Package: ants Version: 1.9.2+svn680.dfsg-2~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 41600 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_amd64.deb Size: 12438152 SHA256: b5925c425fd77520cdd17ae23f9953a252b8825607b70301faa63ec81a766347 SHA1: 4bc9650abc7c5413e9b115916e9ca58fd9852a54 MD5sum: 06d49f0b06c5baeb0bf3cf31dd921052 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: amd64 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_amd64.deb Size: 13840 SHA256: e11b171a5cedb006b35b049238cc2e02fbf485d8e8ffc788093644d11586dddf SHA1: a29232e406d6cba9c3b0e012cf025d2a187c494f MD5sum: 9631bbfc0c1758b0ddac731e3b3de047 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18420 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_amd64.deb Size: 7318896 SHA256: 04e4f1af3206a3f0e97e66d36d8ec4ff7879fb7c45c3c371144ae22bf0b5af4d SHA1: fabd88c91d26c6f6311a8a3bb06371c4d9648fcc MD5sum: eb91b3df7fe97bf1c433f9fd123f4d4b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 284 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_amd64.deb Size: 65346 SHA256: 94cda4a6591894194107e4c7b064c7c00c76b714d7eff451fb96da6f740c50fe SHA1: 0d18316dd00cfe509ecd289efed9e3d8ff90bb3a MD5sum: 9eb71f7471369b690dbd358a37283ca1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3404 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), 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_amd64.deb Size: 1383404 SHA256: d982aa8521d648a2bd1995abf2801385fe79a5114042b22a9dac16aabca2b42e SHA1: bbbbc7399a2fbba1e3b4ebd5872db0265cbbc99f MD5sum: b0fcf255eec797a3d685a39c44171108 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 828 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_amd64.deb Size: 206020 SHA256: b8d6b5ab2c7be2018cd5ff7a149de50693061ab4bcd7c06fade11bbe8179ae26 SHA1: c34915e23094e120ac7eaecc445ae3c9761ffffe MD5sum: 5d593943571dac77fc341fdc90d84ea7 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 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_amd64.deb Size: 38454 SHA256: be585d7e2ec8c59f835b8e28647205b3d70b384dbc349233aeeecc0da71d6183 SHA1: 1c0860610ac737db20a67515df88a4bd179df715 MD5sum: 1fa4b4a66e3eeedc60bcf8048c762ea8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 488 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_amd64.deb Size: 161570 SHA256: 6fce43b7fd4d36ded1fb6270349a309f51477494b09763ef15657ab2356d0df1 SHA1: fc5ab627adfe2a982ed160d8e7e562f78ba09de0 MD5sum: edb4cf849f32f337fb04dcf251951fe4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3792 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_amd64.deb Size: 1630532 SHA256: 9171e6e5e5abaf2247c933b91aa5dd6be834fc7a3e44ad1e0afb09fe6fe4afcf SHA1: 8138404c7eb0909b4d7798ca64b97b8cd8f8d13a MD5sum: d0b6a01af6b36c7b0d11309a8674869d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 31980 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_amd64.deb Size: 8513938 SHA256: d86747364567c62f0e317ae1966fe190b5bba249c0cbd08bf2f27a13704fdcee SHA1: 402d9a54bea3e263be141968dfda2f355e201e7c MD5sum: 3fa1f8e23e040c1b7ef62092fa62c700 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+2-3~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-demos, libfreenect-dev, libfreenect0.0 Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.0.1+20101211+2-3~nd11.10+1_amd64.deb Size: 5500 SHA256: 423449fe48aa201d2b65d09e78e6a51d2684023eb55fe9ac87afbae821e5603c SHA1: 2c8125fa354f6f5d88de98aa4f968c21ba253f24 MD5sum: f62f3edafcb49eb511094379df4dd78a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 100 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_amd64.deb Size: 34388 SHA256: d96ad5b4a86ca9bc33093fb614d35d9bfeec544bd1b3716291586d17a6401f65 SHA1: 37d7c541a6b64cd47293ad77d51f036f16ef03f0 MD5sum: ee6efe949fd171536948cdb9d91b05c1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 384 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_amd64.deb Size: 114430 SHA256: 8a974005961366ffeae5ace6c51391be584326300b4e5802421b49e511328539 SHA1: 4e3eaf547ea2bdd5313db04546c6604da4708f02 MD5sum: e10ba02c5e16c8728ff7fab0805ea176 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: amd64 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_amd64.deb Size: 8436 SHA256: 4e6cc9a5d5e541a4f2ba6f1381131f98682419cea21d15cb2893a53a9350eae5 SHA1: 36b51cc7c49efa1422d1db34294663dc07053f4f MD5sum: ae1249f9fbeba62ad17dfbd5863f92b6 Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: ipython01x Version: 0.12-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4904 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_0.12-1~nd11.10+1_all.deb Size: 940196 SHA256: 88f96c1f19a645139ec34b4d07df27c9fcd0ac9e6bc0aa1cf6c8d1dbc29fc5e1 SHA1: 8cd40b029829bc15b58ffce3e9234fcb6aa123fb MD5sum: 38b912e8309a2e60568e2c02ea4237d1 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.12-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13796 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.12-1~nd11.10+1_all.deb Size: 4302578 SHA256: 435c660ac15aed743cf857f18626b135f73ec5a497d0a26ec74c693a95b59396 SHA1: cf78bb2c55f785bb3be87fc10200aefdb9f40484 MD5sum: 7c06be5f8fc3313e0510b32603121d37 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-parallel Source: ipython01x Version: 0.12-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 620 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~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_0.12-1~nd11.10+1_all.deb Size: 116048 SHA256: 912ada0c3fcd0d9cb0624c14823e97e24cbae177397f1b397c8da6454554d257 SHA1: 691a0152dad083dcf5899c4f940e97a0f7528f77 MD5sum: e6bbb521c4bf35a8cf777b2e399e59bd Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the parallel processing facilities. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-qtconsole Source: ipython01x Version: 0.12-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 392 Depends: neurodebian-popularity-contest, ipython01x (= 0.12-1~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_0.12-1~nd11.10+1_all.deb Size: 80496 SHA256: 878b6a0d361e36ebdeccec0ddb1ce79f05190f0abc760d6caef51a11441f8782 SHA1: 9d028403172b5e91c26b3f163dc1c5d85e5f89b4 MD5sum: 0b6bffe7f8312d2224510c9b7b256088 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8536 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_amd64.deb Size: 3670248 SHA256: 7cbba0720b96e4d09c861fa4d6842825ce58d55331bdaca68f7a91818e6d8f13 SHA1: 8c8556c9f77d8b35db01dad1c2c0d8e850770d81 MD5sum: ea6f402509f2af063c2291b0834067dc 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: amd64 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_amd64.deb Size: 23024 SHA256: 75f049cdd6ff121a14033fd16376cc6c9b8afa05308d547596b212ca2ae2882f SHA1: 0118c09a7869ac6a9ace2d215bcb133606de5c8f MD5sum: c374aaba2ffb256885996ba67feefce5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1600 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_amd64.deb Size: 389414 SHA256: 5471578389634592d0fe1ad6f586cdf913b684d4286de702763246ddddab6c63 SHA1: 1daa1906a089cb328e62ef4b896b59844d7ea037 MD5sum: 9b986440c1e3b9d00e93f0567c705520 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 876 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_amd64.deb Size: 307664 SHA256: ca8fa5787a467640d4161e56079541ce8688ca18587365f1345401df2d02bb70 SHA1: 3f08c74021d6e5037a4d57ce6b3322f3f94cd7b5 MD5sum: b32c434564648cfd98d1fb8ae45323d4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 232 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_amd64.deb Size: 68912 SHA256: 2c95319a2dc2cd3bfb8ec513fb925a55d35371dddd3c9f56fe25ad13fe9af384 SHA1: 5c0000e308023e3dce8cdada105ea72b7bc40c6e MD5sum: 4689128ce8008332d9ed1f03d9f46950 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: amd64 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_amd64.deb Size: 17442 SHA256: 5a0f71a631a6656febc007359f131c8641414b3dcbf351d09e083377e19fb0a0 SHA1: f04401c81ec3cbe49ef4afb822ac889f0298266c MD5sum: f3c155a7605546da20e0a48194ae98ed 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, libc6 (>= 2.8) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd11.04+1+nd11.10+1_amd64.deb Size: 38326 SHA256: b568fc58c42d9bc6bbef13a3b16dafbaab78af70e143969fc45245222aeb0fe0 SHA1: f8f3cf72c8728c4a244b8a2d5f76b7bfa1bd26dd MD5sum: b1ea59602f033de34b5ed1734a567c00 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: amd64 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_amd64.deb Size: 6620 SHA256: 68dc52353a968bfb8fd74077ea7f197e46bd8d957e529a709074bc7fc6456d63 SHA1: 49d59b069d4cc0799734837a2f278c323e28932e MD5sum: 63c75350208ff553258eb1d4b51f7d09 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.2.5) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.1-2~nd11.04+1+nd11.10+1_amd64.deb Size: 6462 SHA256: a8c97c45fa81cd36ced502c7c6cd480701ffb0d4d87bfb9f0df00a72a4e4ae39 SHA1: c72bff33c252896d9cf92c807b889694c6c7e322 MD5sum: 2b0c1ea7fa3a01e66d401aca23a85fe9 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: amd64 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_amd64.deb Size: 44306 SHA256: 3cd9968678eb45548a775f8de7ee4a219e3cc64c619c9adace4701c6232acf9c SHA1: 141bdda6ff06dd35f80f85a64ded62877aaa076f MD5sum: a9b7397b0265292cf1dcc724f5ab35f0 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: amd64 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_amd64.deb Size: 23636 SHA256: 5a5cd2bf9c3649e4fc8ed46c6ec1a30bb1c276440f66a4b9a409f0c763f6a505 SHA1: 9defe86952e64191c593d6341a25cb7eb00c85be MD5sum: 50388915fee4bc03428e1c3d8a84baa5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 156 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_amd64.deb Size: 64482 SHA256: cfc81f9fd18c7e6db734ac31709cddcb041568aae2a1adeb1c4c5450cc4df797 SHA1: 9c1bd46a8c4f7421f29f3b561ae4e45b9b6bfcae MD5sum: 5a833e95586a35b6d3c4892a35571ac5 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd11.04+1+nd11.10+1_amd64.deb Size: 509910 SHA256: 70a7e9008f9c0277cabc3154dd6b2e34e0a6eaea47758d4bb8a9c9752681dcff SHA1: 25d70adf00d024090021eb90efed8d661292d188 MD5sum: f7e595f4133327b51dd66d0772445f06 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+2-3~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.4), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.4.0) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+2-3~nd11.10+1_amd64.deb Size: 27382 SHA256: 0e3a9e5c57f41ce4574bb3cf417a842dca3d780071e1477508bbf144b2c98bab SHA1: 99c672d8ebc705c930bb66150a800cf4e31b739d MD5sum: 1e26034f3aea61bfb57fd4769e73ae2e Description: library for accessing Kinect USB camera -- demonstrations libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package includes some example programs for kinect. All programs start with a freenec- prefix. Package: libfreenect-dev Source: libfreenect Version: 1:0.0.1+20101211+2-3~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+2-3~nd11.10+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+2-3~nd11.10+1_amd64.deb Size: 23854 SHA256: e7163223f34813e4f9c4c2b113ac90404722043e8ef1f3470a1b685e97e65c77 SHA1: 8bae33893b2900cc08ecd78c99c60fbf206e12fb MD5sum: df1e52de082593b42d1d67aecee79a1f Description: library for accessing Kinect USB camera -- development files libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect0.0 Source: libfreenect Version: 1:0.0.1+20101211+2-3~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+2-3~nd11.10+1_amd64.deb Size: 28132 SHA256: 242e53abbfaf0f7c9c65d2aa8c5476be7be707f74b3ff46171e643d6a921d9c3 SHA1: 2d1f85db6828e9fc4098ed88e1d142e582a43eb1 MD5sum: 3f03724e637c6d0e5e4d97b45ec3b921 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: amd64 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_amd64.deb Size: 18580 SHA256: 80eb890fe9b0f84957a2f9f7d4158af8085eca355c7a6121709c91c3a4a211d3 SHA1: 12175ce3bb6285e8ed50ff39141bd07fd4284bef MD5sum: 28f628637982c74b1c6002b904546060 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 308 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_amd64.deb Size: 97718 SHA256: 7e01c9c8446c8f305998074e645138a58844a92692bd54509b9627938d3fe03c SHA1: 7b0ea888f4c2e763af25eac8ad7392475e3be834 MD5sum: 4c20cd5c3a4cee5d1f360ecf73230033 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4848 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_amd64.deb Size: 1353220 SHA256: 6b9bb8b81a5f0a7d6783eeb5e2ee2f313656129e6653282d3749867c99db7e95 SHA1: 079205a71a53826a89ca4b9307bee843ba88406d MD5sum: 213c93b9eecd172dc21c23a64926852b 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 436 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 116834 SHA256: 667cf9da1f5c01e459cdd0eeabcfec11110435b64c0ea3a89540e4909a490ec9 SHA1: eaca1cc91a57272cb5bb0a017017f12165a16a6c MD5sum: 7c92c96fbdbd34f3ca211d93bfd5a13a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1516 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_amd64.deb Size: 244838 SHA256: 3d1117171c241f9bbcaa54084d538cf8a62aefb72226172ea76d95afd7d2ab9a SHA1: 74b26a0ba08ea8f9728516df1c97a8395b674342 MD5sum: a0de67c6e1baf510ea102ad75af6b099 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 384 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 103842 SHA256: dc9bbcba5b2dcb53ee567b34b882fc0941dbf99b221fcd85b48812bdb47effe7 SHA1: 9979b8021dbb583d6daaa625f5a54220c6498410 MD5sum: 20f78c367a8acfc69fff132e1b73f9f6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 524 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_amd64.deb Size: 101914 SHA256: 85cc0c95654fccf0ffc35fe9abb32c3c90e9920b17e73ac2543c1e79eaf20f1e SHA1: 5145e9b684bf9ddad3c7681f6232f1f1c4885aa9 MD5sum: fdf4ff46d8b2344427edf2f664826cb0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcairo2 (>= 1.6.0), libguac1, libvncserver0 Recommends: vnc4server Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac-client-vnc/libguac-client-vnc0_0.4.0-1~nd11.10+1_amd64.deb Size: 9418 SHA256: 6815d21141187d886d4713a8e8a9ae4db3c01e2b9d042fa2d448aed55cc806c4 SHA1: 8b083fa3be91f2e6b9394ffc5379a15ec99fa536 MD5sum: ed091dcde2a5a804add77f1e855734b1 Description: VNC client plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: libguac Version: 0.5.0-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, libguac2 (= 0.5.0-1~nd11.10+1) Conflicts: libguac1-dev Replaces: libguac1-dev Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libdevel Filename: pool/main/libg/libguac/libguac-dev_0.5.0-1~nd11.10+1_amd64.deb Size: 21592 SHA256: 36039c22c96c0257e686353bc4c0b34e5df9d7f6d8132fe08bef441f2bc125ff SHA1: f57d0c06ec7d50ea0842691c0d73e688620cf71a MD5sum: f3600e951b86f78a78d692948afe61fc Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac1 Source: libguac Version: 0.4.0-1~nd11.10+1 Architecture: amd64 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_amd64.deb Size: 11734 SHA256: e38e0d0e52f5158db9000e1cd404962b00995ec04120557871c647b0da71b0e3 SHA1: 7abedcbea2f0937595457f1db0c0daadf5c056d2 MD5sum: 8b31b2091b8e57f197c506101cd7075a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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_amd64.deb Size: 18994 SHA256: 7a2a42c60981d0d72e442087360f1be3b00904d65a2292c22627c9ae8e2f562c SHA1: 8313a5e2b47051e7b92e4be20fa5315c6cf7f9a8 MD5sum: 5e84b4aa9dd548a7d1f79745a90fa822 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac2 Source: libguac Version: 0.5.0-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 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/libguac2_0.5.0-1~nd11.10+1_amd64.deb Size: 12896 SHA256: b2fbeb73854474f440fbb57c176084b760a7b3a4ab0711a589591dda60892630 SHA1: 5775e47e1b69d69c719ce13c2d13b53f5efa8bc3 MD5sum: 2d7cb5929ddcc1151d663839450721f7 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: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd11.04+1+nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd11.04+1+nd11.10+1_amd64.deb Size: 7832 SHA256: 9ca2a0ab72dadcf6f74c3a4fdd1697e0a03ecdd83fc861343f70e15a34da3576 SHA1: ce10eff8f211042fe8f197e46f64038d8386e719 MD5sum: cf9886699c12280545964f6b05fbdf82 Description: PAM module to move a user session into a cgroup Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This PAM module will move a user session into an existing cgroup by attempting to match uid and gid against the defined cgroup rules configuration. Package: librtfilter-dev Source: rtfilter Version: 1.1-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-1~nd11.10+1_amd64.deb Size: 12554 SHA256: 9caaf06e910afcc712b2379eca5cb27359eb12d8403c2ca7307cd07cac4b5061 SHA1: aecc140c11650ef25c24823b4b1a22d294f769a0 MD5sum: 884117d6c6a57c10045b22e2b82a83c0 Description: reatime digital filtering library (development files) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package contains the files needed to compile and link programs which use rtfilter. Package: librtfilter1 Source: rtfilter Version: 1.1-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-1~nd11.10+1_amd64.deb Size: 23736 SHA256: 924eb685295995c280dc42d71e366446a2356c1a17965a405583009902504b7f SHA1: 41f4bfe5c5548657e553dec2f1ad8c575289712e MD5sum: 68df21ba0a6097330a7e4e86d4763f12 Description: reatime digital filtering library rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). Package: librtfilter1-dbg Source: rtfilter Version: 1.1-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 136 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-1~nd11.10+1_amd64.deb Size: 37656 SHA256: 6523a9e1102912578ad12a91e449b6d1fd1ab5d2a0c757df3f9db285a09bb0c8 SHA1: 7c3570a1ac443a078d14e4e05bf1b80b43e669c5 MD5sum: cd2760c984c9fd10e7caefe94636f8f8 Description: reatime digital filtering library (debugging symbols) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package provides the debugging symbols of the library. Package: libxdffileio-dev Source: xdffileio Version: 0.2-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.2-1~nd11.10+1_amd64.deb Size: 27716 SHA256: 061664da53564a38f0091f3d7c7ba31a02083d8a0581715b591411d06f156e1a SHA1: 91cbc83b813d142d2e3e93c3b980127973896a81 MD5sum: eafbc511a44af1fbe9ed50dce501205e Description: Library to read/write EEG data file formats (development files) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package contains the files needed to compile and link programs which use xdffileio. Package: libxdffileio0 Source: xdffileio Version: 0.2-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libs Filename: pool/main/x/xdffileio/libxdffileio0_0.2-1~nd11.10+1_amd64.deb Size: 30376 SHA256: 509f4a22ceddc54be8a9ce21bc4207777895a0600f4bd7f4b8c1ee7cd73a0168 SHA1: 7096e091335a46aca421adf0ebe2432f5d6fbba5 MD5sum: 5d4c30e53b3d5c515d290ded146f5932 Description: Library to read/write EEG data file formats xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead of the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. Package: libxdffileio0-dbg Source: xdffileio Version: 0.2-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 196 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.2-1~nd11.10+1) Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.2-1~nd11.10+1_amd64.deb Size: 62846 SHA256: 9dfc9954147928f8af2be73f13756451fed846475594d067dfae71e8c291f4ff SHA1: df589302f01a95f86c1f46d797cf26c71c964f66 MD5sum: 858e35cd1dc19f721fd4688184d94efa Description: Library to read/write EEG data file formats (debugging symbols) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package provides the debugging symbols of the library. Package: matlab-support-dev Source: matlab-support Version: 0.0.17~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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2024 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_amd64.deb Size: 730762 SHA256: 7c5444a5cf982a6e047a40a9be1f22818ecaf8fc9364af6fd9c80a5178a0f214 SHA1: 8d8a2fef6e3bc86a4f5d478c7101489379bf163d MD5sum: d5cb6fbeef1ec7127571e7c6a839c043 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7304 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_amd64.deb Size: 2284336 SHA256: e2199a61a3b56262daad3a49e58e72e81ed4d25785bed489453167a149e01fc7 SHA1: cf1c476da2c1e361d5d2cb925f4ffa27f7de0ceb MD5sum: 7061a841007dba716523f81f0410631a 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: nuitka Version: 0.3.18+ds-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1368 Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1), scons (>= 2.0.1), python (>= 2.7.1-0ubuntu2) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6) Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.3.18+ds-1~nd11.10+1_all.deb Size: 226128 SHA256: 648ba061e41baf4362e1713a755589c546f79615207a748cddc319f330204545 SHA1: 912f834ce1c7a49db9badf39297f4a7a6e602faa MD5sum: 9ccc6f68d2f86ae830394a829460e935 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class to pure Python objects at all. Package: numdiff Version: 5.2.1-1~nd11.10+1 Architecture: amd64 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_amd64.deb Size: 447442 SHA256: e28207454ee76080d872597889c3ff4b976bda05dd923d3bf75270fe9d361c00 SHA1: 2cd0b56fcb5b751e16516a14ba13d096613e2490 MD5sum: fa3689dba54cfadbb737c83220582a09 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: amd64 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_amd64.deb Size: 17278 SHA256: c2d4c5fbb66f521fb3be43ece1677ab042b6fd745298e3b9508902b3dbbf4ba9 SHA1: 01d091cf5104931f89997f46a5fc038542bd9e80 MD5sum: adfb87f4464f457d8f7d00c57757981d 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: amd64 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_amd64.deb Size: 113752 SHA256: 1e8fbf14f6d2dd89ada17a65ba33364ead4c62016942429cf3cf6a66064564e6 SHA1: d5175e461bcd6135b9f0ca9843d0013a897caab6 MD5sum: a059b141474d5b17e40b68b38df23775 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2376 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), freeglut3, libasound2 (>> 1.0.24.1), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgl1-mesa-glx | libgl1, libglew1.6 (>= 1.6.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libopenal1, libpciaccess0 (>= 0.8.0+git20071002), 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_amd64.deb Size: 766752 SHA256: e518d8d0db149574fffd2f476c9bb3178ac6047a3501a3d0c34edad234336b6c SHA1: 7b7aff7016e7a6e88db557eadaeca209bc1c98cc MD5sum: e12e72d746ce453869d7577b34f208d9 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: 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2460 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_amd64.deb Size: 767096 SHA256: 916d0cbd5b9c9fb5a3282c68b982c707253d5f56648b01894b741c2807378acb SHA1: 3234b86241f40a0416cb94b1d70df0ccd388f8c1 MD5sum: 04fe236692d77f50c4f5e114561534f4 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 204 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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_amd64.deb Size: 61140 SHA256: 3a4a9c323cb10aea03574b3e2b513872121f72e1b3271c0a65090dc6018e6b0b SHA1: 4832923b7e5a26606e63c9e6599b55f88291f673 MD5sum: fdd77da7bc39ffd867707a660d342ec0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 220 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_amd64.deb Size: 52900 SHA256: 3ec9ee9e9a6be6073760269567de24b40fe964a04d17a4351d166e9b84d97b57 SHA1: aff5f722058280dc9e5070e3d00d829489f3af57 MD5sum: 1524ebfae5ead45dbe6d9279e1ee20d6 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.3.1-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2096 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.1-1~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_1.3.1-1~nd11.10+1_all.deb Size: 393380 SHA256: 39e34f533b68c800fdad9ee651282a93ec524621a0aa8975f181991717f5be8f SHA1: 7ec8ed3701b19b404e19182c64faeccc32299f0f MD5sum: d1f1c658c51fa9e039e369a79a201057 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.3.1-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6104 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.3.1-1~nd11.10+1_all.deb Size: 1956946 SHA256: b31320d03ed29e69928a041f3ffd026e027f47a750497037261481bbb8ef1f34 SHA1: 70496141cc05a3c5eafb1dc9e0e81145114f567d MD5sum: 3473eb842f94718d8e0e367bce0e9dbb Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.3.1-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 292 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_1.3.1-1~nd11.10+1_amd64.deb Size: 105764 SHA256: eb39280ce4385c18f8d8b22f9cae8f5e21a28cd0164e666711c0d57092861ed9 SHA1: 0f0cfb3bea37c39691f261c9d6a8188f66b2595c MD5sum: 4d63edfcadb9e7344b3c57daff9965f3 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1124 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_amd64.deb Size: 421382 SHA256: 1662618ef075384312ef114e6a593ef10f78d30e50c5dde4693b7ee33cba40a8 SHA1: f98f33f9bc8963834e372e957702d124913f879d MD5sum: a31020e9b56441cbf800362d79241d82 Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.6, 2.7 Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+2-3~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libc6 (>= 2.4), libfreenect0.0, python-numpy Suggests: python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+2-3~nd11.10+1_amd64.deb Size: 37394 SHA256: 83cd3637a61206f49602f95a92e5d8f857ed0e8654b7883238446987647547cf SHA1: 209aaaf465d8923b0ec26e846693b25e89a8bc6c MD5sum: b847de0dddce02ea90214505c1a1f7d1 Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.6.0~b3-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 248 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_0.6.0~b3-1~nd11.10+1_all.deb Size: 50384 SHA256: 37664893661beda816f73cd4b11b0c501fe260ffb9f125d52b7c8921e661c719 SHA1: cfb5ed12701f5bae95efb2cb540aabb842a5aa48 MD5sum: 9e756903aa5a42791f0f10ddefad7873 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2208 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_amd64.deb Size: 742118 SHA256: 7a1241061ee5d2c051ee23a3f128ee1e02728e62bc213700ec9f058db423cccf SHA1: 8f94b3c7e57de4449f1e51d23ee53fa021adac90 MD5sum: faedfc28bd97d3f86f369a3799295f6c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5916 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_amd64.deb Size: 1462780 SHA256: d75255cafd81ed1029532f9d0af6958766a7e687cfb5a3afa8f2f5bb3808ff27 SHA1: ab43dff3ee31aad2a7f4a65d0f58c20f2138545b MD5sum: 2ef85588ba2588d09e3288d47d731ce2 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: 2.0.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4624 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0-1~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_2.0.0-1~nd11.10+1_all.deb Size: 2319796 SHA256: 50292b2f8a11bde12589f92b5257404772d66b66051e2e1d2477487d3f90a8b7 SHA1: 1ccc2b881f05f53b4057fa19d69a09626e9c42ae MD5sum: 6a5daf3fda464aa6e71abe784d4d6cb2 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.6, 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.0.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24164 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.0.0-1~nd11.10+1_all.deb Size: 4536056 SHA256: 6bfbc12b018478639525975eaf8f18ff76e3f729ac366201550da2b7fd19a1d7 SHA1: 8cb81da4855e19c9e6436e7b178f872b74947914 MD5sum: ee1f01fb76282d305a6e821549b512ae Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.) as well as example scripts. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.0.0-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 216 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 Provides: python2.6-mvpa2-lib, python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.0.0-1~nd11.10+1_amd64.deb Size: 72806 SHA256: 58ec603bcb8f38cac6e469f5ec0631700b673a8a96e74c0669727e6966397012 SHA1: ae2a1231ffe4f06efd6332c581bae00a43ec8495 MD5sum: b710099fb23c32831f4abad52664d5e7 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.6, 2.7 Package: python-networkx Version: 1.4-2~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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1480 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_amd64.deb Size: 375542 SHA256: bc39b5e20b0ff9bca4edb6dba42de11c917c38cf9ad78a15173ade5ca110b839 SHA1: 72f50b6357f14355e0a212dd77df0db76c1030ab MD5sum: 699c3266a6e9900a0fc46d3a63f8b87a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2672 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_amd64.deb Size: 1034424 SHA256: 5a1cf6dcbb4e36e93edecc3fe81ce43890ad327b28d674b362a900ad69074d11 SHA1: c2ca28777f79d1b3bbba62499a910689e996d525 MD5sum: 48743974ea867e4c3a37ef47266879bc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2920 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_amd64.deb Size: 1165736 SHA256: 31de49e6c56efa7a2819b060df87e7f79061fbe53a82d5d54795433465becb9a SHA1: 1887eeb5a89e75bac8b63016363b246f165640ad MD5sum: b3427fab559ef5bb88553cb19957bce1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2128 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_amd64.deb Size: 779764 SHA256: 39eba8584219b4ebc9812ab89af22d890936147ddc603b187d00d09983d4824b SHA1: fbda7b81da3093bb4973c9d4e57eea5ad165a40e MD5sum: e834d0109376028ee0d6c64929aeb810 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2448 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_amd64.deb Size: 664974 SHA256: 24ba8ecf52a6d1518607a078562a7d7ef4b6dde284459ce1eacc4e7d202a16f3 SHA1: f8b1e84b4328e04e596ae8429044814c1de5ecf9 MD5sum: f5288e8057b504b500792a4492169c02 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: 0.10.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, python-sklearn, python (>= 2.6), python-support (>= 0.90.0) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.10.0-1~nd11.10+1_all.deb Size: 19852 SHA256: 2f2a31c4cf4b28a332e12e00ad5699ae29d90feaa8503f0bc2595ef91d5bc78a SHA1: 0c5278354fb35c63f1169fca2ae1e81bde445aad MD5sum: 09bb9848498c11172d90d5bdc69ef63a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2616 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_amd64.deb Size: 1000862 SHA256: 79ef2329e418d531e8767ff28105f6c542cc88519de352c1704d6f059b1aefbf SHA1: 4eb2a2739bf19a703dc87db3ec53681cd9ed881a MD5sum: 7758c1e4235aa9e11d61b510b561f220 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: 0.10.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2792 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.10.0-1~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_0.10.0-1~nd11.10+1_all.deb Size: 833556 SHA256: 882c5b307e123fb0d14309b9a1dee0950ceff59dd5a9b7879271274fb905335b SHA1: 0c3d0f84bd3f6a98a8f5f0664097ebf637b1a158 MD5sum: 37b4235576e8210d70eea718c43f7c87 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.6, 2.7 Package: python-sklearn-doc Source: scikit-learn Version: 0.10.0-1~nd11.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23884 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.10.0-1~nd11.10+1_all.deb Size: 13410826 SHA256: eff70f32f9a2beafdfbbc3ee7d9f2fbd50c1ca17a289d4132d459cab97d5651d SHA1: 26df87cfe1f24c5eb740f5b604f1695ff8e4b2c5 MD5sum: 4cd06f1573bb60441aeb92f4bd7aac07 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.10.0-1~nd11.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3324 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_0.10.0-1~nd11.10+1_amd64.deb Size: 1232568 SHA256: 62d3639013f4d62b089ee44044358ec53215c2579f2b3f8f867a34bb551636d4 SHA1: d24f6b5bbea4ae6743e17c36d782c674dbf8882e MD5sum: 15f1f6cf41b0265f2b26118892c1bde9 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: amd64 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_amd64.deb Size: 199620 SHA256: cda7d8aa84fecbd61edcf2c7581c3de73b92f2fac50651e6e8e233dc5ab58170 SHA1: 7ace1517fe0b92488de6e356c5f55fa0aad296a3 MD5sum: 5d9a795aef70fe88aa5d8850bd0964c4 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: amd64 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_amd64.deb Size: 223568 SHA256: b5363d25be84437f2585a6ec8163f59e73f65d9e2d7bf8f89c64b9e5a4ad2f96 SHA1: f52bcb68e2759594b343b340fb13f2d3f260eaa9 MD5sum: adbd2f498e02b44be2bd0175155884bd 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: amd64 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 2256 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_amd64.deb Size: 392414 SHA256: 13756fb6e30c1fc80d65022d0caaa42fdc545d679a8a68e05d2203c3ad060d6b SHA1: b7d3d5ce2ee20ff15a2f2f0911e489515728dfe9 MD5sum: a597503c21e2f9237d2bbaf428c573ca 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: amd64 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_amd64.deb Size: 133260 SHA256: 3e1107dea4689ea66598f414d1979c8f5f70c8655c203fd37454314419a66078 SHA1: 0935f09ac164df60885d4c103826104f584cff70 MD5sum: 896aedaca7cb28db3e45990c933114b8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1988 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_amd64.deb Size: 712774 SHA256: b45e6b8283b636f20c8568fdf8961650c432f7d9cee14701a11e53e9dd8642df SHA1: fd8cb0bc466efa354d1eacad92dfcfe438df5fc3 MD5sum: d080e892c811923c33eeb7284506b6d6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24760 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_amd64.deb Size: 8265656 SHA256: 4d5e125915c47c7e532e7559c421eb4d4a4f73e6d34d76f2cc6490c01b2b0bdb SHA1: 0198530d8c7e1aa70911191296f01fafb370680b MD5sum: 0a934cb72bd213ac0b1390a5a2c9a4b5 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).