Package: ants Version: 1.9.2+svn680.dfsg-2~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 39692 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.10+1_i386.deb Size: 12445766 SHA256: 7ed897dfbbfc62778d9d4b3d8a929ea8952cee3790a941f73764c4b681878e93 SHA1: b7cc39b210948f2a27227d1b1732930b85f309ae MD5sum: 465ad29893a527a94682712e8e7e00f2 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). Package: biosig-tools Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), 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~nd11.04+1+nd11.10+1_i386.deb Size: 13598 SHA256: 9222503f72105bc07a93d5217ef3cc56da54bde726d84692a559d46625710d18 SHA1: de50bc2c63f7eb6e33d3a7100c07ac087cff586c MD5sum: e9abf330886ef4d38571c502f7109696 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18424 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~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~nd11.04+1+nd11.10+1_i386.deb Size: 7387562 SHA256: e690648ca43a5247879154a8e29b4673ec47593a20531b541c70d8175273859b SHA1: 2dd7eda2a68eed6bd0fda7fa5eecceabcd7a9540 MD5sum: 55d3b4228cfc502c320d337d1e1d474d 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcgroup1 Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/cgroup-bin_0.37.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 61848 SHA256: d7cbc1cb8c1df26bf69a7b04c6b2147bcbbde66ba788bcaf77846d270a76091d SHA1: 845be15927122bcfb2179bd6eea22d34958c1143 MD5sum: 1dcb36f7a4aa3233b983011d19cf3472 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: connectomeviewer Version: 2.0.0-1~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 1355014 SHA256: b17f274b1ce406a55b295a5d1cfe161a430459cfbbc2fe2fc6b2063ba09ffc28 SHA1: 00baca2ea0ab54f9aa787320d826396824c88342 MD5sum: 728d6273844ce3467a02504dd80dff1f 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3804 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), libncurses5 (>= 5.5-5~), libopenmpi1.3, libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), libtinfo5 (>= 5.6+20070908), 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~nd11.10+1_i386.deb Size: 1491466 SHA256: d5606d15191302efc6e67de6a1e079317723e899a4ccd6dfe18175dfc1d33075 SHA1: 04980b1ce3a4b390d48823e24c0eb60e429d94b0 MD5sum: aefdaa5c548ba275d2cc212e85c19773 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 744 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~nd11.10+1_i386.deb Size: 215382 SHA256: 213a19fd8f55f8dbbc2744d869333bf7a573ace1736473d45286a905f28b111c SHA1: 4379549a8c9e004f699db378eaac6a205a4cf5ca MD5sum: d4285d4534d511a0beecc02c45c28478 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2664 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~nd11.10+1_all.deb Size: 301414 SHA256: 407caf324a1cae614eef677f4f19120f1ea517f8139031bd7d17305261e1db77 SHA1: 54ba9fe5087f4dbe720ea572e6ca13d01e2ba5e3 MD5sum: cfbe9d06f77cafdaeac26517ccc512f6 Description: documentation for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides the documentation (manual and API reference) in HTML format. Package: debruijn Version: 1.5-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.04+1+nd11.10+1_i386.deb Size: 37070 SHA256: 5467fe8009b99e9ea54c4ed667eb4d04ba3f5d15d5be8abbd108ff716e1e5222 SHA1: 3f6d147a4f7686b5977c131e9c9df2b9db27b31b MD5sum: 6d250febe022b5d5653751c48c358343 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 456 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.10+1_i386.deb Size: 151502 SHA256: 3c81d9bdf51b63489d5612659bcb9e8eb48987744541e79c53ad2599b8671f03 SHA1: 8d0a175055b2032bc90883c66a165822d894dd37 MD5sum: d2e9309e834748067e85702c284fe741 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3708 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~nd11.04+1+nd11.10+1_i386.deb Size: 1590458 SHA256: cff94dd63b1fa08b51cf13bc1a66061857063e7b852225d35b4e061757f41f0e SHA1: e2508769b7de48d79b7bc8373ebe92a742aaaabc MD5sum: e37d551088d0e76e8dc62d6f87d42d72 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21236 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~nd11.04+1+nd11.10+1_i386.deb Size: 7475336 SHA256: 73c05f2c3f89110b903dea14ec852d75896e0d99b1b71d4a66fb560977859689 SHA1: c198b5545b355acdce58fe6a849a3a5ab21e057a MD5sum: 87331f477d2ea015ab2cd0d03105ec2f 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: freenect Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-demos, libfreenect-dev, libfreenect0.0 Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.0.1+20101211+2-2~nd11.04+1+nd11.10+1_i386.deb Size: 5326 SHA256: 68399b1049fc84ae722916969c13b9cfad9d874d188b577ed455df63849bc955 SHA1: 2fafcf22dbe235d27a406c2e1e2a66c8771c68fb MD5sum: 460e5326842ccc7bfc96df9721f6b6d2 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: 0.1.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-program-options1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 34510 SHA256: 88d8d25316aff96ee767dfa0b539dab3c102f06a3c899463e10e473a441dfb71 SHA1: 093b2f7801a2b36c81ba0712d7f77e070e6fe221 MD5sum: 0d907a391b0a5263da58b15798b61cda 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 324 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd11.04+1+nd11.10+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6 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~nd11.04+1+nd11.10+1_i386.deb Size: 114914 SHA256: a20a0bb76ae0fa2618f9c11a826617d237b418ee2951d207aa41dc58ddf9f073 SHA1: e6b8b3e66e5490e861613d9310910eb8eef09f9b MD5sum: 7d17b8217fa114c98734e02e1cf58f1a Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew1.6-dev package. . This package contains the utilities which can be used to query the supported openGL extensions. Package: guacamole Version: 0.4.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, guacd (>= 0.4), guacd (<< 0.5) Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole_0.4.0-1~nd11.10+1_all.deb Size: 211550 SHA256: a0a634564689b6d93e62c8ca1db1672c5d4fd0955f39368bd88ccac729cb43c2 SHA1: e1931c2a274e574fb8f9a7875db4b1e9931adaab MD5sum: 75922aa4c0c0b2392d23c0b1872d4fa2 Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to your desktop using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser; no plugins needed. The client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole Version: 0.4.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole-tomcat_0.4.0-1~nd11.10+1_all.deb Size: 2980 SHA256: fdd6eb8b42dc9edde50da14f28f56c1f007fa5016ee730f1bbf3f33c9d3f1b41 SHA1: efd81d803b2eca5a5169200e4a19d2665d059d35 MD5sum: 959a2b831906b801c1ad712550fb6703 Description: Tomcat-based Guacamole install with VNC support This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Version: 0.4.0-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.4), libguac1 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacd/guacd_0.4.0-1~nd11.10+1_i386.deb Size: 8328 SHA256: b5584c92dba562fe5f4b963d83e2eefcccecdac8925f0f2f4c5bffc099c3b87f SHA1: 3b3472cf215f7d6f024ab1f446aacb3ef9d64bd1 MD5sum: bfc90ff130daedb7de3134c9ab34b0e7 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: 0.11+git917-gbaf566f-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4748 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), 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_0.11+git917-gbaf566f-1~nd11.10+1_all.deb Size: 893660 SHA256: 39025dc43e93c3f3d3c7511ab6e875a5ba74531f47fdad1336287741fccb9c43 SHA1: 02276516c0e0bfd4d6bf6806bf53ae95351eae69 MD5sum: 34aa43c884358ddf8f3047c41be9f257 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: 0.11+git917-gbaf566f-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13220 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.11+git917-gbaf566f-1~nd11.10+1_all.deb Size: 4004516 SHA256: 182dad7f0faa1dd5e4e55cbe8982810aa012bcb53f5f20955c79a85cfa4dafad SHA1: aa21e0a4036b75d8cfd1ae0b9338896961cc5958 MD5sum: 1ec52e96219dd059a607d89bedded821 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: 0.11+git917-gbaf566f-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 616 Depends: neurodebian-popularity-contest, ipython01x (= 0.11+git917-gbaf566f-1~nd11.10+1), python-zmq (>= 2.1.4), python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), 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_0.11+git917-gbaf566f-1~nd11.10+1_all.deb Size: 114580 SHA256: 34b113fad381fcb541e9a24adb0ae6e9303ff5ddbbf68e4dc87420f51be7bfcd SHA1: 4501060026c515e9abc922a3099553e60ee4ee56 MD5sum: 72bab4d4ff12c9fe2c75f9e54a5e87ef 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: 0.11+git917-gbaf566f-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 396 Depends: neurodebian-popularity-contest, ipython01x (= 0.11+git917-gbaf566f-1~nd11.10+1), python-pygments, python-qt4, python-zmq (>= 2.0.10.1), python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.11+git917-gbaf566f-1~nd11.10+1_all.deb Size: 79970 SHA256: 7b22020809d150dfa13c42dae9096961ceba348f8e249e1b358f50565500b775 SHA1: 99561fd8e46d2332939f1ee80057556c2fddee0d MD5sum: cf6ed24d428de8f67c27fd29df383d89 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8284 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.20, libmysqlclient16 (>= 5.1.50-1), 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~nd11.04+1+nd11.10+1_i386.deb Size: 3665926 SHA256: aa21ba4c57ff403f9a703eea4e6c82a1f296a080b60ff487a0772442ac9bc599 SHA1: ecf3cb81967cdc473f3d77f51d78c21696018cdc MD5sum: adeea70dc76a2ff5e6a4e0307e80310e 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 22440 SHA256: 5ae17bc28a2a044b76e2f20fca2bc1bf5936082310756ffd3532a0215b9c5221 SHA1: b692f518355e918031a88bee17f078a305c168e1 MD5sum: 3b9f824063db682153c4d5702ca6485b 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1256 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd11.04+1+nd11.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd11.04+1+nd11.10+1_i386.deb Size: 383802 SHA256: eeff78d06372756c7f9ec14eb8862bf5e3603008b0462e1d8ed1f40870d6d410 SHA1: c14bbe52b38789bccb1b418f8eb05925df17409a MD5sum: e73f32f34e47d5eda834b17c89c6c67e 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 776 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.96.3+svn2677-1~nd11.04+1+nd11.10+1_i386.deb Size: 300200 SHA256: 4b5b412c7db3cd529e8b2c329993225c9ebbcef07498dc1c0931cd4be38475f3 SHA1: 24958495d3994322bd4281766b242d21622e60b1 MD5sum: 4b77a390f617e8552ee61d49b4c096c5 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 200 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd11.04+1+nd11.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd11.04+1+nd11.10+1_i386.deb Size: 61046 SHA256: 7813107953b7eb3e367295ec24ab1a27daee6844d02fc04dcf706bee714d97a5 SHA1: a97ec45076961e4dbfa9881499b29b6f1c360780 MD5sum: 2b56531e6927baa91ed25bce857f6d24 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd11.04+1+nd11.10+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 17436 SHA256: 673e389a8d1a5100ae800f8cf655dbdc82b799e532801c735220ff662c9628fb SHA1: c69f72e16bdd2ca7ca77f9dba3c6b41caadd792c MD5sum: b62d51316404df67abd25fc665ca7b2c 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, libc6 (>= 2.8) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 37392 SHA256: 3383e1f446e53ba6861796243019f250367870ae6af9332e4cd1bf3ff004e025 SHA1: 2d5d87391d3b0be4cdfad4bf26baaf58d52d9bf7 MD5sum: bc8a3cf120e2699afe4b7138c6da2d86 Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libdmtcpaware-dev Source: dmtcp Version: 1.2.1-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.1-2~nd11.04+1+nd11.10+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.1-2~nd11.04+1+nd11.10+1_i386.deb Size: 6824 SHA256: 03212fa1d395d7e564bb470bbe5b9d47680d9f8759c4e51c046ca48f8d7abc03 SHA1: 41fc167a5f7482ad674a187350a3acd43c543762 MD5sum: 2de7751cdc9e26c96634e679ddf9154c 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_i386.deb Size: 6516 SHA256: ffe29b76d7f7873a57b6b74cc81dd694c5e81726abe95b0bd345b3688c107e7b SHA1: a4f94756d50fd4ab1107243b37e18bf409ae6acf MD5sum: 99ca3c68d78ecad206bdf8bda21ee07a 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 192 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_1.0b-1~nd11.10+1_i386.deb Size: 44310 SHA256: ef811711d0875b77a8f33b633a71b63038fd24e1a513e7552a3329f74c3b4f02 SHA1: bbf147ee8cbbf8613c5074237c4bdc81c53fd615 MD5sum: c2e92209a4895c6d51115ca9891216ec 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.8.0), libfreeimage3 (>= 3.13.1), 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~nd11.10+1_i386.deb Size: 23634 SHA256: c4437e9c05fccf9f6c0da2eff3621a95286360bda8f6c1b43537d5211d2c636e SHA1: 8e2f57a8ca15437a1ef468a5bb0963d339ed9ec6 MD5sum: 90935b108cf6366ecdc51b89b74abb95 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 132 Depends: neurodebian-popularity-contest, libdrawtk0 (= 1.0b-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_1.0b-1~nd11.10+1_i386.deb Size: 61856 SHA256: c5627fbdf9ac803ff7303ae5e52e27a9ff9cf511c0206528821ae5f05113260b SHA1: 55a12a4261452c981759364178b0562f40140ce1 MD5sum: 18230e8c6edaadecd060ca7d79346935 Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL which allow us fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Package: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_i386.deb Size: 509894 SHA256: 0c4411e8f674a27092fd5f8cd125f81d30d24ddc1ac26ea9a23c53dc8b830e72 SHA1: d65fd9dd7ffa6255e83da89f5f0e226ad1071028 MD5sum: b0abb08673f2b902286e49b7fd6403b5 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 2377554 SHA256: b10bc856da21570c058c78ecc6d45f7ec65ebcfa496e8648a15818832848409a SHA1: a9049d21248516a856a3247716434fc0f3570174 MD5sum: 3132bc48507615180b857a6ff67c20b8 Description: eigen3 API docmentation Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . This package provides the complete eigen3 API documentation in HTML format. Package: libfreenect-demos Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.6-6~), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.4.0), libusb-1.0-0, libglut3 Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+2-2~nd11.04+1+nd11.10+1_i386.deb Size: 26324 SHA256: 6855313310a5bb411e69f6cb0fe7a7c077dca75592a3c4ca16b00116f85166fe SHA1: b052811831535ab2b35e240954d4a192a8b0e18a MD5sum: 266bb5f0c92f2f77cafa6b7e4669475d Description: library for accessing Kinect USB camera -- demonstrations libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package includes some example programs for kinect. All programs start with a freenec- prefix. Package: libfreenect-dev Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+2-2~nd11.04+1+nd11.10+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+2-2~nd11.04+1+nd11.10+1_i386.deb Size: 24092 SHA256: e728d6a0da4fcb8b5dad8d120fd2c65e3e486681eaa5a20f2e5b5181e9e4636b SHA1: 8108fb7b0946e39d8b1689ef3ee2a0d10aa0b234 MD5sum: 33567234daac3b626bc950bd5f8a009b Description: library for accessing Kinect USB camera -- development files libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect0.0 Source: libfreenect Version: 1:0.0.1+20101211+2-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 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+2-2~nd11.04+1+nd11.10+1_i386.deb Size: 27722 SHA256: e43a1f080d6790726348f450132d0c3a2ca2de0882eb6f40fdab1f7a3f121878 SHA1: 0d4ec22934a2e9af042feb727f9e69ed1f99d97f MD5sum: 24d389c986458858367e06af891de49b Description: library for accessing Kinect USB camera libfreenect is the core library for accessing the Microsoft Kinect USB camera. Currently, the library supports access to: - RGB and Depth Images - Motors - Accelerometer - LED Package: libgdf-dev Source: libgdf Version: 0.1.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd11.04+1+nd11.10+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 18584 SHA256: 6c475523cde1a7fdc8be02c49599497d64bccc55ca0ed1a06e2d5ee460a91443 SHA1: 36f4ec52ae651099e6d63d7055c6b3117081f4d1 MD5sum: 5c539274825e95288dd0f1d296934a66 Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 98906 SHA256: c0667c095a99260d3504655ed7fa2d50cf1026e3447d9e4d30518cf76b192394 SHA1: d45e17d84e26dfc845cdf1647a204a9db86cd8af MD5sum: 3c77bbf652564db8a83c39ed9c3bc08f Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3672 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd11.04+1+nd11.10+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 1217656 SHA256: 285b0a8bce108161a5f43c28c6310786cf8b3485e8099cc8b657603cc2b64df1 SHA1: f71ef8ca5e75aa4ca834fbcb0595aff9213d8625 MD5sum: 3e9663740c0089384c35539df86a37e1 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 372 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1 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~nd11.04+1+nd11.10+1_i386.deb Size: 116000 SHA256: f4adb793322facff4ba80059a6e46dfa6663aa31bdbd01593aad0f8a2e55c4fa SHA1: ca5ac5e9ab026e94e62e10a512e7832bc8ec3a40 MD5sum: cf039bae6b7eeb4891e95985fb6977f2 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1344 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_i386.deb Size: 241544 SHA256: b1dca912f95eefcc1e742aa3ab5ef3b3e53c4158b48a2389beb60f1ad8d55aec SHA1: dc485ebaa361af52e81a4b7dfa5423ce4b679f1f MD5sum: ddd0e7226b6cf7ba3313aac95ef695ba 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd11.04+1+nd11.10+1_i386.deb Size: 103234 SHA256: f3c2bd0e6ef850aac0971aba0d82a80b48af1fc5c477044f390786a6d200817e SHA1: 281e784f9711a65f9491f629e48a66e5b07ce152 MD5sum: d18894f116e80842ed09fe24e60bfd86 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_i386.deb Size: 97530 SHA256: 7ea5c363b70cadd30cecca9a5c9875bd3e96b07a6e4b846184b7fb403217f3a7 SHA1: 535f3aa5e7be978bbb83edca0b139a67f2cca1f2 MD5sum: e0c7e8d6fe6266dfbacb71f531724c54 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development libraries compiled with GLEW_MX Package: libguac-client-vnc0 Source: libguac-client-vnc Version: 0.4.0-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcairo2 (>= 1.6.0), libguac1, libvncserver0 Recommends: vnc4server Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac-client-vnc/libguac-client-vnc0_0.4.0-1~nd11.10+1_i386.deb Size: 9758 SHA256: 2f8b85c9a7ec38b3b37ddf408ae35024fb3bf679888f6ae85784ce4ccaeb892e SHA1: a65d2c1d41eb1244b081ac31ad6e8860918f7edc MD5sum: 8abb307afc054a29afd3dc62eb05870c Description: VNC client plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac1 Source: libguac Version: 0.4.0-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.2.4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac1_0.4.0-1~nd11.10+1_i386.deb Size: 12626 SHA256: 0627759b5651ed7b497c51e97c6d68d663d9265174804d5d73e484e39ea43b02 SHA1: c188d46d86267ecf906487d84fcf0f04692358a7 MD5sum: e3ab54ee72d2dca18ce304d49db504af 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libguac1 (= 0.4.0-1~nd11.10+1) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac1-dev_0.4.0-1~nd11.10+1_i386.deb Size: 18600 SHA256: bbb5f3fef9742f41437860b273acd2a53b31d5e973f4f508919c3d046234bec4 SHA1: a2873b8006b85443eaf8898aab613597dcb1c2f4 MD5sum: 986fcfd1770d09e27b644c51eb9fc02a 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: libopenwalnut1 Source: openwalnut Version: 1.2.5-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4860 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~nd11.04+1+nd11.10+1_i386.deb Size: 1525714 SHA256: 3be73c8cf745f9d39303575fa8a5b547a054c240a3c4b04c743ffc85dc7cedd8 SHA1: 5a933f5b6d0b747d0ce912b3839db75e8ce0a8fd MD5sum: 472a6e6f6a5ecfa45289552ad8205c2d 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2092 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.2.5-1~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_i386.deb Size: 262390 SHA256: cba7a148aad1540d71bda264abfa3ef58bffed5f2e6c69bae5483229002dd3bc SHA1: 74d971f162f83a14fe9e3d10e8558fd5b8e88c43 MD5sum: 0c8dd7b3eb973b08b38c07aae63c356f 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: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 7782 SHA256: 37b6db8ec7d10eb9994e66db74f28690ca36efbdbd16ca06f94cc3840d452eac SHA1: 902b82d0cc3b5a212193ce7ccbb308833d164c74 MD5sum: 34d8a36f3fe62b1c532bfe458832d342 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: matlab-support-dev Source: matlab-support Version: 0.0.17~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.17~nd11.10+1_all.deb Size: 6718 SHA256: 52ee098ecf540f9300bd56cf5a8a9da8d5195669331a73e36073973db2196638 SHA1: df9ac4620be23b5b3cc339781bdacc8c680f2c46 MD5sum: 139884fabe6065ac8874b3d3f3cd66e1 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mriconvert Version: 2.0.217-3~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1948 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.11.0), libwxgtk2.8-0 (>= 2.8.11.0) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.217-3~nd11.04+1+nd11.10+1_i386.deb Size: 722268 SHA256: 5f6ab44a9f505f3e1861ffa6efedf8cd2524d1a18c0584a2b053984d0abe0788 SHA1: 97b6762a02a65c3f5e5369df49d8b5e5aa766be8 MD5sum: 764babe0277f526536983949389955ab 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: mrtrix Version: 0.2.9-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6780 Depends: neurodebian-popularity-contest, libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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), libsigc++-2.0-0c2a (>= 2.0.2), libstdc++6 (>= 4.6) 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~nd11.04+1+nd11.10+1_i386.deb Size: 2301074 SHA256: d697495c050deebe28c8a1144bf5ec0313cb8fcae7b03d35499497c75de9a495 SHA1: fcbd9dc1b1f791b88639ac1e6f380b2c4ef951e7 MD5sum: 514507361eb51c49820e8c0a65d1303a 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3304 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~nd11.04+1+nd11.10+1_all.deb Size: 2939916 SHA256: 720a054a2d0ff0a6b6c3ddcebbd6c78d47eaddd2f362a646537f8dac42a65f51 SHA1: e3fff0557bbe928ed291990afb558f31ec9be413 MD5sum: c35f3afd5aac4f4065bd2c58d55efcb0 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 268 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.27~nd11.10+1_all.deb Size: 113950 SHA256: 09582ce46bd68258a147ddda6ae067e0141772273754c2a6087c7be3d6ffbc9b SHA1: 7f94e1d77060c1c032ff4fbe4c55976fe1273ed2 MD5sum: ab2a74c425be3fc2b3f777c700c4d325 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5860 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.27~nd11.10+1_all.deb Size: 5087708 SHA256: 8418d77388d5874f7e630b6c1f0ed39e3d0b1e1b3e441b19dde399502d89dd2f SHA1: d5daa8b0ad0161b58324c0f9a533fd61aa1bc5e3 MD5sum: 3eba0e10e76b268691bdebe6ebfcf0f5 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.27~nd11.10+1_all.deb Size: 13432 SHA256: 7244a0dc843c58fcfd7ffbd0b26eef4d723c9f1fd3e803dea4bd95784500d94f SHA1: 91aa2dc6d2655f25533f8e12e5bec6f3dfd3cee5 MD5sum: ea418e7e890186f66c8d5118e541f89a 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.27~nd11.10+1_all.deb Size: 6388 SHA256: 8b46fd7c86dd23896058a4b176db16d333b4f5d99fef955633862d839abe295f SHA1: 1f806abc3ef38e02ee1585aebddc94aba585e34c MD5sum: 2bdb56786408810db1dab0aa3d3ad241 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.27~nd11.10+1_all.deb Size: 5558 SHA256: 58763ce315c6871388cfa7170a307d433d5ab61a21531de47c9c188f4b5241b1 SHA1: 6159a904670899f5619a820ca19ddfa8ed8df8e3 MD5sum: 0133fd0efcddb631a3a0c794ac73261b 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+nd11.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 12 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+nd11.10+1_all.deb Size: 4014 SHA256: 5bacffa126ab7654754369919f7b9527aadf57b51661f4b016fe67f8843f6cb9 SHA1: 307fafbeafac540b694e923cd3ad54b0216ebf9e MD5sum: d99019eef17b40cf51fb433ab293e096 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+nd11.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 8 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+nd11.10+1_all.deb Size: 2358 SHA256: d3a82c79097120adb8d94cec97abcbfbbd4234ab8afd8819836a46eb9583b839 SHA1: 5f01b7eb97342580aca0b251374c0122317afc39 MD5sum: ce97700faa0092c67219d66c583df95a Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: numdiff Version: 5.2.1-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 680 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.2.1-1~nd11.10+1_i386.deb Size: 446202 SHA256: 4e8a49b24eb39704aa826f71a5f037bb6e2d99b9a954b2f367115ea5bbcfa760 SHA1: d4e6a6536d85858e8872f92e3a5cf13f7c900265 MD5sum: cb91dc39f9a2c1c1fcdff61139099473 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), 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~nd11.04+1+nd11.10+1_i386.deb Size: 16602 SHA256: 9c1083c4150164dcbb5b1a3a8cc2ad1cb92ac80b68c0621f72efba02c567c8d2 SHA1: 47e6dcf63ccb1027b09388cc79b3b1d5712f0fc6 MD5sum: 67bdd7dc32c39cd8c1091a42f15334e4 Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.1-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.1-1~nd11.04+1+nd11.10+1_i386.deb Size: 112612 SHA256: 0ca980e25144a5f2b7f9871d4f08ab5a462320063c98e91b1b93acd71306bffd SHA1: 1096a8d072fc7c612dad815ef7ef079ab64d400f MD5sum: 5b34901d8bd130929d946bba52f92fe2 Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.9+svn2380.dfsg1-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2300 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), libusb-1.0-0 (>= 2:1.0.8), libx11-6 (>= 2:1.2.99.901), libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2380.dfsg1-1~nd11.10+1), psychtoolbox-3-lib (= 3.0.9+svn2380.dfsg1-1~nd11.10+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~nd11.10+1_i386.deb Size: 750024 SHA256: aa47ea45c56367e7c869c453c51d37f5f472223533ea4b30a92f571c0ebdc3ff SHA1: 93ac71d1f5026a3688c43c1f044c00738596fc24 MD5sum: 0ac6515e4dc3c38440bd0cf43ac2ecfc 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: opensesame Version: 0.25-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4904 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~nd11.10+1_all.deb Size: 2840406 SHA256: 01df3aba684cd84ca3649f6e1af5e134f8bcf8d22dfe205784bff8d5705c82be SHA1: 32e31c0d5b952d526b4bc2a6f395dceb46e96583 MD5sum: ee95f38d9b21d5b9776b54a1afa3c317 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13252 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 (>= 2.4), 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~nd11.04+1+nd11.10+1_i386.deb Size: 4498896 SHA256: 69f63d5b70381d7cdbd8d1409234ae01922dfcec6f8315876712d04be6b409dd SHA1: 5d0415b97010746bfc069826284f0e082cab75b6 MD5sum: 6b95b2c4026b159a9a00952d8ffb451d 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1672 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 (>= 2.4), 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 (>= 2.2~2011week36), libstdc++6 (>= 4.6) Recommends: openwalnut-modules (= 1.2.5-1~nd11.04+1+nd11.10+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.2.5-1~nd11.04+1+nd11.10+1_i386.deb Size: 572376 SHA256: cd808a09e11a715a050811e6c4f04348135bba7078718cf6fea827079de0a4e7 SHA1: 69eeb9df9e82d1271501f5332bca771e1fa0bbc1 MD5sum: e1a5a2672953e51c13d6e4609eeedb2b 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+nd11.10+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+nd11.10+1_all.deb Size: 680236 SHA256: 027b3fc78a6e2d64f80f8d1fb858bd737268a7773f9e3570fa4061ba709313ea SHA1: e428cf604766a0b7d9790717cd0b1de37c08ebbf MD5sum: cbd5e2e9ee0c345b662ae12bbfab1df3 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: psychopy Version: 1.71.01.dfsg-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5016 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.71.01.dfsg-1~nd11.10+1_all.deb Size: 2659098 SHA256: 6ebb741486c068ff82ccd2cccce1a7c530e7982a61fc5552e0e00d0a5875bdce SHA1: 76124445799ba4ef130a6afb22e0b8826191fde2 MD5sum: 157337ec651128f35ed76987a065b10e 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 54400 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2380.dfsg1-1~nd11.10+1_all.deb Size: 19698288 SHA256: 65a09a7c5c23c3c1a88efc211a4c33600e5da0a6f7f58c0501463d4c59145281 SHA1: 48fd556e695ed758ebb6f3a931d34776659adda8 MD5sum: abee84e271de7a029f2941085f211f54 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2176 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2380.dfsg1-1~nd11.10+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2380.dfsg1-1~nd11.10+1_i386.deb Size: 750170 SHA256: 1c93b2fb8a4f0ffa86abc9e59d886eed8c7f508cfe3d8dce35e32f92bc34c1db SHA1: 433d95a2a0e7d306dd7f8eb90cd8fe1aa5a889c1 MD5sum: a3e77c30fe543b9aebb4faeabc3227ec 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), 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~nd11.10+1_i386.deb Size: 60496 SHA256: 5da705620f5a65efb6d0f07c1406101afa72dcda7015ebfe527e11c76564867d SHA1: 88730a9b44486b214346fc538a727f4080415ed5 MD5sum: d033d8ded257e3fe382a6abcb28011b5 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.96.3+svn2677-1~nd11.04+1+nd11.10+1_i386.deb Size: 52620 SHA256: 0f51a0657fd88678e2533aed075a0bda5a79ab9dc9a66d788fa07d8b837aa311 SHA1: a6ec12cf93b357bb87237f5a1d085efa4dca1e50 MD5sum: b74f4f142535816e9151f3e7b63d0736 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.3.0-2~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1692 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.0-2~nd11.04+1+nd11.10+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.0-2~nd11.04+1+nd11.10+1_all.deb Size: 314128 SHA256: 08b4a0009b9926272ae58ade4f5741070bf97bfcc6741a09c5a10250c29d438b SHA1: 175b8152fe527fdf429736f3dc650dfe024e5f4e MD5sum: 4600890d78fd6bfd25843cda16c0e76c Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.3.0-2~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5340 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.3.0-2~nd11.04+1+nd11.10+1_all.deb Size: 1659934 SHA256: 9ec0fe95803f8efdceb4b7ce86e91ae9e545b27810791cbfea7d43c34208d999 SHA1: c171ac26c92980065ca0c0e22de1ae4fba18c738 MD5sum: b3f8b549a92c914f80d413830c18907f Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.3.0-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 260 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 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.0-2~nd11.04+1+nd11.10+1_i386.deb Size: 95682 SHA256: 6929d20d88ea27a520bed222661ffd3e81b616e3b917d12b0f097b3f5fbe9a0d SHA1: 15d3d68bb8fe28e0dafcc48780ce6618b0323946 MD5sum: d0c476b6b3f544c50173b6050da87df6 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 217768 SHA256: 945ffa29194d61612623fe49db9f5d194183157ceff5300a912415ac49ba3fcf SHA1: 9b4966ed4efe166d691118e8a36b15b709feaa95 MD5sum: 957be7ed778327afda20974094ead97d 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1892 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), 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~nd11.10+1_all.deb Size: 390178 SHA256: 333fddb15545d2c48265ea2c9fd7b04708c7531bbca3ad6919fc864f3380bbb8 SHA1: 55daf3b7cb8fc7dc8510cd5b90f1e400e83e0bc5 MD5sum: 95596361fc2aab8562fb38c278eff27c 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2068 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 1456922 SHA256: c589323ffb756b27d73f04059925820f5fd6b5fd1a6954c4184853d27772b681 SHA1: 37f184bf1cdfcce447cb97cd61619405a17b26b9 MD5sum: 502cfeb9124a90c56e588cba037d3303 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3236 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~nd11.04+1+nd11.10+1_all.deb Size: 1947914 SHA256: 223966c8bb7d50d91b726bf08093c722dca7b6e0f074b8b81826f7968bdecefd SHA1: 6a35fb7629258fd72107f81441205c5cb7976b99 MD5sum: 2763bd2ca1b21fe40d0cd389e6747aec 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1028 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.4) 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~nd11.04+1+nd11.10+1_i386.deb Size: 347308 SHA256: 1127b3d855e00b8ece0f7d9d4336cf61c3f552cb5a7780e1f776417a39520174 SHA1: c8602715442591ca1ea55c5dce7d7a881416c37c MD5sum: 0d5cd1f1ec68699780fd53028dc32747 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+2-2~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreenect0.0 Suggests: python-numpy, python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+2-2~nd11.04+1+nd11.10+1_i386.deb Size: 31108 SHA256: 32410d603c1f3d19aa6ab5928f65eded9442760b8b7c89cb03a1358a27b55140 SHA1: 46688290a6bbdfcce00b5393a79784970a299998 MD5sum: 6548889fbc0d4734e1c9caca315a953b Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.5.4-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.5.4-1~nd11.10+1_all.deb Size: 44446 SHA256: 0f9de04f3956eb061ef49c4f9c09989afd88c8dae54b4cd82efec2e4756719c2 SHA1: f27ddf6fa3a9ffcff511405028f98f11a630bbb8 MD5sum: 0cb865b72dda5dba64968f3c3e99deab 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-mdp Source: mdp Version: 3.2-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1904 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-joblib, python-scikits-learn, python-pp Suggests: python-py Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.2-1~nd11.10+1_all.deb Size: 478986 SHA256: 8d5f8630a62df158c425f789e4639416566b0016daa346ec3b551c0a6668d420 SHA1: b4949f722e574cabe69f40ab3d3e17d6a8866e06 MD5sum: 2106d8575db2fe07b6f8eebd89c5f356 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1952 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.3, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~nd11.04+1+nd11.10+1_i386.deb Size: 564808 SHA256: fde8d951a36e2f32c536f40e8d6a7cef7f6e58a08c9e886c85b407a9aa77998b SHA1: 0aab30f82db54b1189ce85df56970693b61b2024 MD5sum: d49388ef8dc6c55df8e945af5213c418 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3916 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~nd11.04+1+nd11.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.2.2-1~nd11.04+1+nd11.10+1_i386.deb Size: 1364202 SHA256: b45cba60f0a39e918da32b8103161cf927d4be5b7923f59ca551952b9def5b04 SHA1: 5d731f8df483b2a7af168849ab2da26f6723bad2 MD5sum: e2cf0c01687ddc0cb70c31072c1c5d10 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 288 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.2.2-1~nd11.04+1+nd11.10+1_all.deb Size: 59306 SHA256: acb3e9941d233ded6c6a2f03df950b1a1498756f1f19c77183e3f71f0875f3c0 SHA1: 50302ebeb331ebe1e534e7989f583e970907974b MD5sum: ea1cb8afa8ec0c43ab259e3a46dbfe7c 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-mvpa2 Source: pymvpa2 Version: 2.0.0~rc5-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4588 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0~rc5-1~nd11.10+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~rc5-1~nd11.10+1_all.deb Size: 2309368 SHA256: 82d020b0a5143669dd57f0cbbdc44f2b6dba13afd387f2addc0f3e58cbff913b SHA1: 4495ea46b7e789d38f0cbbd7185fc053fc4de078 MD5sum: a5502e9334d788a4e2360ff3ac68453d Description: multivariate pattern analysis with Python PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.6, 2.7 Package: python-mvpa2-lib Source: pymvpa2 Version: 2.0.0~rc5-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib 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~rc5-1~nd11.10+1_i386.deb Size: 71054 SHA256: 500585a2f712af5edc289f4d239f7a29c07ef91d8937da3c7525433508c5856b SHA1: 304435924b3d3c4bf3c1cc1205a0758ebafed8a0 MD5sum: adc2456f9630be9d66db7a1e3ad19bb0 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.6, 2.7 Package: python-networkx Version: 1.4-2~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 647342 SHA256: 8305ffbf3b9b0f4aa7fa01ee79ac0bdd317ce34ea593424b9007c813fddfbf33 SHA1: 4989c1be10a38f3df5de4966e6ffdd2990ff43c8 MD5sum: 3db204e91dd1120f3c8de68c94cb5a9c 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15820 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~nd11.04+1+nd11.10+1_all.deb Size: 6197340 SHA256: 1298fe35d1eaf05f88bb0bcbd55220c48f785482e2994c873bb5d482f8884f60 SHA1: 6230c70c0dc8cb4cdb17ce84c325fc4c3fbbab4e MD5sum: 30cd62bc8d4adefad8856a266c364c68 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3608 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~nd11.04+1+nd11.10+1_all.deb Size: 1665880 SHA256: c13ee5d3e2f61d84a4c50b43e1139b5d242616d1178bac377d61f30679ae147d SHA1: 90ffa7825dd0bb2dc8f44681e08ee4c5b0a3f99e MD5sum: 210fe8353e5cb3f8ffcc8425960fb9fb 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2764 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~nd11.04+1+nd11.10+1_all.deb Size: 410072 SHA256: b5cc16147e9bc1084f0fed4c05b41f704ebf2c99eec14d3ae35a2df3c0de32ad SHA1: 1d2b23e082309c99778e4ea31ae86bcfed2660b5 MD5sum: 0123ce1c38f9661e9ea0fa9809ac30a6 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nifti Source: pynifti Version: 0.20100607.1-4~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1432 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.04+1+nd11.10+1_i386.deb Size: 372614 SHA256: f25784471ad6b8d675e5b9fa197de2ffaf3ee98f555e0c91008d58aafbb479d2 SHA1: 3e9e6617f53a89babd095d6acf2397946f8f7bc0 MD5sum: 91ffc6f6530bdc93d9b481c08fbd6598 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3688 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~nd11.10+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~nd11.10+1_all.deb Size: 743450 SHA256: 855d2243245bfd196d6f439a3f7a3233bd254d8a0fb20143051b51eaf3178d7e SHA1: 6944b721106cff7daeda6e4e1064d5632a289228 MD5sum: b47f3495c30f4a23317d42171f858dd9 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10504 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~nd11.10+1_all.deb Size: 2760496 SHA256: 58d9e5d7c1fbe6baba68b90969506511e1155f050c255a8f679634cf060be92c SHA1: f744587e54e078f842e47d4e23c9c80c85a3991f MD5sum: 908818fbef37f076b627b47ce3256ba4 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2504 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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~nd11.10+1_i386.deb Size: 905506 SHA256: b2819542122e42e69ebe486aeb995774e26b10a0d64591be8f6c4de3541d8fee SHA1: 0ce3a297392e7973f4145cc0bd734511eb677ed1 MD5sum: 977ffe2edf3a5601584d35c8f1856bb1 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2792 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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~nd11.10+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~nd11.10+1_i386.deb Size: 1028068 SHA256: 36b2cc837d8c51a1a3f4bab10ec87c1f55743331076a9868580f717c7790ce0f SHA1: b3000587a2b2ffb0a144efc6a93f15130bd6883b MD5sum: b8e4d60819b9affa68f3dbf938b9ae6e 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 388920 SHA256: 375e90d9718a8e86a8d2ef3d747078ff623c5f66a22f40cf369fe850977d163b SHA1: 6abb2ac1c4b477bffe92b1076896b5df2030c1d3 MD5sum: 82346a425faf1bdc93e09a7027f1d128 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4196 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~nd11.04+1+nd11.10+1_all.deb Size: 996242 SHA256: 2de23cc3372eed187d9346603908b7c83fa9b885949a5bab8fcc35f2cf1b3b97 SHA1: 641e59ff5c53e48514f517c411c5a85bbc3190ed MD5sum: ac686d7b8aa3abc1adb6afab8bac7493 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 3902438 SHA256: 94cb749a46bb7846d06c5e38a905ef49a0db37d0c4d924d022c8dcddcd2fc80f SHA1: e63b6ff92c76b1a49fa4761156a52f8fdf12c6c3 MD5sum: 47a136537d4b5911cc4767ab9bd9a630 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6968 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~nd11.04+1+nd11.10+1_all.deb Size: 5211328 SHA256: 11d527cd2b6c6aaebd41197f1be3eac3b189c8d27f68f72335c52222cb293aff SHA1: 218ea273a943f2eba04e7bcb4f92f5df812255f6 MD5sum: 8fb95718fa4b5c8e25dd193045b5fa38 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-openopt Source: openopt Version: 0.34+svn1146-1~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 206460 SHA256: 88192ac96e59d062ada457eceb69346320b8a2444e790e9f3cdd017ef87f8523 SHA1: e0db2fd66646b2fd05e567ce2f129e88b7b20a20 MD5sum: 4da1dc0fa4cc6592a53429f3aef84f7d 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~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 476 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.5.6-1~nd11.10+1_all.deb Size: 67022 SHA256: fb20c7391c028ce128fd1fedc5b52d60f41dc8dbf99bfb840c133064fdd19b0d SHA1: c7fb9233f270f923a9529173c42dff114504f289 MD5sum: c6247f93fa123cf5ab6071e38b6839e1 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: 0.5.0+git7-gcf32be2-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1476 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-dateutil, python-pandas-lib (>= 0.5.0+git7-gcf32be2-1~nd11.10+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_0.5.0+git7-gcf32be2-1~nd11.10+1_all.deb Size: 282388 SHA256: 364f35b38450a09a60d18dbe3ba2365fe9fc3bb7b5b3697bf537886f99e6b685 SHA1: 3ce8cbad8867091fc6f23da362d4f70bed1334ba MD5sum: 36cdbd9829d0c0e5fa4b19c6ebf16bed 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: 0.5.0+git7-gcf32be2-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1984 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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-pandas-lib, python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.5.0+git7-gcf32be2-1~nd11.10+1_i386.deb Size: 620154 SHA256: 229935a18a4b5e2a973a5068c57c697e36441fe5d1cbe5ceea9e289f96f4d7b6 SHA1: 1c107196555fea9972614bf14019e86d5cad3643 MD5sum: 2353a1a109335a33379722657b665ec8 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-pypsignifit Source: psignifit Version: 3.0~beta.20111109.1-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2312 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.10+1_i386.deb Size: 644628 SHA256: 44bd714344950619b1f0c14476203a4bfb0ec1ca8d69cb81f46d7d240500f82a SHA1: 9752abc5be6d4888669b0d068360fd74e8288a70 MD5sum: 078b346bd0d31ff2a2f9a2f7b7dc265b Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pyxid Source: pyxid Version: 1.0-1~nd+1+nd11.10+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+nd11.10+1_all.deb Size: 11100 SHA256: d011406599bd44d733fc6b2dc8e48e6380c2aead88cc559a748176f4d4565974 SHA1: 2a5004077b19787ef3b372a80c0a5f337d9b0d8f MD5sum: 24217d1a30d0ee4a90e48706724f71f8 Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-scikits-learn Source: scikit-learn Version: 0.9.0.dfsg-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.9.0.dfsg-1~nd11.10+1_all.deb Size: 17114 SHA256: df74eafec047e410dff0a8d28b851a78f7f38551a40aea311690ef26ab4293fa SHA1: d9bfd7e733d6fafba87bc2996b551c346291bcec MD5sum: a3bdb5eab6d9754a221d4c1ee7f59890 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~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14656 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~nd11.04+1+nd11.10+1_all.deb Size: 9048484 SHA256: ede4d2c70d56d31f6e0e3313e8d72ebe205f7e2b37fc03b88812f6fbc0f604cf SHA1: 4f35caed7db3cb85373f8434a6a0b19b4d0b9aeb MD5sum: bd65ec66ff908836ea4a9301630c4b39 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2304 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd11.04+1+nd11.10+1_i386.deb Size: 849512 SHA256: caf8d52096b891714d20e1421d2b2379fd54bcb8ebee1283c7d77cd7073825ff SHA1: 2d93d816f54fcc10caa4b9ac2db6092386a681b9 MD5sum: 5f2d806d7f6c96f8be59c60fe50b9cca 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: 0.3.1-1~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13280 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_0.3.1-1~nd11.04+1+nd11.10+1_all.deb Size: 3099496 SHA256: 4f45dce2a3e67ff593aa39f555bc5866a7ff9d127ce2309dd5c32620b3c1b45a SHA1: 4ea9c45b9d569fd5eaaaa8b312d6ccd641465d75 MD5sum: 3d65f4e24732b3b80e557a4403614521 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: 0.3.1-1~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20736 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_0.3.1-1~nd11.04+1+nd11.10+1_all.deb Size: 2664322 SHA256: 0e5a74fda1fc38fab4e14ec00b6f81da3d85b2b33307f9728e99e4c1bb23b0e6 SHA1: 82a71562f957a9a9b70c530587e33fd418273ae1 MD5sum: 4726b6678b449e525291b24a9a78a0b7 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 9852 SHA256: e2c3258c674efe146f278f1aeaf4f784a14650a328c13f14ba61c7e57d3998ef SHA1: a40a6bbbc81b78db9240d74ecb28f02deb114e4f MD5sum: 8f5351e7916aa4bd818b8b32b85bd1d5 Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-sklearn Source: scikit-learn Version: 0.9.0.dfsg-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2452 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.9.0.dfsg-1~nd11.10+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_0.9.0.dfsg-1~nd11.10+1_all.deb Size: 770564 SHA256: e83d98e20068b3e521bb6729c454d6aa4d0fcb518a5aec77392215ab6bedad2c SHA1: 8d3cddf19f2e73cb2ae5c316065a3a8ef2cf2d03 MD5sum: ee5655ec27c704ae430f24792b9b1854 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: 0.9.0.dfsg-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22660 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.9.0.dfsg-1~nd11.10+1_all.deb Size: 13902626 SHA256: 5715f8731e73e6d139a1606fee91a105ac7b413307c8ccba4c07324fdd97057e SHA1: 749ba87c88eb99e2f838e5c92ef8baad34588ab5 MD5sum: 365988c2880a31afb8ec7bf2a14a6898 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.9.0.dfsg-1~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2632 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_0.9.0.dfsg-1~nd11.10+1_i386.deb Size: 989560 SHA256: 8a7bbdf5deae6315fa736b7ee14583789846b73f46601ab9a85a001e2cd33f48 SHA1: d35fe74f6e978a025e701dcd239202923cb23fd4 MD5sum: 343a8fdb9004a652a1655ee53afdb6f6 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 1260302 SHA256: 495b7afa951c288715f8c0b6f6c314c3286907bae13d423ceea99ba046781b7f SHA1: 4feb90b0ae8149804402955ccdaca020c35170e1 MD5sum: e6d442360ccd5c369d1610e870a607d1 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 472 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.7 (>= 2.7), 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~nd11.04+1+nd11.10+1_i386.deb Size: 199842 SHA256: b8875f290944b6d3c4eeaf8d00767b61c42e72400f7c56a92726243978af508c SHA1: 21fb1368e8f0618617a4fb999c68f0b66718473a MD5sum: 8436972f39d6457656f74d16918696fd 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 21954 SHA256: 09d5f28be9a56a3fab4e2340d598b90316b95829149e81eb5b099dfbca279df3 SHA1: 07e6862105433cc58f66b811abcb22eabb4b1672 MD5sum: ecddf9c6f30c7b1fc274be9952121b07 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.6, 2.7 Package: python-tornado Version: 2.1.0-1~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), 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~nd11.04+1+nd11.10+1_i386.deb Size: 223398 SHA256: a9d070beafafc7ea83b96e4504f17b99c88309b90eeacd7fab71c8732847f147 SHA1: a7bca7194760829ab3ffe6a05f88c8fa6ca4ecfb MD5sum: ed95e4ece1741a6f6bd8fb5e15c8c870 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-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd11.04+1+nd11.10+1 Architecture: i386 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 2216 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd11.04+1+nd11.10+1_i386.deb Size: 383842 SHA256: b384c97c553ffff21be0c58343fddbf5b62f77047f63671fa991294ab0620719 SHA1: dcdf5831c8b50832e617ab72a8d5e62de88618c4 MD5sum: 9698caab05041dea206a1a57dcbc30da Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python-tz Version: 2011h-0.1~nd11.04+1+nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 176 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~nd11.04+1+nd11.10+1_all.deb Size: 45756 SHA256: 0b42a2fabc5c73d7694010c9988894bb9a7a82e49ff0bb6fa84d404414bffc72 SHA1: 2dd818e3c70c7324e1f43e53a24c662c88aae798 MD5sum: 54c73691895639b1a157fc6b6bfd6cb7 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~nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python2.7 | python2.6, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: python Filename: pool/main/c/cctools/python-workqueue_3.4.0-1~nd11.10+1_i386.deb Size: 139944 SHA256: b5e418ce4232dfeed7f66fdcdda3b209f4ee8e963aa5a7bc85fdddb9607bc3d5 SHA1: d6ca13e57647714b515ac2f4fde04dc13f425602 MD5sum: 13de52c13555fab8a5c9f4a2b28b7659 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: spm8-common Source: spm8 Version: 8.4290~dfsg.1-1~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 10547266 SHA256: 818fd22ff4522e1da4fd7392ae96773e8969474b5dcd48aafc747d16fec2b2b7 SHA1: 89e89c76154108bae4cd77fb1e20215e38212e9b MD5sum: 0a4c2d7a2b7642c89c8bb4b885806cfd 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 52167598 SHA256: a4da0ecf01e57cec56be91a1b2794cbefa6bf39cfbe3a18eb12623e6b8cd08b1 SHA1: c6d41a3ccb77c4b9c5be04d6e111c010a60c65bc MD5sum: ca6324572d0b99c6e6173c6013c2f20b 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 8648888 SHA256: 807233ba039a504d677af13126af18711be648b89da43b2153ae5ecd656dedc0 SHA1: cc7be1a5c2f30b87244952224a59d15603ec3f55 MD5sum: b87d69fcb19857a2a33f968ffd5f8815 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~nd11.04+1+nd11.10+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~nd11.04+1+nd11.10+1_all.deb Size: 28668 SHA256: 6c16b3aac482cd09a97a080b5a21c1370874d89db73751958c8e987e47d224f9 SHA1: c562abe8878857ad986a9240fa2a5db55b5c20f3 MD5sum: 6e631fecf851be98bd45cd90abab7f1c 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1848 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.11.0), libwxgtk2.8-0 (>= 2.8.11.0), 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~nd11.04+1+nd11.10+1_i386.deb Size: 701624 SHA256: 298a2b5b835d7ffa1f8b496dd42bc31a0848819803e406090a64a1cdc9bead04 SHA1: 9e96da863afa47122da07286d5ec993b23ff461a MD5sum: aa042e1b1a919ab1311f71ebd3bc4ed8 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~nd11.04+1+nd11.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19448 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~nd11.04+1+nd11.10+1_i386.deb Size: 7740430 SHA256: 85f0eb499300ef4c7bc1cf2b49d6335b9bce1ced6edd2e9d3b7fa660500016e3 SHA1: 220352258f702db525bad42485db246357b5addc MD5sum: e6c2290e96ea623cfa8943ee0c957543 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+nd11.10+1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 28 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+nd11.10+1_all.deb Size: 6796 SHA256: 88485e95ac025362071bc727554e2927b890623998096ea4b678f98ad5cd23f2 SHA1: 2ad41e4dbc038d641de8f08ddfec35d676cf4a26 MD5sum: 8f1843ba525ecbc928fd3bf1b3d81444 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).