573da8f3fb2509aa8ea15fdb3 MD5sum: 69e240110075d752c110aa20f4e98dd3 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.6, 2.7 Package: python-networkx Version: 1.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: http://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.4-2~nd+1_all.deb Size: 647276 SHA256: 8686482d59b2830b57bbb4c95a26e38598c5d2b46b8bfc3c41ef5079c7de3f85 SHA1: 8e2dcdffdac74665f7c48190e2594d95466e3c37 MD5sum: e610b0ef6d98a399e29c3b2be7968038 Description: tool to create, manipulate and study complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-networkx-doc Source: python-networkx Version: 1.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15804 Depends: neurodebian-popularity-contest Homepage: http://networkx.lanl.gov/ Priority: optional Section: doc Filename: pool/main/p/python-networkx/python-networkx-doc_1.4-2~nd+1_all.deb Size: 6175086 SHA256: 7576cef9c963357c491c8ed98372493e4567e864c9bf9b30c1da2cbc2dd0cf80 SHA1: 861dba2262ad5310d0b4065953ee4838e7575ad7 MD5sum: ba0a43a93a019711296e4657536ef25b Description: tool to create, manipulate and study complex networks - documentation NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains documentation for NetworkX. Package: python-nibabel Source: nibabel Version: 1.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3616 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel, python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.1.0-1~nd+1_all.deb Size: 1675184 SHA256: 6f2fa75bd3deb5bdc282c4ac771a13ac95ccf61b27357979d28fc512e9a9f497 SHA1: e36f5c13d0c93dc61ba1c00c19edc43dc08f5840 MD5sum: f6d35a6b5686a477a50158bfdbc24a8f Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.6, 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.1.0-1~nd+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~nd+1_all.deb Size: 411332 SHA256: 3114d404283c2f8e253fd99769d764e3f1e2ff2aff96baa62e249b09d2e6c4ed SHA1: 1178962ae832f0451dda8db995fa05cee2dc6627 MD5sum: 63aff31358a6b7648df71ed098b1dd88 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-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~sid.nd1_all.deb Size: 469776 SHA256: 674d6faa8c47cc5d2abded6bf10d56d3c7b2041b70390b254d6bed4fe0b89f92 SHA1: 1e06be036a09d6114c43bcccf080aa256f7c7a69 MD5sum: 26e58a8ca88e85dfba68eae891bdcdeb Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nifti Source: pynifti Version: 0.20100607.1-4~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1424 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libnifti2, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python2.7, python-numpy, libjs-jquery Provides: python2.6-nifti, python2.7-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-4~nd+1_i386.deb Size: 377084 SHA256: 630cec8f4008e6127ee461fd011d0d39ff03accaec835ceb757e4433860209b2 SHA1: f7640ab7f1ba4a37883f11b3455e9d5bc5c7d94d MD5sum: 0e5212d61e909e62d2a52d252a8150e7 Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.6, 2.7 Package: python-nipy Source: nipy Version: 0.1.999-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2713 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), python-scipy, python-nibabel, python-nipy-lib (>= 0.1.999-1~nd+1) Recommends: python-matplotlib, mayavi2 Suggests: python-mvpa Provides: python2.6-nipy, python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.999-1~nd+1_all.deb Size: 743428 SHA256: df0f7a6a62b45aba2a3123b21852dadbe29e7021ac3d9fb568341e1c92b74fd1 SHA1: 603fb3e2474b655f13f5d662488ccb0c415f1875 MD5sum: cb5493fe4c224f440ce98efd0477deb7 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.6, 2.7 Package: python-nipy-doc Source: nipy Version: 0.1.999-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9334 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.1.999-1~nd+1_all.deb Size: 3515626 SHA256: 09e40badd49e0409afae732c7bab2b24d54721847ca031345f0029dc5fd41af2 SHA1: 6c2b822e606106c4a496c9aff8662e41dd1477f5 MD5sum: 00c570986926ebb14a60558355bc59bd Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.1.999-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2390 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3.6-6~), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Provides: python2.6-nipy-lib, python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.1.999-1~nd+1_i386.deb Size: 904764 SHA256: 83696c81e0c347aa801cb21202958c7284a58ee049c293797529b05be5988711 SHA1: 687b49ed52da26753c505f892eee77821644ba12 MD5sum: 6a21a85ded766deeacc1a17dd65e7853 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.6, 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.1.999-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3232 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3.6-6~), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), python-nipy-lib (= 0.1.999-1~nd+1) Provides: python2.6-nipy-lib-dbg, python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.1.999-1~nd+1_i386.deb Size: 968478 SHA256: a4691362b5526196e9b6e8e0fd3c727b905083353a33869c6272e4e9fae399ef SHA1: 6e73e928f819659be6ed73f75a9452a06656526f MD5sum: 30e0d0fa5f240316dacf530f0a977ff1 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.6, 2.7 Package: python-nipype Source: nipype Version: 0.4.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2156 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat Provides: python2.6-nipype, python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.4.1-2~nd+1_all.deb Size: 388860 SHA256: c20f177a44ea2c98a1ad17de4674e17ab48ef2a01b8dd099f6a495a4575c2724 SHA1: 75271228905e5ad7ee67a26bdfc1c3531bc7ef7d MD5sum: 61d05d1d3fd34b5a8a0c78287e1bf708 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: 0.4.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4188 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.4.1-2~nd+1_all.deb Size: 991376 SHA256: 2c8e71ec1817952fbc1f95e5502c6979557603d9c4bcb1104f3978e0720ef5b0 SHA1: d79bbb8dff55050473b3bf7d68934aa5eb982418 MD5sum: 0870520c3b52fb29e41cf53135a7167b 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~nd+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~nd+1_all.deb Size: 3902378 SHA256: f7b7e4f18738c65aa393d794ca8930132aa5e1d24253037a72fb70327babfb35 SHA1: 9b63bde335f881b8e14585ee096dd552747556ce MD5sum: ca45a99d6b22191775e0ba34696a827b 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7008 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.3.1-1~nd+1_all.deb Size: 5266966 SHA256: 1b1ecec6ffa30013c4dc71a767155523ece1166eea6fb29ef7b1905a576fa36c SHA1: 9d41b04415865f0e254da84e7bf988ba83b314b1 MD5sum: 02ced0a333b7c1f723eace0d094a63ba Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-numexpr Source: numexpr Version: 1.4.2-1.2~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 973 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_1.4.2-1.2~nd+1_i386.deb Size: 294400 SHA256: 1cdddc2d6ab45c2ebf89c91137e00c0ef7d6cad4996aa1a57c4702986aef076e SHA1: 25858b0bb6f46aa8bd4cb11173ce57b28e22a73c MD5sum: c133f4bbf79f5d1c05f097fc68aaa6a8 Description: Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-3~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 528 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-3~nd+1_i386.deb Size: 161978 SHA256: d4f4cc254bcaf36cd0d53257bd19c29ac82916f4720c2df6a72672e161066492 SHA1: 2836028ad1fc276e36d600f8ce510eee438cd210 MD5sum: 38de5c4446de6ede5fd3941a1620edfd 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1448 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.6-openopt, python2.7-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.34+svn1146-1~nd+1_all.deb Size: 206378 SHA256: 129cdf1bf1798ed6938cd23e067210f4bfaba47f5071730dbb9b8982e3b17fe0 SHA1: 240a12ecc28adb8b6fc7509ad1178c1a6b4334ef MD5sum: 82fc34e72ae6ee7e524744c05a76aea1 Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: 2.6, 2.7 Package: python-openpyxl Source: openpyxl Version: 1.5.6-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 333 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.5.6-1~nd+1_all.deb Size: 67034 SHA256: cf4c0a0ea043ac5240b7e52e50799d9fac46534cd86c935cc990ad50bd63d71c SHA1: 99dab3e384f664a602258383717b1aec14b3527a MD5sum: b007caad3b72fae3773da7e36049410f Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.7.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1737 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-dateutil, python-pandas-lib (>= 0.7.0-1~nd+1) Recommends: python-scipy, python-matplotlib, python-tables, python-tz, python-xlrd, python-scikits.statsmodels Suggests: python-pandas-doc Provides: python2.6-pandas, python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.7.0-1~nd+1_all.deb Size: 390588 SHA256: d5068d9df723c95de4c3c3f21ea4d9b5ce81250fd302236f60508c23dbf5a2b9 SHA1: 21665b0047b5721834af4b4632236af6d5a8beb1 MD5sum: 20d6ab053904bb6a70d69b124e2242b0 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure Package: python-pandas-lib Source: pandas Version: 0.7.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2789 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.4.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.6-pandas-lib, python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.7.0-1~nd+1_i386.deb Size: 998538 SHA256: 63460012059d543dce54056b953375d93f19fb6a849480667d1a302daf38a2cc SHA1: 70371bd3d9cc4f35ea8c7a7d325274c81ee82962 MD5sum: 6d7a3fb5bec98a97ec4f05b37cdaf78c Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. Python-Version: 2.6, 2.7 Package: python-pprocess Source: pprocess Version: 0.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 884 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1~nd+1_all.deb Size: 107946 SHA256: 3e996c9f274f6d3992e71be3c577f9e669f5b9342871151eefcba58a877e8a84 SHA1: 4a9b10cb4f210d526c5505cba62a4d6b7874ba8c MD5sum: 11dd58cfc840b815da9f81491de54a29 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.6, 2.7 Package: python-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd+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: python2.5-pyglet, python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd+1_all.deb Size: 972190 SHA256: d192998b5a0ad23a8014afd611a21ad4300c71dbd5d14b3f64e3f0fd669b6210 SHA1: 5e072bcd364c59d478f4006386eb7487a8ba4dbd MD5sum: 920b7e086aa6042bef058e20b3c5b057 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~nd+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~nd+1_all.deb Size: 187286 SHA256: f05cfb775f0d8307d3e861dc2d61ab202f10605606a0c0c5c9d38ae670e55566 SHA1: b953d289b3c182e130169fb1f63a994d8019797e MD5sum: 9edb8e594953950fe21834adad1ecbca 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~sid.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~sid.nd1_all.deb Size: 6946 SHA256: 61b96afae4d2c43351ad598253b8b38fff6b0c2d99669f49f431b8d8678f89be SHA1: 8442b14c93a7d2c3718d78655dc85fef951bcfaf MD5sum: 1eaea3d3d51bcd440299d8aa65220111 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: 2.5, 2.6 Package: python-pypsignifit Source: psignifit Version: 3.0~beta.20111109.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2275 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit/python-pypsignifit_3.0~beta.20111109.1-1~nd+1_i386.deb Size: 662864 SHA256: d1526da14b49ed4a938d166758fa9f092ce0338cccaa635bd1b340989cf86d62 SHA1: 2202fadcd20668bb9720ad61f9566699cd2769be MD5sum: a2da511c6194bcf5b83b0f1bb05b66be 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-pyssdh Source: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~sid.nd1_all.deb Size: 119482 SHA256: 047337422d8c671d1ca38e938384c985fc1fac566d178123b6cb5ee4d1fccc51 SHA1: 2fb56ca17ad07ee58955caf8de17a4cd24d3d85a MD5sum: 1790628c9012a2ae40aff02998bd9c41 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-pyxid Source: pyxid Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Homepage: https://github.com/cedrus-opensource/pyxid Priority: optional Section: python Filename: pool/main/p/pyxid/python-pyxid_1.0-1~nd+1_all.deb Size: 11020 SHA256: 1031c0d69dd73cb38f3e0b826193211706a94bfd04da4287288418b257e54249 SHA1: 0f0d0524354e5d07eb89efcb11779d9acd9d57e2 MD5sum: 1f2a9bc07952b1f5c6b65fc5c092f75c Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-pyxnat Source: pyxnat Version: 0.9.0~dev0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 660 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Provides: python2.6-pyxnat, python2.7-pyxnat Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.0~dev0-1~nd+1_all.deb Size: 107000 SHA256: 3277b9e60fe7a40c3864ed9838d48e4275559541712ec9e71ababeeff6c06efc SHA1: cb077dbb435dfe45849ff2fc74fdda933be118b6 MD5sum: 03c10921243ce9b256700496c6222ab9 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-scikits-learn Source: scikit-learn Version: 0.10.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest, python-sklearn, python (>= 2.6), python-support (>= 0.90.0) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.10.0-1~nd+1_all.deb Size: 19828 SHA256: 034a39738a0fe4f1dc8ef824dc090fbb2221491e561f2716e09f941da362ecaf SHA1: f46da2278b18e143f7e5451814c771ec73123e4f MD5sum: 347c14c5c36f5cfe8898a8ded39d4d71 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14640 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~nd+1_all.deb Size: 9043588 SHA256: a3580dd93cc951f5b3da98a18f6ce655a37ecc07c16cfc13ce98611158832935 SHA1: 361d6b1e7f35dbd4109872ac9a4c76fd38260beb MD5sum: 849e8c3327a1dc3603ec72731825e36c 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2324 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Provides: python2.6-scikits-learn-lib, python2.7-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~nd+1_i386.deb Size: 855870 SHA256: 12ab7a67cf056bc1eb1957a40cc0d1be11857ec90d1ecdfd8b521eb8345e67fd SHA1: 9b4bd8ebf1f6b7f2ab301b338784dcd379c9de0c MD5sum: c4446375cd1f6bc05105cc2fa6ea01ad 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, 2.7 Package: python-scikits.statsmodels Source: statsmodels Version: 0.3.1-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12296 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Conflicts: python-scikits-statsmodels Replaces: python-scikits-statsmodels Provides: python2.6-scikits.statsmodels, python2.7-scikits.statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.3.1-3~nd+1_all.deb Size: 3106342 SHA256: a2fb60818f75916a1beae06bc52ef716f0f66fa2eaf9cbc46c34947983ad5b7f SHA1: d1df940937c858d3b208449e915122f944445b9d MD5sum: b2a4dcbe38ca3b407dcf01e6c491c8cd Description: classes and functions for the estimation of statistical models scikits.statsmodels is a pure Python package that provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Python-Version: 2.6, 2.7 Package: python-scikits.statsmodels-doc Source: statsmodels Version: 0.3.1-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11862 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits.statsmodels Conflicts: python-scikits-statsmodels-doc Replaces: python-scikits-statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-scikits.statsmodels-doc_0.3.1-3~nd+1_all.deb Size: 1730080 SHA256: 9875fc340fb0864a50f25a49ccda891ef56f558d1ed2064d3228af6a11cad607 SHA1: 227075dc660bdc38dac44766a69f1946bae9d31e MD5sum: 31a373254562e7e36e26c7ac9346c6bd Description: documentation and examples for python-scikits.statsmodels This package contains HTML documentation and example scripts for python-scikits.statsmodels. Package: python-simplegeneric Source: simplegeneric Version: 0.7-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Provides: python2.6-simplegeneric, python2.7-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd+1_all.deb Size: 9802 SHA256: ccfadfca5d3a2796000fcc3d0ada9731e0f45258b365c0ee84591f3770427913 SHA1: b4bd46ca82b53ea624e1ffba0de0728089a89140 MD5sum: 0482bb6d6be4162e4e3e57a5a181d55c Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-sklearn Source: scikit-learn Version: 0.10.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2235 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.10.0-1~nd+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.6-sklearn, python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.10.0-1~nd+1_all.deb Size: 832850 SHA256: e7b74b601c1a5e503c5dd5dbcc52b64fa26119be08519675bf1df77e00fa1e89 SHA1: c0704ba6873b30c417080cabfe53d253105b2e9f MD5sum: 8ba9bfcf8d1159979e7539da3d148352 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.6, 2.7 Package: python-sklearn-doc Source: scikit-learn Version: 0.10.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20757 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.10.0-1~nd+1_all.deb Size: 13380088 SHA256: 0bcf14b6597a89ede6d5c1d57a20a65513f6f34ac4f3cfe3aa08680b5c94ed95 SHA1: 0e5753f2a5ae92ab8e01c02d1b5fb06159df81a2 MD5sum: 3748a448e471f2bded33081066ce1f42 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.10.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2950 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.6-sklearn-lib, python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.10.0-1~nd+1_i386.deb Size: 1134796 SHA256: fac45fbc6a7704bbd9abe62af3e917bf10f0d05878f71441f95c044e5f8c8969 SHA1: ed0d131d12fd01c67873c949d706b777b5a4eedf MD5sum: 0837a35563ca12b1f4476653c2aed8db Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.6, 2.7 Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd+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~nd+1_all.deb Size: 1260238 SHA256: 6b0bdebb3903a4eb0a75440f121dde7c531d0b7b060d33223f1185d9e0a27ce9 SHA1: 555f959d260ce486fb4395838b0918eaf71fab5e MD5sum: c52dab199b31675ed95d4298586b8ed2 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 512 Depends: neurodebian-popularity-contest, libc6 (>= 2.2), 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~nd+1_i386.deb Size: 231390 SHA256: 1c88937648d6f673f8bfbd8ab512286e5d74f2e7c7df95995ee8fc5520ea9bde SHA1: f839b408d99a51ae64c5421145071deec985cd4a MD5sum: 76bd56d114dce5d128d38a86a0e55bd4 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~nd+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~nd+1_all.deb Size: 21896 SHA256: 9f72bca932d735b81b935b7a51c8ef71c796039624931fad0ecec1e534482dd3 SHA1: ceb14fa980961c75e97b0ca4174aa3e5fb8552b4 MD5sum: b3307c35a74058502442e06b0b1a8fec Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.6, 2.7 Package: python-sympy Source: sympy Version: 0.6.7-1.1~nd+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~nd+1_all.deb Size: 1696300 SHA256: 65cc1db7a2ef35ab86aef147e04c6b2d8b7c2ca10e689a3e9767e3bce6291484 SHA1: b6182a46ed673beb7b3568356ac27cb73ca33585 MD5sum: 16047fa2cf0d90581ff5df51e1de35b1 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-tornado Version: 2.1.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, python2.6 | python2.7, python (>= 2.6.6-7~), python (<< 2.8), python-pycurl, ca-certificates Recommends: python-mysqldb Homepage: http://www.tornadoweb.org/ Priority: optional Section: python Filename: pool/main/p/python-tornado/python-tornado_2.1.0-1~nd+1_i386.deb Size: 223240 SHA256: e48226c5f84e8edfd0f5b9beefb6ece2a95a573777c4382c4523089845ef8ec2 SHA1: a545ea826a1877eebe7e2cb8a0686320554751df MD5sum: 841fa03b37ae50ab479c174e2ec0aa48 Description: scalable, non-blocking web server and tools Tornado is an open source version of the scalable, non-blocking web server and tools that power FriendFeed. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the underlying non-blocking infrastructure. Package: python-tz Version: 2011h-0.1~nd+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~nd+1_all.deb Size: 46912 SHA256: 0e8fdcb7a39493961a0d36f489eb13080b7f1e52a6d8324fedeb2d9772af249a SHA1: b1818fcc06cc8630f2af4eb25229e441028a0d81 MD5sum: cdd882a56d74682e4229bc00421ee82b Description: Python version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). Python-Version: all Package: python-workqueue Source: cctools Version: 3.4.0-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 392 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: python Filename: pool/main/c/cctools/python-workqueue_3.4.0-1~nd+1_i386.deb Size: 134726 SHA256: dee0678bc396fa3a5945e27f77d5e9b3ecdeb979cbe075f52a044974ce0cb0b3 SHA1: 10e617bb4accefea62d1dd960539e4090d48339d MD5sum: 5ecfee76ee0b93365089dba6b5b7e2ff Description: cooperative computing tools work queue Python bindings CCTools's Work Queue is a system and API for building master-worker style programs that scale up to thousands of processors. This package provides bindings to access this system from Python. Package: r-noncran-psychofun Version: 0.5.0-1~sid.apsy0 Architecture: all Depends: r-base-core (>= 2.4.0) Installed-Size: 600 Maintainer: Experimental Psychology Maintainers Source: psychofun Priority: optional Section: math Filename: pool/main/p/psychofun/r-noncran-psychofun_0.5.0-1~sid.apsy0_all.deb Size: 70968 MD5sum: ad3d95b1a239fa17cae77a362e9f8639 Description: Bayesian Inference for Psychometric Functions The package provides routines for inference about the parameters of psychometric functions. It provides routines for maximum a posteriori estimation and Markov chain Monte Carlo sampling from the posterior over model parameters. . This package is in many ways the successor of the psignifit package. Package: sigviewer Version: 0.5.1+svn556-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 956 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.6) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-1~nd+1_i386.deb Size: 422770 SHA256: d6318176b2a5df4e4975333765fdac347156cdd8e9ad9b9b023876d1085c7c1e SHA1: 60d491eb1959a9d56c98d3d1d8c85ee043979ca8 MD5sum: 509545877c86edd6436fec4908acb1f1 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~nd+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~nd+1_all.deb Size: 10547186 SHA256: 8259c16103a8d5a4633fa4f1f009de963c46cf29ad56d031308c574aef12a5cf SHA1: db0c109459249d4e2dbe2714d518d4367d401c74 MD5sum: e1dd481790e9c155b33923f772707a1f 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~nd+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~nd+1_all.deb Size: 52167546 SHA256: 34f179cb6c5f07e2cca308b199821f44fbc0216dcc2b096af4c9e6225fa5b574 SHA1: cf3a4188d88d54dee74aa1d469cb50f8024cf20e MD5sum: cda8296526ed5bc2efb5e7b7da46bcb5 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~nd+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~nd+1_all.deb Size: 8648780 SHA256: 747ac1dcf327bcd7b3086d000b182eb5f4fc60b30269edf88c68651c6e7e5e82 SHA1: 87be5ffde06e2e3e08a2b9d4fac565784e3a2343 MD5sum: b9f8f78ad274703d783a63ee06c9f929 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~nd+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~nd+1_all.deb Size: 28590 SHA256: c50f821d6eb4b0afe501c575de1b66aa196ac7745f412ca7c3064eed3f4d3c43 SHA1: 8002f08bea6021c1fa12d9e2de8b2e2482fcd799 MD5sum: aa37bec3c54a92373aeb2871266f1e77 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.6, 2.7 Package: stimfit Version: 0.10.18-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1920 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3.6-6~), 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~nd+1_i386.deb Size: 746716 SHA256: 60ed6e30a6218dd84fb5d401983e282d254c3fcf30988673fc24780f8241387c SHA1: c0d6b7ab893257315ac33356b019408f3a68ca9e MD5sum: c5f948c2929d73fbd7fa66e470f45005 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~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19508 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~nd+1_i386.deb Size: 7750322 SHA256: 057f076693849cd19dfdc6f1fc199feeab742b5a3a47b0fa7bef46e5add9777e SHA1: 94c6018533752b45c0da46c4d766f31d34076b6c MD5sum: 689dfeff61a6cc763c85639d74c94a92 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: ubuntu-keyring Version: 2010.+09.30~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd+1_all.deb Size: 11788 SHA256: 87608e20a998b8cb9799d0613e97f0b4f592a26c1433b383ddd813aa69365155 SHA1: e943e925a1106701b6e0c160fd9c06a04490355d MD5sum: 24b363866e0f915e14ecd5ed541ee822 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: voxbo Version: 1.8.5~svn1246-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9696 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), 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~nd+1_i386.deb Size: 3704722 SHA256: 1b83555dd860a6c8f91226596b5dee4b754abfaa3d06e86f308d07b58f2fe5dd SHA1: 2f7d6d96920560285b9300af6bae44fa589835fb MD5sum: d4b2ea047ade4ef198d847c988e05900 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.