Package: ants Version: 1.9.2+svn680.dfsg-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 35720 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.18, libstdc++6 (>= 4.4.0) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-1~nd60+1_i386.deb Size: 11192930 SHA256: 568c4339f13ba27662bf9de41051a69309240b2c528e82bad46282694494f2c7 SHA1: 14392177124e45df7b34f20231031a8dc39395de MD5sum: 9be6a0f0cd11b0de92e0bda7260101c0 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). Package: arno-iptables-firewall Version: 1.9.2.k-3~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~squeeze.nd1_all.deb Size: 132476 SHA256: b002efbc460e228ef300147169187793cc9cc8b36e7acf807567d35aa8d56099 SHA1: 7945add5a3b0968d8deeac27bb6d5bdf667ff03a MD5sum: ebcb9a6d4f275258f76616360ff739d0 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: autotools-dev Version: 20100122.1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 216 Depends: neurodebian-popularity-contest Enhances: cdbs, debhelper Homepage: http://savannah.gnu.org/projects/config/ Priority: optional Section: devel Filename: pool/main/a/autotools-dev/autotools-dev_20100122.1~nd60+1_all.deb Size: 72966 SHA256: dee3f923f4e6856aac8efa5aa8c890af4466679721b9a2dd03977c7bddf0d857 SHA1: 2c2a0419c7324111348c91772971ffef898ef835 MD5sum: eab0255d3b1d7620acccb2f6e01b667e Description: Update infrastructure for config.{guess,sub} files This package installs an up-to-date version of config.guess and config.sub, used by the automake and libtool packages. It provides the canonical copy of those files for other packages as well. . It also documents in /usr/share/doc/autotools-dev/README.Debian.gz best practices and guidelines for using autoconf, automake and friends on Debian packages. This is a must-read for any developers packaging software that uses the GNU autotools, or GNU gettext. . Additionally this package provides seamless integration into Debhelper or CDBS, allowing maintainers to easily update config.{guess,sub} files in their packages. Package: biosig-tools Source: biosig4c++ Version: 0.96.3+svn2677-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.0), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_0.96.3+svn2677-1~nd60+1_i386.deb Size: 13694 SHA256: 5ccd2e3e80a95fa0f45f2be6b4e53821150fdb2f429fd2a16da56d3c2d222cee SHA1: e56918a5302fec75430ac5dcafca45e3c975d0b4 MD5sum: 4ce7d49ce1edf3a689c360b59bc65079 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19156 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvtk5.4, 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~nd60+1_i386.deb Size: 7481880 SHA256: 1b8d80589fbe158f6dc83a3a8f9af8bac04f3524b24d8156b9e1a5dc6be0bb60 SHA1: fc24970ca85bd711f3cc012681ef4303b9a82d09 MD5sum: 21b9a963312db88fd24f99d93499bf8e 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: classads Version: 1.0.10-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libclassad1 (= 1.0.10-2~nd60+1), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: misc Filename: pool/main/c/classads/classads_1.0.10-2~nd60+1_i386.deb Size: 36646 SHA256: a8a38fa338df426524cd1de4efb918a1bea4d2296b4dba127618d19356bfd785 SHA1: 7742e477419c7112f5f3802b429d9f1db8fb32f0 MD5sum: 67d2b74e4132d9a7fb1a08a42a6793b2 Description: Condor's classad utilities A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides command line tools to manipulate, test and evaluate classads. Package: condor Version: 7.6.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 11112 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.7), libclassad1, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2-1), libexpat1 (>= 1.95.8), libgcc1 (>= 1:4.1.1), libglobus-callout0, libglobus-common0, libglobus-ftp-client2, libglobus-ftp-control1, libglobus-gass-transfer2, libglobus-gram-client3, libglobus-gram-protocol3, libglobus-gsi-callback0, libglobus-gsi-cert-utils0, libglobus-gsi-credential1, libglobus-gsi-openssl-error0, libglobus-gsi-proxy-core0, libglobus-gsi-proxy-ssl1, libglobus-gsi-sysconfig1, libglobus-gss-assist3, libglobus-gssapi-error2, libglobus-gssapi-gsi4, libglobus-io3, libglobus-openssl-module0, libglobus-rsl2, libglobus-xio0, libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.7dfsg), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libltdl7 (>= 2.2.6b), libpcre3 (>= 7.7), libssl0.9.8 (>= 0.9.8m-1), libstdc++6 (>= 4.4.0), libvirt0 (>= 0.5.0), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), adduser Priority: extra Section: science Filename: pool/main/c/condor/condor_7.6.0-1~nd60+1_i386.deb Size: 4320282 SHA256: 52200529741ed077cfbbbceb113d7b8744c8544ec2836305cb56da4453ca1eff SHA1: 03d0d57c5acb799950bdc4ad86326db13de30857 MD5sum: ffc10c4ca972abb657a85db1225b8062 Description: workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . The Debian package uses Debconf to determine an appropriate initial configuration for a machine that shall join an existing Condor pool, and moreover, allows creating a "Personal" (single machine) Condor pool automatically. Package: condor-dbg Source: condor Version: 7.6.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 31396 Depends: neurodebian-popularity-contest, condor (= 7.6.0-1~nd60+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.6.0-1~nd60+1_i386.deb Size: 12327402 SHA256: 728ca3c14f29fc026d132b84424c7822d26ff4d3dbd3fe972c6109905214fb18 SHA1: 1cc7f7265dca90d70953a9304892ba21c918422a MD5sum: f2a387848910ca787593704b1564286c Description: debugging symbols for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-doc Source: condor Version: 7.6.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11748 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.6.0-1~nd60+1_all.deb Size: 5952904 SHA256: 29f82d877503dd97889104ff83cc1476db4e32c48e01a0df77c60f72c5e3517f SHA1: b43e0237083387ea947e6a85cfd1a1c3a755eb45 MD5sum: 2e315ab49113528625997cda8db4cc1e Description: documentation for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: connectomeviewer Version: 2.0.0-1~nd60+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~nd60+1_all.deb Size: 1354956 SHA256: b0950f7c42d584f3476f79920cdbfcc342d10563f1b06b88acaab7263c36add6 SHA1: a713af7f9f16e3b54e22916ee6498bdaafebd798 MD5sum: 02d405b1f02ad49b4c2192af7ee48f1b Description: Interactive Analysis and Visualization for MR Connectomics The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics. . Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit. Package: coop-computing-tools Source: cctools Version: 3.3.2-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3264 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.21-1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Suggests: coop-computing-tools-doc, condor Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.3.2-1~nd60+1_i386.deb Size: 1237612 SHA256: 06d72fc3e15be3814929e826334a9fb8a16c5bee82a28711d6bdfb82ee9af786 SHA1: 4b89d88d405cb8ef5d16be51ea6688b3f9b65e54 MD5sum: 8612f78caa698a2022d95e1d65bb9fd3 Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.3.2-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.3.2-1~nd60+1_i386.deb Size: 213172 SHA256: d08c9a0af70db932b579ea688127792369f609fb1983ff3fa1a91cc0dcd1a148 SHA1: 51a0d1ba8465701e5d8071629ffda34f956fc082 MD5sum: 895af351b9f6bd2111b40e8e74d2bcfd Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.3.2-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2404 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.3.2-1~nd60+1_all.deb Size: 261104 SHA256: cc5bf58997f3f489256882bcda11eaa6b4a04057abe172f1f769e59056aa7742 SHA1: 903fb3021444602b151296e4580c39063e44ab08 MD5sum: 14c3aac2ecf35079e30b9c9c802c833e Description: documentation for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides the documentation (manual and API reference) in HTML format. Package: cython Version: 0.13-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4580 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3.6-6~) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd60+1_i386.deb Size: 1117358 SHA256: 1c0d771c94c4672bfe3002e50e45071803cc46fd3e965ef38c9936aeaf5dd911 SHA1: fe682d833f41d773c6efc835fa3ffd2a12160580 MD5sum: 0e0639397070f5d486c97ff43efb81ad Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7672 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), cython (= 0.13-1~nd60+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd60+1_i386.deb Size: 2920676 SHA256: 52e24849159ed4815448591b67613978d797d1b0ef8c15e7e840ff3a8c168147 SHA1: 4c858cd3133a6fc782aab05a5166ac20a0b082f2 MD5sum: 0ebc710c64b47d7c5c297abd63577833 Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.5, 2.6 Package: debruijn Version: 1.3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.3-1~nd60+1_i386.deb Size: 31900 SHA256: 1c4c1806f79c5f99d37ec496d68f4fb57454585f7461013da39f1b42c21a64b1 SHA1: 2148820a3ed6c81178b3e5023da09c923af447f2 MD5sum: 7e8ae3266dd6a70ab4541febe8a0af1a Description: De Bruijn cycle generator Continuous carry-over, fMRI experiments present stimuli in a counter-balanced sequence, meaning every stimulus precedes and follows every other. Higher level counterbalancing is useful to guard against some modeling assumptions of the approach and to test for the effects of stimulus history and context. Sequences that efficiently provide this control of stimulus order are called de Bruijn cycles. . This package provides a commandline tool to generate de Bruijn cycles. Package: dicomnifti Version: 2.28.14-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 476 Depends: libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.4.0) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-2~squeeze.nd1_i386.deb Size: 146588 SHA256: 28fa96633deeb30dff4a871cae75b831684ac8a6e0bbb5e8dacdfa3f964980d2 SHA1: bf3815e66ca5afc2be8169706ced47978c021215 MD5sum: e13e3ee31ea0cab9865af7a1202cd871 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3624 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_1.2.1-2~nd60+1_i386.deb Size: 1558742 SHA256: 6ffc73f8308665b968dda6da1ec9edc64e5fb089ca5f81c1f06339d529ff3d57 SHA1: a1d106a8a0b42c9d62961f60c62659123ded5599 MD5sum: c8965f5e2f9a19d82fa0792f5903a30b 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17492 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~nd60+1_i386.deb Size: 6120178 SHA256: c6672bc311263bdd9e2c9a6ae001680644df33d41b280d8da0f5fe3c05a0c550 SHA1: c86d0352695682118fb5d1fad1355adbf3d9ea31 MD5sum: e58cfad3577cffe559da6e6a3c712acb Description: Debug package for dmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Windows applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: eatmydata Source: libeatmydata Version: 26-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3) Provides: libeatmydata Homepage: https://launchpad.net/libeatmydata Priority: optional Section: utils Filename: pool/main/libe/libeatmydata/eatmydata_26-2~nd60+1_i386.deb Size: 8010 SHA256: ccaa8f8343c96056f26d8db4c18711c6b8804a0274c355bf2937d3f891c07842 SHA1: 1867693942c0f6f55914925762ebeab9ac32954b MD5sum: 6e9eab3835add9a2eac0f9e20ff31aa4 Description: library and utilities designed to disable fsync and friends This package contains a small LD_PRELOAD library (libeatmydata) and a couple of helper utilities designed to transparently disable fsync and friends (like open(O_SYNC)). This has two side-effects: making software that writes data safely to disk a lot quicker and making this software no longer crash safe. . You will find eatmydata useful if particular software calls fsync(), sync() etc. frequently but the data it stores is not that valuable to you and you may afford losing it in case of system crash. Data-to-disk synchronization calls are typically very slow on modern file systems and their extensive usage might slow down software significantly. It does not make sense to accept such a hit in performance if data being manipulated is not very important. . On the other hand, do not use eatmydata when you care about what software stores or it manipulates important components of your system. The library is called libEAT-MY-DATA for a reason. Package: fail2ban Version: 0.8.4+svn20110323-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 596 Depends: neurodebian-popularity-contest, python (>= 2.4), python-central (>= 0.6.11), lsb-base (>= 2.0-7) Recommends: iptables, whois Suggests: python-gamin, mailx Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.4+svn20110323-1~nd60+1_all.deb Size: 97978 SHA256: 9917cc19fa2afe2f625983920944b213694e358364265dfcbb46fb940dc9822e SHA1: adeffffc2e35f7dbb494eb5ea43061cade49a8b9 MD5sum: dd93359047596c5d23f660c214a1cdc9 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Python-Version: current, >= 2.4 Package: freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 32 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+1-2~nd60+1_i386.deb Size: 3118 SHA256: a84315797e348ca61e8939d70cba40201c6aff0fb7f5c801e38b47c39e5e4c03 SHA1: b00bfccc9650e39be43a09d1fd9c1e67fe19233c MD5sum: b1895becfab274e8c3ea4d406229dd62 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 3864 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8b), libqwt4c2, libstdc++6 (>= 4.4.0), libvtk5.4, libvtk5.4-qt3 Recommends: fslview-doc Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_3.1.8+4.1.6-2~squeeze.nd1_i386.deb Size: 1493774 SHA256: a124d69a68e3c33e3d872896150655898e2e0c7c6045117e18f8130fc126f4c2 SHA1: 38bea305cfeb6ff7b7cc9819573f0ded042b95e2 MD5sum: 559f71c004dce3aa4773767a5defa231 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3216 Depends: qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.6-2~squeeze.nd1_all.deb Size: 2378936 SHA256: a8fbd782cbb61ed77104e5e28da08040c63de551af6dda1e6ee41a098b40dcc7 SHA1: 565f0f4026969f9fa84091efdec611106608ebf8 MD5sum: f3f752fb3534ec465e7f6c98503ec376 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gdf-tools Source: libgdf Version: 0.1.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-program-options1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.1-1~nd60+1_i386.deb Size: 39056 SHA256: f9e87ada2ae22036cac65dce1ef9565f607ab4a1c6b44064bc530dc90ed2d093 SHA1: 581c7afc353b13afd143654cb1bd10a83b9f7a7d MD5sum: 5fa43a70ec35fff13d94701e84a21fe0 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: gifti-bin Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 124 Depends: libc6 (>= 2.1), libexpat1 (>= 1.95.8), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-1~squeeze.nd1_i386.deb Size: 28730 SHA256: d39ded92265112712c77d9117b70fa915b56f1cc3681e498c155754ad64cdc58 SHA1: 410001a3b15e8fd43a44d6d30b9ceecbc7762be7 MD5sum: 45401b0fff219489478c581175d6a8db Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: itksnap Version: 2.2.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8192 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.18, libstdc++6 (>= 4.4.0), libvtk5.4 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.2.0-1~nd60+1_i386.deb Size: 3651816 SHA256: 7f11cdb7da92f4f809820fd8a40ac749bb857f96fbd81328459643298ad229d8 SHA1: c2a7f3c83e4ed9673fd86d191bc365b4e21e741d MD5sum: d7081814d1c2286f9f09aab327cd26ec 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: kbibtex Version: 0.2.3-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 2548 Depends: kdelibs4c2a (>= 4:3.5.9), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqt3-mt (>= 3:3.3.8b), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), libxslt1.1 (>= 1.1.18) Recommends: texlive-bibtex-extra Suggests: texlive-latex-base | tetex-extra, bibtex2html, latex2rtf Homepage: http://www.unix-ag.uni-kl.de/~fischer/kbibtex Priority: optional Section: kde Filename: pool/main/k/kbibtex/kbibtex_0.2.3-1~squeeze.nd1_i386.deb Size: 784668 SHA256: 983e4e1e7b846ebdc732340e00f7274aa12d052a28178d3c2de8f70cff9ace07 SHA1: c4ad2445f44469f9f88b7100d92fcfc4b7cf2e5c MD5sum: 06fd2eb66cae4212965a588d1d843ab5 Description: BibTeX editor for KDE An application to manage bibliography databases in the BibTeX format. KBibTeX can be used as a standalone program, but can also be embedded into other KDE applications (e.g. as bibliography editor into Kile). . KBibTeX can query online ressources (e.g. Google scholar) via customizable search URLs. It is also able to import complete datasets from NCBI Pubmed. It also supports tagging references with keywords and manages references to local files. . BibTeX files can be exported into HTML, XML, PDF, PS and RTF format using a number of citation styles. Package: klustakwik Version: 2.0.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd60+1_i386.deb Size: 20768 SHA256: b5016eeb4d6dd0fce460d43489cb975a989e1f9bd22a45bfafb063d1d059bd35 SHA1: b385da0f2ccf592b41c0ad95d17395a9e0875f60 MD5sum: b01c49ec4b2afabcba71c0ed1e04b0df 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1212 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd60+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd60+1_i386.deb Size: 373418 SHA256: 026f8c985cd57c7da2b1f93622733f0c64409c98cd9790cef19c881dcc48024c SHA1: 57f7aecba6a0232a26de5006312f6b4d91bc030b MD5sum: a0211e12fbac4a0919bc30698cb27636 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 756 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.96.3+svn2677-1~nd60+1_i386.deb Size: 295632 SHA256: de5ffe0eae0339b90c38bf76b00de613a90f2b383dd415071f9bedb7131e085d SHA1: 954559fb48ba0a2a9d4de1f1e33010574a3ef463 MD5sum: c3a0ecd3669acad4f5713314edeaf883 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 188 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd60+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd60+1_i386.deb Size: 56780 SHA256: cb4875c57275693912c1d64d82ba63369da95566a7e9e6539e910177385ea220 SHA1: bcbf855c6ab36f533af7cc5b2f036dfeb462d30b MD5sum: 685ce25f16b5286fa0e4c4ca571b484d 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: libclassad-dev Source: classads Version: 1.0.10-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1656 Depends: neurodebian-popularity-contest, libclassad1 (= 1.0.10-2~nd60+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libdevel Filename: pool/main/c/classads/libclassad-dev_1.0.10-2~nd60+1_i386.deb Size: 528710 SHA256: c561e2e337d67e95fb75fa47a8eb5410e332c5a809c8d31f8f76db2e4edd59e6 SHA1: 28b0f2d35e9e2aacb68903a869c0aa8add0489f5 MD5sum: 59a54a4ea65e2f42cebd140f75b5d710 Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad0 Source: classads Version: 1.0.9-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1052 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libs Filename: pool/main/c/classads/libclassad0_1.0.9-2~nd60+1_i386.deb Size: 423730 SHA256: 9a21434e3014be15a5b66423b1493e0e3adf051040af58fd18655993997f564c SHA1: 6768fb008cd279c6cdd2edcd96306c072e652ff9 MD5sum: 93099ea85cc73c220a2187e382b5ad6d Description: library for Condor's classads expression language A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the runtime library. Package: libclassad1 Source: classads Version: 1.0.10-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1016 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libs Filename: pool/main/c/classads/libclassad1_1.0.10-2~nd60+1_i386.deb Size: 423914 SHA256: dbc7df34a559dad4ac68ccaecd35f8f252bda467c4860dc4e4fa861c889d9048 SHA1: 12e40d5b7fe625d8b9cc20e5b932299875f901b1 MD5sum: 5f1219665423f8bbd57765af6542f30f Description: library for Condor's classads expression language A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the runtime library. Package: libdmtcpaware-dev Source: dmtcp Version: 1.2.1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.1-2~nd60+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.1-2~nd60+1_i386.deb Size: 6600 SHA256: ee9c5365a4505a0907788b0ca4c2805cf30066ffc28d1b80328e9d3cf17fe16d SHA1: ebd3f1c8b9279070828225a572d835ba9374e0ca MD5sum: bde14da4373657e75e7a6fbec46749ac 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.1.3) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.1-2~nd60+1_i386.deb Size: 6312 SHA256: b552b0a3271e207bc049e5179347b5097bac6a640d362fbae282498dba35ca79 SHA1: 1507d2dc485fe745767430f272466d9a963f1446 MD5sum: bb6ad907dde7839e73a1cc3467d9c8d2 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: libfreenect-demos Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.6-6~), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libsm6, libstdc++6 (>= 4.4.0), libusb-1.0-0 (>= 2:1.0.8), libx11-6, libxext6, libxi6, libxmu6, libglut3 Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+1-2~nd60+1_i386.deb Size: 24388 SHA256: dfc200cb4c978fc4d71a131d61773ae8fbac07fa495f2451a8cec2e65cff14c6 SHA1: 363625392ecd4edf8c442693c949b9fea76fd81d MD5sum: d4346c6d09747bd70d30166bfda361c8 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+1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+1-2~nd60+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+1-2~nd60+1_i386.deb Size: 24964 SHA256: ef919561f2352352572a05ad67a8d1c802d21716ee1aebc0946e77f6f6522943 SHA1: 551d8de69a5dec6b83e09c312a6ef9bb10df5855 MD5sum: bb39b1e8b0a03fbbc3f0f37fa1a77c4d 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+1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120 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+1-2~nd60+1_i386.deb Size: 24090 SHA256: bf24df4222897d2b5d50b7acd53069451a1e239c88acfeb71ba298921051f1b6 SHA1: 5ed9d1fb7f18d9fb0e75fc3773257ce236e52dad MD5sum: e2a9e58354388e5a9259a52a86e70fb0 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd60+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1-1~nd60+1_i386.deb Size: 18514 SHA256: 8cc89e2a3989fe96b9ca490148bc7bbcd95af066c8e97836a5662c33222ed6ac SHA1: 486e7930aef47c163ec624b8f54116d9400f5f4d MD5sum: 6fba08eb8d3b15c1e868688be224a211 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.1-1~nd60+1_i386.deb Size: 105104 SHA256: 4cc7f571ba247c5df4da96c929bba20ffbe88ca3556ada8d05c79ef6890d94df SHA1: 455d6e5a84df3d9993b54ec254c84c05d888a975 MD5sum: 6af531161b04265f63a4d29a6d0415d5 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3592 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd60+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1-1~nd60+1_i386.deb Size: 1086408 SHA256: 00c75cf21f169c89da313c573acd82fa2b6a73d0e533e116d2faaf8046cf29c1 SHA1: a151c275dcd18b8e8681cfb0b8c5677420dbe0d9 MD5sum: b3f5d06f61e1be4bc4eb47ba89085866 Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 204 Depends: libgiftiio0 (= 1.0.9-1~squeeze.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~squeeze.nd1_i386.deb Size: 62812 SHA256: 867b6088809e2367db92779aa1e8c9a5f98eca61efe0c18a2291fbc0e7c6cbac SHA1: b4c327e2fa299bab3eb3f4c27c85b0460b315d89 MD5sum: 214ff5bda9d8062090d3ae5829931678 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 172 Depends: libc6 (>= 2.3), libexpat1 (>= 1.95.8), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-1~squeeze.nd1_i386.deb Size: 56988 SHA256: fc68dcc4aca8ef9560e7a28aea64c973dcb918c1622a0bfed92a4e75c89bbc6d SHA1: ee53dc464034c6835285763ad2ec9c1304e9f47e MD5sum: d4b070d164e9d57ca70ee9c08eea2ac6 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libnifti-dev Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 464 Depends: libnifti2 (= 2.0.0-1~squeeze.nd1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-1~squeeze.nd1_i386.deb Size: 151338 SHA256: 5f907628840dd4c157d714c96ada28368996b5d6c343832dc553af1b0b9939ba SHA1: 479af124a523960bf9768f3756de0f64257947f7 MD5sum: d776ab112afb15d0006427f3117d330e Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1896 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-1~squeeze.nd1_all.deb Size: 245414 SHA256: c421052431a49808544394d7242ddbd0437c09c001e9936fa302d29b653603d6 SHA1: 16d20e3475e20aaf39aa4df9231cb5117421d33d MD5sum: 1de8bde7f67f9fd2b7f2571ba0212457 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 292 Depends: libc6 (>= 2.7), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-1~squeeze.nd1_i386.deb Size: 106516 SHA256: 4a3ebc725d6ab85147ceb4432313b46194831375f7a6af562f9eac768ffc6603 SHA1: 62fb913c4852564dc99b6f1a5f6091f4d17d652d MD5sum: 21fe0aa975d9290ecefb6c736cb3849e Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libodin-dev Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 15604 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~squeeze.nd1_i386.deb Size: 4026742 SHA256: 6f89e2583ac92cbd7d324e0a7bf6909d5c29ad684a9bed21f408b57017a62ffe SHA1: 30f15cf7d87d4454be0592d4ab5ab87de3a4b095 MD5sum: fe92a978a99660150718d9ef9ad315d1 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-3~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 252 Depends: neurodebian-popularity-contest Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-3~nd60+1_i386.deb Size: 45666 SHA256: 14695678cc08df71c99641e8b7f102d72d7dcf3069159aed2581a02c27e736ce SHA1: 0400e53690fee584ff0c25b49476d01c60f260c9 MD5sum: 0b0fd91aeafbab17f29e12583d17b992 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-3~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 784 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-3~nd60+1_i386.deb Size: 232604 SHA256: 6b132147570489305da49a87ca83808cbf82a8d99819b6fda41d2c8b3b6d62e3 SHA1: 3d1b3248416641a08986c9a294ad8ab46c93a6b9 MD5sum: 8289fcbe753b04e4405676799e354cdc Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. Package: libslicer3 Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 109604 Depends: libc6 (>= 2.3.6-6~), libcurl3 (>= 7.16.2-1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libinsighttoolkit3.16, libkwwidgets1.0.0908, libstdc++6 (>= 4.1.1), libteem1 (>= 1.10.0), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, zlib1g (>= 1:1.1.4) Homepage: http://www.slicer.org/ Priority: optional Section: libs Filename: pool/main/s/slicer/libslicer3_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 25230644 SHA256: 0a5aef02cd1f481d15f853cb83fde6d34c21b2cc8c17bcb1b55e611db7b736e7 SHA1: b71c5599158dc1d45f6d7c311bda8b3978f2b33c MD5sum: a36e4011d8a5b77b8844383815b36bcb Description: software package for visualization and image analysis - runtime Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer libraries. Package: libslicer3-dev Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 3088 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1) Conflicts: libmrml1-dev Homepage: http://www.slicer.org/ Priority: optional Section: libdevel Filename: pool/main/s/slicer/libslicer3-dev_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 446332 SHA256: 17bb3f3cb59d5a3f2f659f5deb7fe5f430042b3a1f11fd866a8554813a2a24c7 SHA1: b8d299264486671b5e088db0d9475cdb52a06cb0 MD5sum: 630b7119115ae8f53f2e78cb4728c658 Description: software package for visualization and image analysis - development Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer development files. Package: libsvm-dev Source: libsvm Version: 3.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd60+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd60+1_i386.deb Size: 39864 SHA256: dd0cb500d6522ffe7aa367abbfc85a720d36ffac44166c3604d831c6892908d3 SHA1: 4322115b6d1ff50cebe9516a89f3fc61ed254a52 MD5sum: 9eb917105dbf2030bdf2e51041b8efa6 Description: The LIBSVM header files These are the header files for LIBSVM, a machine-learning library. Package: libsvm-java Source: libsvm Version: 3.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libsvm3-java Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm-java_3.0-1~nd60+1_all.deb Size: 13482 SHA256: 747f6bbaa0672dd192c281637bd277fabe9147c7d20168f2b6fd17e20038e3de SHA1: db5548e811b699c6a300814200cf0e949dcce62f MD5sum: d984c74835cf5628722c9688890e79c3 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. . This package solely provides a symbolic link from svm.jar svm3.jar. Package: libsvm-tools Source: libsvm Version: 3.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, libc6 (>= 2.1), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python, gnuplot Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: devel Filename: pool/main/libs/libsvm/libsvm-tools_3.0-1~nd60+1_i386.deb Size: 112540 SHA256: e3657ca5c25405dcbdcd9fc678c452ed1a91f7736e52d322691d5b1ccb139c9f SHA1: 232ab1646cecc3ef778f641befcf84d232cc0603 MD5sum: 15248e6a65b48910dd5054688e6e56c3 Description: The LIBSVM binary tools LIBSVM is an easy-to-use package for support vector classification, regression and one-class SVM. It supports multi-class classification, probability outputs, and parameter selection. LIBSVM homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm Package: libsvm3 Source: libsvm Version: 3.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libs Filename: pool/main/libs/libsvm/libsvm3_3.0-1~nd60+1_i386.deb Size: 42924 SHA256: 790a966d496326803362bc905ec6be41254d48a3dc9efa9499791a0bf36739a1 SHA1: f578711335527f364359d5195d9b302f00341fca MD5sum: 54299518cb1ff003857baba112f5ef1c Description: library implementing support vector machines The LIBSVM library is used to calculate Support Vector Machine optimizations with a great variety of powerful options. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. It is primarily of interest to machine-learning researchers and artificial intelligence application developers. Package: libsvm3-java Source: libsvm Version: 3.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, gij | java-gcj-compat | java1-runtime | java2-runtime Suggests: java-virtual-machine Conflicts: libsvm2-java (<= 2.91-2) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm3-java_3.0-1~nd60+1_all.deb Size: 60470 SHA256: c987074f9d3999f640bfcb339c768614ff592d3912a0ed5612b1a7dce443057d SHA1: 3c15a635564faded13725b2e51510f4dfb8cf7cf MD5sum: 9ee4532e7ca8eb5d96ef4c8bd603a7b4 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. Package: libvia-dev Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 696 Depends: libvia0 (= 1.6.0-2~squeeze.nd1) Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_1.6.0-2~squeeze.nd1_i386.deb Size: 213252 SHA256: ae497c2d49da6add63f34cdc38e6ee626f653a5f45c3797f3d91c4b463736d47 SHA1: ce64b6edfc0ecca4d4d55fcdcabbac6c374f1ef2 MD5sum: 48455f9e52e3980683e3dfc42c85b549 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 936 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_1.6.0-2~squeeze.nd1_all.deb Size: 110492 SHA256: 4e8b7ff2508c5a1611f3b8c0a7187d504559a7afc6333b3cd00fa4f20fc4cc88 SHA1: 6153d1287d5042551385c28bd9e46c9b5258c390 MD5sum: 1e42168726e0b36b1b9c1aefec7a276f Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia0 Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 440 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia0_1.6.0-2~squeeze.nd1_i386.deb Size: 179612 SHA256: c43e468df2e6dbb08cfd296b00bf0b8a16e8e19ea0bf8e59bcafee1aedc629d4 SHA1: d51eea6874085fcf58f23cc6d3aa5a53dcba5cf6 MD5sum: ca7372905cb4b9fad56ebf481610227d Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3448 Depends: libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti2, libqt3-mt (>= 3:3.3.8b), libsm6, libstdc++6 (>= 4.4.0), libvia0, libx11-6, libxext6, zlib1g (>= 1:1.1.4), via-bin Recommends: dcmtk, lipsia-doc Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/l/lipsia/lipsia_1.6.0-4~squeeze.nd1_i386.deb Size: 1273038 SHA256: 92d251834c3ed15a8d3defdf58787e0297bade1a9f21247a5c17b88e53d5a480 SHA1: cff2550e197690bfaaec4e761179867019cc019f MD5sum: 97baff1322c502374375163975369928 Description: analysis suite for MRI and fMRI data Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an efficient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development of LIPSIA was the efficiency of the software implementation. . LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported. Package: lipsia-doc Source: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 7004 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/l/lipsia/lipsia-doc_1.6.0-4~squeeze.nd1_all.deb Size: 5539242 SHA256: 698077dd0ec212ab7db8d81fb1ea253fde3176d0817184edf9cc35f1b634be0b SHA1: 9370ec74bf24fddf9143bc0556f7f3535560b929 MD5sum: 5d38c0c06db5d46971b92e261ab545db Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: matlab-support-dev Source: matlab-support Version: 0.0.14~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 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_0.0.14~nd60+1_all.deb Size: 5470 SHA256: c08905c7ea85e0cca79a7d7ad975e801e5fb210c7f42b3a109f7ee8c81a3066c SHA1: e818c9eb90a39a197fad15e3f906cdb57933fd38 MD5sum: 5ae0952ee0a3ba92f156de5a9b26732b Description: helpers for packages building Matlab toolboxes Analogous to Octave a Makefile snippet is provided that configures the locations for architecture independent M-files, binary MEX-extensions, and there corresponding sources. This package can be used as a build-dependency by other packages shipping Matlab toolboxes. Package: mitools Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 6236 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.3.6-6~), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti2, liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-3~squeeze.nd1_i386.deb Size: 2378350 SHA256: 34169a7105b1e99036adcd851feb0f10d65b5373ad27dc029d5e3cd2ccf26313 SHA1: a6c58f078a5fb9c5b53cdb3aea709c18791e32fc MD5sum: 6e4f8ba474af1a3eddb3fdfb3187b033 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mriconvert Version: 2.0.203-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2096 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.203-1~nd60+1_i386.deb Size: 762292 SHA256: 41da8aba10bc7e0f5e7a408f2a6db6e7ec95e1225be630b0177475afba44b993 SHA1: dad674a91ff58e51ee542f4f62c7968916d2f00c MD5sum: 08e66f6e742cbb8f00761738377bb018 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20110413.1~dfsg.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10716 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.29.3), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.8.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20110413.1~dfsg.1-1~nd60+1_i386.deb Size: 4075810 SHA256: 0e6eefa380af6fe41cfd33a3f2b4753bd531e381247b1abe6cdd34a4d599a924 SHA1: aa20b457616de8cd03f940898f4c7f44f31e7198 MD5sum: ace56422aade86fda02a36abb5a65835 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20110413.1~dfsg.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1808 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20110413.1~dfsg.1-1~nd60+1_all.deb Size: 1666502 SHA256: e972e2fd5b38a2803513db1b5823f9c04a9bb3548e594045525f3b08aebe3e8d SHA1: 4da65400b9d63ecee1ece7cc8c0efaa442d34d72 MD5sum: e333ff559a869d6707eca408b5e9ecbb Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20110413.1~dfsg.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1180 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20110413.1~dfsg.1-1~nd60+1_all.deb Size: 738130 SHA256: 50c6a5eb571faea0e02e63b91e4a58d0e1a5f3b134af191522c3a31f2be4fa31 SHA1: a9a1b04f619ca34f4efc00d641c83d9b88d685ae MD5sum: a1d1fe1d35b3b534f5e991550d73b842 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.9-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6452 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.29.3), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.24.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.20.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.26.0), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.3), libx11-6, libxmu6, libxt6 Suggests: mrtrix-doc Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.9-1~nd60+1_i386.deb Size: 2278790 SHA256: 46b144387dc25a68331a18612679e3adfc9da42e561ec82d238d8c98dcf16af5 SHA1: a7304f47d12ba21c2f5087b5fb768fac14fb9926 MD5sum: fce6fc5f968d1605f77cea6f18c94383 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3312 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.9-1~nd60+1_all.deb Size: 2945966 SHA256: 323a536337d152179d431dbdc9de9d36168d31b666515ab3ece9ca671858ad81 SHA1: 7f25e3e96b4b25449e20e8bb99d0fc57de1cc0f7 MD5sum: ef977e9abe990aa05704dcd369f9bb4f 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: 0.25~nd60+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_0.25~nd60+1_all.deb Size: 113122 SHA256: dda7126bf63174954b7b46b6adf8f5da981b4c174fc76b9a0f7be89a204756c2 SHA1: 0b3019327a538923c273d0d980ebfe5bcc613e8a MD5sum: 655dfd4f04b53404ba0de13b6edecfe7 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: 0.25~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4408 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree, moreutils Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.25~nd60+1_all.deb Size: 3845826 SHA256: 13262578e113106221cf16523c66b2291e60af01aab496f842767127e6482925 SHA1: 02d34392d8fa9a238bf5d8c86b22386bfe177daf MD5sum: 9d4d4554286822b06be1a5d16aca4b44 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: 0.25~nd60+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_0.25~nd60+1_all.deb Size: 12826 SHA256: 842201673c0bee627f2c054a4f67a65fd59a6becab6a85b39cfd4dfb16b1c4fb SHA1: 69ecde8b57fe3ac0c274251e120c8b5d667af52a MD5sum: 93033fc8f6af470e8e9d6f0c8311bad5 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: 0.25~nd60+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_0.25~nd60+1_all.deb Size: 5868 SHA256: cc55b770b85418a98feba6a05edf803e56f063d3eee55a32873b1898fb3ab038 SHA1: 5e11ea26290c142b9076e030020f197ea59969ef MD5sum: f4c127d5e9645c1c39c6e457d9616c32 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: 0.25~nd60+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_0.25~nd60+1_all.deb Size: 5026 SHA256: 0d5b28835441e3c8b19e8005fff562f937e620a7632674c2df0321614fc1109f SHA1: e6d3b7decc91bc82e39023534761a28c002dba69 MD5sum: c6f805547dc3b09f6adc56214ce47a1f Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti-bin Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 188 Depends: libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-1~squeeze.nd1_i386.deb Size: 59178 SHA256: 2990e1363bb38f8f721f787c5728027dcf4eb56c6594cf5da39bda4cac9ec909 SHA1: 5eb049efc861aedebf8260759171d809cb4e8bb5 MD5sum: 18a4ed953057c85252118ddacd512538 Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: octave-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Depends: neurodebian-popularity-contest, libbiosig0, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.1.3), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.7+20100313), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.96.3+svn2677-1~nd60+1_i386.deb Size: 18660 SHA256: 7212e52557d843dfca499b11ca23bbcfd421485b4fd7d07b355bd0b084853c57 SHA1: 0edd4ae984d34b390fb6fd6a7107b722873b12b8 MD5sum: 652e3a0e1b18c441a9845749d29ccd4d 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~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.1-1~nd60+1_i386.deb Size: 132078 SHA256: c4bbed5b98804b5142d71cbb5f08cd172b828b3c31708023c8e52d2e3728bbcb SHA1: b6aa96b151b10c5bf2209906d3d3bdda5f6a38ef MD5sum: 2af51720b1687aba78ea27b73e9c6d6a 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+svn2078.dfsg1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1900 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), freeglut3, libasound2 (>> 1.0.18), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.5 (>= 1.5.4), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libpciaccess0 (>= 0.8.0+git20071002), libraw1394-11, libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.8), libx11-6, libxext6, libxml2 (>= 2.6.27), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2078.dfsg1-1~nd60+1), psychtoolbox-3-lib (= 3.0.9+svn2078.dfsg1-1~nd60+1) Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.9+svn2078.dfsg1-1~nd60+1_i386.deb Size: 611072 SHA256: bf981f0259ea449a5a276e197078664fec74db070ac922c84684826620665df2 SHA1: e07aae4cbb24b7171111c70135ce45fa007377fe MD5sum: f22cf4d3004b1c2ca0ac1cad938efbf5 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. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 4000 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.4, mitools (= 1.8.1-3~squeeze.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.1-3~squeeze.nd1_i386.deb Size: 1547432 SHA256: 023ad14334f378adad8d680c8e6e1372821795ec064fe05ac85a09fea9b7dd15 SHA1: 899697a83502d5a8e20e5fcbfd07ca82932e50b8 MD5sum: e076da095a8af0280156721535f83e6d Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~squeeze.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~squeeze.nd1_all.deb Size: 34368 SHA256: d3c29b416792bf1d8ca68eb2af7da3b0d60a8f0d836fa9d1d3b83cdd9329b878 SHA1: 1f8d2aca09d37c8e5efb01093a0e10909a862e38 MD5sum: 78bfb172b4686b3985ab9ee42929d028 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-3~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 484 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-3~nd60+1_i386.deb Size: 150434 SHA256: 8ed0ca2f24cc202954fc28f8d2777fa854b69e3998bd97dd4bdff22c85d5485f SHA1: 6f335a827c5fa3610c639c2dc138a405095e09c1 MD5sum: e72df70b1f013416d463560de1eb1822 Description: tools for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides command line tools. Package: opensesame Version: 0.23+git1-g0212357-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5092 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-tk Recommends: python-serial (>= 2.3~) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.23+git1-g0212357-1~nd60+1_all.deb Size: 3335776 SHA256: 01ff8416c9153d574bd3ad7b814c11d71010ff9c4d8ab0ddbb1c5a6f1fa62642 SHA1: cf59b72f735777e9d96b31933a8b064579475b5e MD5sum: 01b774b33e313d2d2c68d4605dbe6603 Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Python-Version: 2.6 Package: psychopy Version: 1.64.00.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4748 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-scipy, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.64.00.dfsg-1~nd60+1_all.deb Size: 2611648 SHA256: bde06a743c505b8fed6a4519c3c395358a091bde7ba9d5b1570bd7436ac2cd8a SHA1: 1e04ba8291c7171d9ebb7acae4ab3ae5bea39338 MD5sum: 054d6a0e31e622efe4de3fe4647243c6 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: 2.5, 2.6 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2078.dfsg1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53368 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2078.dfsg1-1~nd60+1_all.deb Size: 19154684 SHA256: acb0b90f856d35c61eb77cef011c3b9f73e2ade140620069f4e23a1d2b675ec2 SHA1: 4a9301d79d72cc244e4c83467ef14e868ce802e8 MD5sum: b774037bd3817338aae122bc4830b003 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) . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.9+svn2078.dfsg1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2012 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2078.dfsg1-1~nd60+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2078.dfsg1-1~nd60+1_i386.deb Size: 662912 SHA256: 823d23a5b6eb579610d945acb749a5d4b4b24dfbd0cda910a8d960f97aaf52c2 SHA1: e7eb01be8b01703e412f11b73680819f48a00319 MD5sum: d96899a3ffda1408224271fcb588dc8b 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. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.9+svn2078.dfsg1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 184 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.9+svn2078.dfsg1-1~nd60+1_i386.deb Size: 61246 SHA256: 39c18d5193acc7de62496799194bb6e64045524f4cbf6275189ea113d02d70af SHA1: 4309fef0f674141f3837727f13d6b807bfd16e35 MD5sum: 581887d2ce558770a3b0242df70a5756 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. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: python-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.1.3), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.96.3+svn2677-1~nd60+1_i386.deb Size: 51214 SHA256: 02ad01ed650a60af6e99c6737a04538860e127da56103ca2943bea17bfd9b821 SHA1: 50a9d722a998e4c45cece188cd107ab87acc0fe3 MD5sum: 683d7aee61e16b2d0bb7353f1d80d779 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.3.0-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1692 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.0-2~nd60+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.0-2~nd60+1_all.deb Size: 314048 SHA256: 827f0572c12c8e2dc30b7df6ca851b9c990d2b820d7740a52033375a908c7b26 SHA1: 278e2c840a9389f89caa142c8e0ef9ed72dc4744 MD5sum: aa070370e087f8b95e590aeaf7aa7e9a Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.3.0-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5320 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.3.0-2~nd60+1_all.deb Size: 1651040 SHA256: 2f3be42514fca02c8294450f861152fde3098e9ad06d6fdd5f21793e9e5deb11 SHA1: 8b699779fb48949a5b413547a23b0b17e29eae19 MD5sum: b327e4084febad0f56b621c98bd4349a Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.3.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.0-2~nd60+1_i386.deb Size: 51902 SHA256: 4e7bb4718ea18fdc9bb7d1373fb6d934196e3c4c258cd1d08d8d4082e15de691 SHA1: bf0cd9ff996a227708bff00fa64e4174dd5ee1bf MD5sum: 59df3a80ebbd4266e651fb7c0ec4f8f9 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~nd60+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 Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd60+1_all.deb Size: 217692 SHA256: 89c8c15b49c321ab86c69d97c6eb00eb731b2bd699c40e38dc56f8eae505412c SHA1: 6bf2302a69863a6985783df190603edfb88b7417 MD5sum: 68cfd02459ffb3eca1787a8a7bb959d2 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: 0.9.5~rc1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1864 Depends: python (>= 2.5), python-support (>= 0.90.0) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.5~rc1-1~squeeze.nd1_all.deb Size: 372934 SHA256: 86c7cf926457b1ee202649b15563e1cc5f38003f0b12acd47b0f912fe7ba3349 SHA1: 69ded2a0cb005e606fdb53ae5c7d2812a9e08955 MD5sum: 18025a434efb994467d69e223bd17d6d 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: 0.5.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2204 Depends: neurodebian-popularity-contest, python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-1~nd60+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.5-dipy, python2.6-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-1~nd60+1_all.deb Size: 1459154 SHA256: daab1be58938aa4b81f3ed2c53ec43abc70b945f82c81f056670477faec081cd SHA1: d6a8c40632b746054e6bb070faa91e59888c1c55 MD5sum: aa0449dcef5aa1112c92765eecdab788 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: 2.5, 2.6 Package: python-dipy-doc Source: dipy Version: 0.5.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3292 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_0.5.0-1~nd60+1_all.deb Size: 1950840 SHA256: 793a351eac3a27d5f3df2994da9e22045944fef469ffd8337acd4e74f3096bcf SHA1: caf5c0ee7957226c3ca54f5a6b3764c2aaf762d0 MD5sum: b5c55bdb5de993e26585228e8d1b11c4 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: 0.5.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-1~nd60+1_i386.deb Size: 3428 SHA256: 1596fe6962e251195542f1746baa9a0d192e77aa88e7656441e11488a50656b1 SHA1: 07a387ca9fc9d4f4e1eb56b9852fdb06aff83523 MD5sum: a01c4a22a35c3a98f1d3375dfe56f2ce 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. Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfreenect0.0, libusb-1.0-0 (>= 2:1.0.8) Suggests: python-numpy, python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+1-2~nd60+1_i386.deb Size: 28094 SHA256: d9ee29285adcc199b886be7480a6626eb9fd944980eaafc19f10a4b8979df0d1 SHA1: 43ce327a62159691cb2fee4bc10f1f53f7e01c57 MD5sum: 127874d5fcd0479c93b54b0a5b5c3742 Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.5.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.5.1-1~nd60+1_all.deb Size: 44190 SHA256: ca18a591fc8be91b94f5707bf202ac7922f327b825541e6c728b73db7dafc3e0 SHA1: 2a75a9bc506292ca2f92c724c06a4be96eaeba1f MD5sum: 88763db87313297defb9b7a76a833cee Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-libsvm Source: libsvm Version: 3.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd60+1), python, python-support (>= 0.90.0) Provides: python2.5-libsvm, python2.6-libsvm Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: python Filename: pool/main/libs/libsvm/python-libsvm_3.0-1~nd60+1_i386.deb Size: 14318 SHA256: 8e0e64ea9c203f419c81136ce66c78190120d1eed203ab47f00a9277883cedcb SHA1: e3224c0ae1aa5fb7a0c33067f7eeaca2a44e2581 MD5sum: ff63fa7e2210ad4ca7f08447220d0a8f Description: Python interface for support vector machine library Python interface for the LIBSVM library using ctypes. This new python interface is provided since 2.91, and it is incompatible with the old one. Package: python-mdp Source: mdp Version: 3.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1812 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-scikits-learn, python-joblib Suggests: python-pp, python-py Enhances: python-mvpa Conflicts: python-libsvm (<< 3.0) Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.1-1~nd60+1_all.deb Size: 455304 SHA256: ffd752cc611a6bf97b7d5c2fe8c6c75eee316116098ba57661c5c08e3bd55e6a SHA1: dd0209b10f8ad22ce1e578be0dae8a75ce999367 MD5sum: d880c07b9ec8bea8c440fa5d00f0fbc4 Description: Modular toolkit for Data Processing Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. Package: python-mlpy Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 428 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mlpy-lib (>= 2.2.0~dfsg1-1~squeeze.nd1) Suggests: python-mvpa Provides: python2.5-mlpy, python2.6-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 58266 SHA256: 77f4b8e2129db61e00feaad3c1460a923975820c91e625dc4fff605039f14c7a SHA1: 878fa1b9c71726e276b82d462006a5a90c127ea6 MD5sum: 69d292f9dfb2f666d6a3542ddbe60dd3 Description: high-performance Python package for predictive modeling mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . mlpy includes: SVM (Support Vector Machine), KNN (K Nearest Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression, Penalized, Diagonal Linear Discriminant Analysis) for classification and feature weighting, I-RELIEF, DWT and FSSun for feature weighting, *RFE (Recursive Feature Elimination) and RFS (Recursive Forward Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated, Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time Warping), Hierarchical Clustering, k-medoids, Resampling Methods, Metric Functions, Canberra indicators. Python-Version: 2.5, 2.6 Package: python-mlpy-doc Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1136 Depends: libjs-jquery Suggests: python-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: doc Filename: pool/main/m/mlpy/python-mlpy-doc_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 480866 SHA256: a1a158d0318129c2b6ac767cf0385b266a45aeaa6a06a45fc5bf61d6a77ff9b5 SHA1: 0de7a2884bfd8de60215558a742d138d0d35f167 MD5sum: 676b76390bb77f41f7a1ee949b11e212 Description: documention and examples for mlpy mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . This package provides user documentation for mlpy in various formats (HTML, PDF). Package: python-mlpy-lib Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 448 Depends: libc6 (>= 2.3.6-6~), libgsl0ldbl (>= 1.9), python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mlpy-lib, python2.6-mlpy-lib Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy-lib_2.2.0~dfsg1-1~squeeze.nd1_i386.deb Size: 121286 SHA256: 2e849443ca2e80a1704bf50b280d59b1c050aba414752bfa555eb9b04be6a333 SHA1: e748d227727cc8b0fd91b5afaf9696187ed0d009 MD5sum: 7374f7da64d5a4e499f367af961ad901 Description: low-level implementations and bindings for mlpy This is an add-on package for the mlpy providing compiled core functionality. Python-Version: 2.5, 2.6 Package: python-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1844 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libopenmpi1.3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~pre1~nd60+1_i386.deb Size: 534334 SHA256: 2401f0fe597d05ecd8480ae51f69774bc1da9f45d6a3bceaf2d7d101c3abea64 SHA1: ec338a55570cc4e9de5d6ec8dfbf98e4812fa1b7 MD5sum: ce70bc9c02cd0584abf9c77fd0dcc8b6 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 1.2.2-1~pre1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2712 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd60+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.2.2-1~pre1~nd60+1_i386.deb Size: 1011006 SHA256: a8e6589ecca23b4591474278379b350860269bcb9033aed65b02dfb8bba6746b SHA1: 4faec419a80e7df44f7902198218b1d852f2cb3b MD5sum: d56d4554ce96503b68f3185140699201 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 1.2.2-1~pre1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 272 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.2.2-1~pre1~nd60+1_all.deb Size: 54806 SHA256: 1b60db1309827d5c6ca4de2674c4133a7fe851d1fcc86d6a5d13043ed75c76a8 SHA1: cedce687642d97f89416079719540eedd3c926a1 MD5sum: 8365de41874844b3114055398c97d734 Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-mvpa Source: pymvpa Version: 0.4.7-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4076 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-2~nd60+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-2~nd60+1_all.deb Size: 2196770 SHA256: d1d7a825b792a5c998fba0c24cde296643fa58c292e1dbcfca3989db45c31840 SHA1: 86d776b22218359073100d5cf4190613cd079eeb MD5sum: 5ffad94fbc1fb319daa679f30937c4be Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41168 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.7-2~nd60+1_all.deb Size: 8741852 SHA256: 60219592f12361f3744118de0ff8ab84483b081d5637d6edcdc050e327f407db SHA1: 8539bcf016eba65b0c35c909567e076f6f959afe MD5sum: 5b7812d48cdc9ce79130b7684ab2658c Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.7-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.7-2~nd60+1_i386.deb Size: 68964 SHA256: e6cbbc1981a67709a22922105d86bdd1ad42d53d40125ce6fcd5e6d31cf756a4 SHA1: 1273430b041e3c077fa414a54d3af0e3c72c6a15 MD5sum: 1faaeb2cade17740cb37411be2d519d3 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.6.0~rc4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4596 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa-snapshot-lib (>= 0.6.0~rc4-1~nd60+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa-doc, python-scikits-learn Conflicts: python-mvpa Provides: python2.5-mvpa-snapshot, python2.6-mvpa-snapshot Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot_0.6.0~rc4-1~nd60+1_all.deb Size: 2314452 SHA256: b89b1b9b4bd7fd3f40dda7b25df20075fe2874234ef69b447d77161d592a49f7 SHA1: 23ece922204ce7d35e47b491b46407a8895c325f MD5sum: 9557d57f336963684b794f9a11822f22 Description: multivariate pattern analysis with Python PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.6.0~rc4-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 196 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib Provides: python2.5-mvpa-snapshot-lib, python2.6-mvpa-snapshot-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot-lib_0.6.0~rc4-1~nd60+1_i386.deb Size: 68972 SHA256: cd68647894775233a0055c108a21cdd4a33030a0c961950b8e3652b2e37ceaed SHA1: 83b3d906b2f4aa22a9f14621a93143a576393612 MD5sum: b06787487dbfdde270c93af8f830830c Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-networkx Version: 1.4-2~nd60+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~nd60+1_all.deb Size: 647278 SHA256: ad2839debf74b059def0e377f52e5b3fad23613603d2f69c61a6a7f59bfbd6b7 SHA1: ac9dd5bce62e8f0e1460bf9cff1b4655278cb7fb MD5sum: 88fcc837ad2b6e0c5bcf56df2802b09d 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15788 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~nd60+1_all.deb Size: 6169452 SHA256: c55591f29b87d1772fdf11a511fee43512b88d27dbdb99b0083c2d131b8ffdd6 SHA1: 15e7a5d65dfdb7ebc585a56a55441a4240644b2b MD5sum: feabea6baf7cf83997120652132961f9 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3612 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.5-nibabel, python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.1.0-1~nd60+1_all.deb Size: 1674964 SHA256: 06e5c8a04b7b277eeeb82cd86feec4e71ca6feefa29143b229c87f472ee66a12 SHA1: 290f626510aa00ffbf97c7b7aac5e1c6a43c64cb MD5sum: 30f37cd229fc8d61549b825affe66274 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: 2.5, 2.6 Package: python-nibabel-doc Source: nibabel Version: 1.1.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2756 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.1.0-1~nd60+1_all.deb Size: 411792 SHA256: e901d9bf87106049902f3fa8f081a554f480d54d76cd718a6adac3bab11fda60 SHA1: 9955f00929b27036eb3c14f96b037b97abc48bf3 MD5sum: 68aefe26d8adc89821c69dc3792bb487 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~squeeze.nd1_all.deb Size: 469788 SHA256: 88f8f2603bab6606985a137433460486b70e5765b08eba1ca81b8dccd3cfe96f SHA1: 12bd934e7cec2d24b9aec58fd66b592b9b4be485 MD5sum: feea254498444cc7f9827456091e83dc Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nifti Source: pynifti Version: 0.20100607.1-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1416 Depends: libc6 (>= 2.3.6-6~), libnifti2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, libjs-jquery Provides: python2.5-nifti, python2.6-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-2~squeeze.nd1_i386.deb Size: 344682 SHA256: d1d670f3c7b5ce720fec8d6452905a8a16be55c41ee158321a3ff9d639e61eb3 SHA1: 8972416b2e0e5e11e32fdff9b39eec4f2b3899f0 MD5sum: 4b407502a42e35faefe1e7ba214d416b 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: 2.5, 2.6 Package: python-nipy Source: nipy Version: 0.1.2+20110404-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3380 Depends: neurodebian-popularity-contest, python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-scipy, python-nibabel, python-nipy-lib (>= 0.1.2+20110404-1~nd60+1) Recommends: python-matplotlib, mayavi2 Suggests: python-mvpa Provides: python2.5-nipy, python2.6-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.2+20110404-1~nd60+1_all.deb Size: 692246 SHA256: dbd332af6df7a4d3e062afbf51e47e549637d33b3badb1d6afcca0af865cb2a8 SHA1: 16c508b0101b137fac31b79512888b04417bfc83 MD5sum: aa7ec03cf5b22044ab54328d845cfb47 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). Python-Version: 2.5, 2.6 Package: python-nipy-doc Source: nipy Version: 0.1.2+20110404-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9472 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_0.1.2+20110404-1~nd60+1_all.deb Size: 2542666 SHA256: 8402a3270ce826c5b81a3e24f9ebd9e96882538e5255642a9c11e9e53e216558 SHA1: 8448e2e79022511b67d8f2dd30bc22129fd575e1 MD5sum: 6b9e7b40b5ec8dde057d82525d4da34c 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: 0.1.2+20110404-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4872 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Provides: python2.5-nipy-lib, python2.6-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.1.2+20110404-1~nd60+1_i386.deb Size: 1572086 SHA256: afd8df8d5f59a3668df61d4972fa6d4f0413c24d6c17014c1dd90d630b9f1b23 SHA1: 706ee03ffcb1c4585fc6c9517c0e09feef953073 MD5sum: 94881f9764b6ec374d52ff3a91f2b272 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). . This package provides architecture-dependent builds of the libraries. Python-Version: 2.5, 2.6 Package: python-nipy-lib-dbg Source: nipy Version: 0.1.2+20110404-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5148 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-nipy-lib (= 0.1.2+20110404-1~nd60+1) Provides: python2.5-nipy-lib-dbg, python2.6-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.1.2+20110404-1~nd60+1_i386.deb Size: 1686966 SHA256: 71213ce721e64cf8db2230b13bf74655da1c8e9ad00f8601daba07d11260bcde SHA1: 8bebd5415f79e2535fc5805879127311f3d26cc5 MD5sum: 4b5e7441c4a680e001874643bc6e6019 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.5, 2.6 Package: python-nipype Source: nipype Version: 0.3.4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1820 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits, python-nibabel, python-networkx Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat Provides: python2.5-nipype, python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.4-1~nd60+1_all.deb Size: 318210 SHA256: 4b02a21370400bd2a6a2fdcb92cce159e2e45898802f63d853c47ad67a658abd SHA1: 2f0714c88670bab2f5d8b06fa97618576506abaf MD5sum: fec9a5dd6d4bc7a7e32f35742bb2aa88 Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.3.4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3944 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_0.3.4-1~nd60+1_all.deb Size: 884034 SHA256: 52db9a39d5d4c21d52201d7646a2bc4ccf77e34b7deedf2065ce6142729b6293 SHA1: 11f64de775b76ba6bd34bd8a6973c72eeae31071 MD5sum: 2c75f4d66d14880ec609ab189a8b670f 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: 0.2.99-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2100 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_0.2.99-1~nd60+1_all.deb Size: 1432872 SHA256: 00aaf48297e03adb47886d0b078595690bc9f6222f8c32e361a96d01b3f9b8e6 SHA1: e1a9304f2fe7196ed85577b99dc3fa98c98a08ab MD5sum: 884fa54fdb86f9c12341c31d714ded7b 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: 0.2.99-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4576 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_0.2.99-1~nd60+1_all.deb Size: 3004984 SHA256: 1240a1a701600f2e7d4760fb160e686a1de19f751079d786bedd76bcbe4a9bb8 SHA1: 223a641ae2e3e0ec4256faa621cc2f711f476b98 MD5sum: 92bb6a3903c2b38864db7a92c4edf4c3 Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-3~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 512 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-3~nd60+1_i386.deb Size: 154976 SHA256: 855071e0940cba63ef4a446f6ea5349140db276b5047ba435f9c522249193557 SHA1: eb4b5007d7821af09369110522c9eba4af10f1f3 MD5sum: 88a1a575f3a830c0b03e784e0fbf8fc0 Description: Python bindings for openmeeg library OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides Python bindings for OpenMEEG library. Python-Version: 2.6 Package: python-openpyxl Source: openpyxl Version: 1.5.0-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 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_1.5.0-1~nd60+1_all.deb Size: 57466 SHA256: fc6b028c8e0af4b972374b1b105499a31dbfc05977a328c61ffcbcf48ba8e25e SHA1: bc4168a3ecf78f7f87cec5f9045a65cb49854e77 MD5sum: 5c3ed5f8c2e581fc908aa6fd736f7bd3 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pyepl Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 2164 Depends: python (<< 2.7), python (>= 2.5), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~squeeze.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.18), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0, libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.5-pyepl, python2.6-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0-3~squeeze.nd1_i386.deb Size: 536326 SHA256: 78e856106e6abb8c0324b82bc5579ae79d64e8a696b260d7faa2a97362f50119 SHA1: fd989302b24fc3e0eb16e99bbe1c022fd3a90344 MD5sum: 6934b01474a73e988c149a4baa988e43 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Python-Version: 2.5, 2.6 Package: python-pyepl-common Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 852 Depends: python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0-3~squeeze.nd1_all.deb Size: 817820 SHA256: 575a264fe983d8b7d0ad9eaac6baae7c46308bfea1a454dd466636f7cd9b60da SHA1: 219e559bf4ac39efbc3f0e375cf3ea8849d1d224 MD5sum: b3492c37881b41822afe7760f1b3cc5a Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4356 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.5-pyglet, python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd60+1_all.deb Size: 972196 SHA256: 91b6b5b43bba43c419bc93e875ebba6ac09733899d7d34e944a5df43c3a33a6c SHA1: d9cb126e2761a5bd4b56f73542eac4dadea3f185 MD5sum: e3b5a0fd56d17deacf83460ebcea6737 Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-pynn Source: pynn Version: 0.7.0-1~pre1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1020 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.0-1~pre1~nd60+1_all.deb Size: 187306 SHA256: 459db03a63906adee62bfd9f1e62bace32d7a78b1315cb7825f09f4340c29917 SHA1: 3f2d7e0646a501a4204692c46c9e337c2970271e MD5sum: 1c43e019054fad888cd2e9b75a1bcdf7 Description: simulator-independent specification of neuronal network models PyNN allows to code for a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pyoptical Source: pyoptical Version: 0.2-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~squeeze.nd1_all.deb Size: 6956 SHA256: 66717fa53f6d283a3a697f969f32bc1c15f1467bbc26bb09ffceba7beb871644 SHA1: 3201dafeb370ade84db53fbe0ce85c1a0e57455c MD5sum: cf68976930753cdd2fde4b74529ba1b6 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~squeeze.nd1_all.deb Size: 119516 SHA256: 1adaffa1132d6581ae599f8781f656a482fb586ecdaa789ab235068043a7f85f SHA1: bd3b2114258a93dbd1108eaea341f8541ff74a47 MD5sum: 1f942f44319f70c9cc3afcaac2e70796 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-pyxid Source: pyxid Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Homepage: https://github.com/cedrus-opensource/pyxid Priority: optional Section: python Filename: pool/main/p/pyxid/python-pyxid_1.0-1~nd+1_all.deb Size: 11020 SHA256: 1031c0d69dd73cb38f3e0b826193211706a94bfd04da4287288418b257e54249 SHA1: 0f0d0524354e5d07eb89efcb11779d9acd9d57e2 MD5sum: 1f2a9bc07952b1f5c6b65fc5c092f75c Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-scikits-learn Source: scikit-learn Version: 0.8.0.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1424 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-scikits-learn-lib (>= 0.8.0.dfsg-1~nd60+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.5-scikits-learn, python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.8.0.dfsg-1~nd60+1_all.deb Size: 310620 SHA256: 1527c63b4e2a3e835d7f9b1dea52d1d27d4f4b9847bbbc018776d6bba02b6ce7 SHA1: 929512db3b00b86d2c9fcce1c8338a208c710b6e MD5sum: f94320b394be3819b1f1cb88bb8b2aaa 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: 2.5, 2.6 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.8.0.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14612 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_0.8.0.dfsg-1~nd60+1_all.deb Size: 9029692 SHA256: 59218b71a4ca435362f2f7e9e166c57321770c8dc1cfb9514b53debc22eb8b1c SHA1: 9586fa2f77485b730cf792178bfe489ee4e7e6f3 MD5sum: 7a3cdcc8fb4611a119a5f7135d41700f 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: 0.8.0.dfsg-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2404 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Provides: python2.5-scikits-learn-lib, python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.8.0.dfsg-1~nd60+1_i386.deb Size: 874362 SHA256: fd96254294fcfad5a11163f66c37dcbbfeb85c515f83d93be42693876796ff73 SHA1: 1eccfcc50cbbf33a3c2b6a7539ae32f5b786b2ef MD5sum: e6dd8b0ef90d965259a1c648e5765110 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: 2.5, 2.6 Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd60+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~nd60+1_all.deb Size: 1260210 SHA256: 5a134abec0131a6dcc56b85cd9089230b68374cc7e4896d8806d7e6e2e9ee9a7 SHA1: 21654aba4316d6b6799f864a41f925c64adf8725 MD5sum: 3968ce5358f08a65453ba21236af6630 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: 0.10.13-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 472 Depends: neurodebian-popularity-contest, libc6 (>= 2.2), libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python-numpy Recommends: python-matplotlib, python-scipy Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.10.13-1~nd60+1_i386.deb Size: 212714 SHA256: f4dba0a523844d93d9d93f928e31169ae9c8f1a31f547ab3c57e5b5cd44c3f69 SHA1: 709737f1353eb53b21d21c5b94cd53ddc78e1261 MD5sum: 96183970afabd34703304880817c3335 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-sympy Source: sympy Version: 0.6.7-1.1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9268 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-imaging, python-ctypes, ipython Homepage: http://code.google.com/p/sympy/ Priority: optional Section: python Filename: pool/main/s/sympy/python-sympy_0.6.7-1.1~nd60+1_all.deb Size: 1696348 SHA256: 90437808b931d5eb683327ab48a3ca8e81092be6f14d7f9cdf3f1fd8c8e6381d SHA1: 8ff9042d8752320997021155b1d7ee3620d11545 MD5sum: 38368c397ca1f942608ee78c4d6f1a8f Description: Computer Algebra System (CAS) in Python SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. Package: qlandkarte Source: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 32 Depends: qlandkartegt Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkarte_0.16.0-1~squeeze.nd1_all.deb Size: 2600 SHA256: 971cfe8965e2ac770ab91d1ff374cd8a75c9c59d21a4a3a6c2fec65f0aa36f27 SHA1: 94b85cfadc8414252933de2d0bab789f82ea1161 MD5sum: 461d6da351ea7fcd3dbffa8c5a5bfcf3 Description: Transitional package for QLandkarteGT This is a transitional package for the QLandkarte to QLandkarteGT upgrade, and can be safely removed after the installation is complete. Package: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 4972 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgdal1-1.6.0, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libproj0, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libx11-6 Recommends: gdal-bin, qlandkartegt-garmin Replaces: qlandkarte Provides: qlandkarte Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkartegt_0.16.0-1~squeeze.nd1_i386.deb Size: 2746470 SHA256: 051fe228305ff0cda9b7b33d57c4f1468f209b3936bcf7de4803b560b2627ef3 SHA1: 582f277bc81ca7f2c8e210a6d2607a0ad20b19fb MD5sum: afe54d1477816bc0fa3568f580f44ac8 Description: GPS mapping (GeoTiff and vector) and GPSr management This package provides a versatile tool for GPS maps in GeoTiff format as well as Garmin's img vector map format. QLandkarteGT is the successor of QLandkarte. Among various improvements (e.g. 2D/3D map rendering and reduced resource demands) the major difference is its device-independent architecture, which is not limited to Garmin devices anymore. Therefore, the package also does not include device drivers. Drivers for a number of Garmin devices are available from the qlandkartegt-garmin package. . Additionally, QLandkarteGT serves as a frontend to the GDAL tools, to make georeferencing of scanned maps feasible for users. In contrast to similar tools (e.g. QGis) its straightforward interface is especially suited for non-scientific users. Package: qlandkartegt-garmin Source: garmindev Version: 0.3.0-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 504 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libusb-0.1-4 (>= 2:0.1.12) Homepage: http://www.qlandkarte.org Priority: optional Section: utils Filename: pool/main/g/garmindev/qlandkartegt-garmin_0.3.0-1~squeeze.nd1_i386.deb Size: 173266 SHA256: 5accd56b9d821da2fad69ea72d98e85181f862f9243b23c86972a3dfacdd5411 SHA1: 6d08d975d38903b9a43b91a9f886d7258fd55363 MD5sum: 587a9221a1879465e1e74743385dcd0a Description: QLandkarteGT plugins to access Garmin devices A collection of plugins for QLandkarteGT to talk to various Garmin GPS devices, including GPSMap60CSx, GPSMap76, eTrexH, eTrexLegend and similar GPSr. Package: sigviewer Version: 0.5.1+svn556-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 984 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-1~nd60+1_i386.deb Size: 427994 SHA256: 89d4c667129c8cf062a2c82416cd31d6bd35d978e159324db1e2990a369fa9c5 SHA1: ddea7783af89c1ed8be7b9b47a05d073937b5606 MD5sum: 48993d5b684d99f2649155025da3794e Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 109832 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1), libc6 (>= 2.3.6-6~), libcurl3 (>= 7.16.2-1), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libgl1-mesa-glx | libgl1, libinsighttoolkit3.16, libkwwidgets1.0.0908, libopenigtlink1, libstdc++6 (>= 4.1.1), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, slicer-data, itcl3, iwidgets4, tcllib, tcl8.5-kwwidgets Homepage: http://www.slicer.org/ Priority: optional Section: graphics Filename: pool/main/s/slicer/slicer_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 23163276 SHA256: 3e91c2662ac069fb1f26d269b71e92d6eaa0e8def7cf4086050f1250fda6f956 SHA1: 0a064e6e4969b93b78fdafc57b705c4052c3e2e6 MD5sum: f9f144ec4df50bf71315b7fe9e7ab889 Description: software package for visualization and image analysis - main application Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer main application. Package: slicer-data Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: all Maintainer: Debian Science Team Installed-Size: 75656 Depends: tk8.5 | wish Homepage: http://www.slicer.org/ Priority: optional Section: doc Filename: pool/main/s/slicer/slicer-data_3.4.0~svn10438-3~squeeze.nd1_all.deb Size: 45850452 SHA256: c5a750d8b5ae619e7676d13bc9f8975e081771cfe9b6d534b000b54968903d3f SHA1: 34f83bdb09471100da1c6ea84b67a6064bf20708 MD5sum: 7470a7eb5cb992fb85799cd88960ff69 Description: software package for visualization and image analysis - share Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer data files. Package: spm8-common Source: spm8 Version: 8.4290~dfsg.1-1~nd60+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~nd60+1_all.deb Size: 10547196 SHA256: 9e2d24f75d4404bf2e7d874aacaf19392bc9b9751240719e7a1155cc9e39976a SHA1: a2f678875febab994ed88e5b23c39f70aad1417a MD5sum: 3ecbc2df3015515f8fecd942163f15ed 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~nd60+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~nd60+1_all.deb Size: 52167536 SHA256: 20115d5bda0d976422ba2edefadbade317f1ac87545556d681c7c30751d7b239 SHA1: ba3dbca6ffdbbde5e6e4d4b263e401a88a5acf49 MD5sum: 38d56d3332949d4cd229d67f780e14ab 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~nd60+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~nd60+1_all.deb Size: 8648790 SHA256: 1bb918b5adb52f507cf779a35b39433a2669cd397463b8ae82e2c2388afd3624 SHA1: 15c34aa92d8b78218aa2a3f19be01074fbad9eef MD5sum: f542e6320106fe690f4805444fc7bc3e 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: stimfit Version: 0.10.13-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1980 Depends: neurodebian-popularity-contest, libatlas3gf-base, libc6 (>= 2.3.6-6~), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1), python-wxgtk2.8 (>= 2.8.9), python-numpy, python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.10.13-1~nd60+1_i386.deb Size: 743596 SHA256: 947663556402c36daaf152759d34e6af17d94af02f3bbb46d4f739d42ea2692d SHA1: 460096e723b2b4d388bc4dec0816cdffd4886cea MD5sum: 196f769c19be49b4ded7a74515fd808f 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: 0.10.13-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12760 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_0.10.13-1~nd60+1_i386.deb Size: 4879326 SHA256: e2ba2424b03ae71da42d36f03c43bff0daae00fd4a3aecefb5b1219635f9b6bb SHA1: 0220ed3dcb229335e045a5de8b6f52aa6f9bc95a MD5sum: 21f9f812250b9421e8236a7fec00ed3e Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: via-bin Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 828 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia0, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/via-bin_1.6.0-2~squeeze.nd1_i386.deb Size: 174850 SHA256: e11e9d7aa657e76f4728f90affb75ec9da7af2bfad08f4db2b9beeaf2e23fde8 SHA1: e4fd24a57e867c43e1a1a2ed1facb0e658bdec23 MD5sum: a7b674b69bdca403db243833a0c01526 Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: voxbo Version: 1.8.5~svn1246-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9696 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti, matlab-spm8 Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1246-1~nd60+1_i386.deb Size: 3704676 SHA256: 85fa328a68fe5396b83bd5deecd9a4ecc085f14624a30bb60f68b8258633df51 SHA1: e08684d1d24a7a10d74297defa19af38be404f67 MD5sum: c29d119b1f6392e1aaf82600fd9bd69f Description: processing, statistical analysis, and display of brain imaging data This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others.