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: cgroup-bin Source: libcgroup Version: 0.37.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcgroup1 Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/cgroup-bin_0.37.1-1~nd60+1_i386.deb Size: 62598 SHA256: 70e0e4d28c391a4482ab1d214386ef80bb26e4b12444ae82afee075155e3f1ec SHA1: 027c121664153bfa988832cb0a3f41133e386692 MD5sum: c84ca171c7742baa2c6794d319a147d0 Description: Tools to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . These tools help manipulate, control, administrate and monitor control groups and the associated controllers. Package: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9876 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.7), libcgroup1, libclassad2, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2-1), libexpat1 (>= 1.95.8), libgcc1 (>= 1:4.1.1), libglobus-callout0, libglobus-common0, 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), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), perl, adduser Recommends: dmtcp Priority: extra Section: science Filename: pool/main/c/condor/condor_7.7.1+git837-g37b7fa3-1~nd60+1_i386.deb Size: 3950440 SHA256: dbb8382c35980eaf323636cd76e6fd001f8d3358c0c1989ce4a9ba78061932c6 SHA1: dc603b3b886cc7aa31c55118d72124c6cb0cdbf0 MD5sum: e11bcbbb326b6c7b9254de0a21d40cdf Description: workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . The Debian package uses Debconf to determine an appropriate initial configuration for a machine that shall join an existing Condor pool, and moreover, allows creating a "Personal" (single machine) Condor pool automatically. Package: condor-dbg Source: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 34148 Depends: neurodebian-popularity-contest, condor (= 7.7.1+git837-g37b7fa3-1~nd60+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.7.1+git837-g37b7fa3-1~nd60+1_i386.deb Size: 13323280 SHA256: bdf9b532099bbe40dd1f5699dd09f35e68df02b7e5b62dbee365895141d99a52 SHA1: e20a568c8dd33a75bd570ff5f218f4ee19d98d8e MD5sum: 9a3c34a5f74fae8ff7bf8eea2ae3b4d9 Description: debugging symbols for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-dev Source: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1060 Depends: neurodebian-popularity-contest Priority: extra Section: devel Filename: pool/main/c/condor/condor-dev_7.7.1+git837-g37b7fa3-1~nd60+1_i386.deb Size: 311594 SHA256: 983bb8fb8f46d3b7146e5ffd5b1160bd0c08c6e4ff66791f9307348cb133155f SHA1: 568f0bdbfbbcc80a809f226437f2718243f90601 MD5sum: 63007e22bc477a583c87b1f3e9fdfe17 Description: development files for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of Condor add-ons. Package: condor-doc Source: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5868 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.7.1+git837-g37b7fa3-1~nd60+1_all.deb Size: 1276270 SHA256: 39a0c87eed8b08dc7fe710f82d422168392ff1e7140856fe81479f1f798a19ff SHA1: 8d916ce1f24fbf7a5021eb01fc62614a8b495f04 MD5sum: f86f30c5b3b53894095b62cef7d36a2f 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: 3.3.4-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3452 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), libncurses5 (>= 5.7+20100313), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0) Suggests: coop-computing-tools-doc, condor, gridengine-client Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.3.4-1~nd60+1_i386.deb Size: 1319332 SHA256: dec6890f449cd361fd76778249ffd0ac8716365d2e6e3dc8968d8c48453eaaaf SHA1: 38f03bbb62966fe53d5a5d581e856f668b325ad6 MD5sum: d49aae36d7ce7e3b832304cc25de69dd Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.3.4-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1008 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.3.4-1~nd60+1_i386.deb Size: 228596 SHA256: 06833a782b7860f6242e239aaf1de278db0d9b64eb5e08b49fe81a470ebe5485 SHA1: 34e527ac4f1a5a4ee9c04fa21d3571321442485c MD5sum: 8c496621bf394bfecc32aa06a4931f9d Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.3.4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2512 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.3.4-1~nd60+1_all.deb Size: 280236 SHA256: 5295c6a85db5e505e66f83723693cb3527ef697314265eca49e6255d13587676 SHA1: f6814e1520750606f3ed0dabbf2d333e144a2a3d MD5sum: 46323dd54e4ebbdb5b3173f58e4c5f28 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: 1.5-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libfftw3-3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.5-1~nd60+1_i386.deb Size: 33404 SHA256: 14e482aea474a0bc74ee743992f8b294c3b26dee7ac16ef67c5d246f311d1452 SHA1: ae6af221cd90e3445cbe3c5012b439c4de52ce51 MD5sum: 5ceef64e5fc3e2e14e400905f70fbc76 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: dicomnifti Version: 2.29.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 432 Depends: neurodebian-popularity-contest, 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_2.29.1-1~nd60+1_i386.deb Size: 148434 SHA256: ae76f7cb93ef115965506ab5b67a2f2c1e1b4a6b230e9cb0cbebdd94b090cbe8 SHA1: f59bff3ce5961e3c0d25a26bf1d503e63e4ec517 MD5sum: 09e1207255efb1b79425616abb563ab1 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+4.1.9-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3816 Depends: neurodebian-popularity-contest, 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+4.1.9-1~nd60+1_i386.deb Size: 1494582 SHA256: 37f693a2a56971b60bc7232897b1fb6e6c89828bd3978524731cb69b2c91cdd8 SHA1: a0e35082316bacfcf7c1adf7eda09a470591543c MD5sum: bd23b329000bf34f55cbbd115fecd661 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.9-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3124 Depends: neurodebian-popularity-contest, qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.9-1~nd60+1_all.deb Size: 2351302 SHA256: 64c32f8bbbbbfddfc65e97d37eec4341d377874849c6e8f7f759aeae873e7a45 SHA1: 73726555ec7747f07c2bef1b77c62eb10e381e09 MD5sum: 66b10fb39b745b649ba377098763568b 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: glew-utils Source: glew Version: 1.6.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 336 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd60+1), libc6 (>= 2.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Replaces: libglew1.4 (<< 1.5) Homepage: http://glew.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.6.0-2~nd60+1_i386.deb Size: 119240 SHA256: 7bb9248b205d89470cfbc996472c9c68e6ee8bb113f2b2f3f3ffc3105aa90994 SHA1: 8b82d67d5a6b202e63f0daec7243f547ff5f5198 MD5sum: 24c78ab0a98d9faef843e4777b3d32fb Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew1.6-dev package. . This package contains the utilities which can be used to query the supported openGL extensions. Package: ipython01x Version: 0.11+git511-g039e00a-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4260 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python2.6, python (>= 2.6.6-3+squeeze3~), python (<< 2.7) Recommends: python-tornado (>= 2.1.0~) Suggests: ipython01x-doc, ipython01x-parallel, ipython01x-qtconsole, python-gobject, python-gtk2, python-matplotlib, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.11+git511-g039e00a-1~nd60+1_all.deb Size: 828574 SHA256: 8ac8b4d4950be99b87204fd658156da86b91f327aa79b033a561a7633c362ae9 SHA1: a7ac96c5d66c83a818c172b7c320d8539ccd4236 MD5sum: 002e6874c77e89b91f42aaf63c2c2b96 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.11+git511-g039e00a-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12900 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.11+git511-g039e00a-1~nd60+1_all.deb Size: 3982884 SHA256: 6b24acca2cf00257ee4f18b93c4c11b5cd6494bc4dc62301a92503ac3e2af0ac SHA1: a4f65f91e5840fad67a786a4d2a054e520416721 MD5sum: 853d27d4af369ef8781fd133cc44feed Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-parallel Source: ipython01x Version: 0.11+git511-g039e00a-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 584 Depends: neurodebian-popularity-contest, ipython01x (= 0.11+git511-g039e00a-1~nd60+1), python-zmq (>= 2.1.4), python Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-parallel_0.11+git511-g039e00a-1~nd60+1_all.deb Size: 111000 SHA256: e19ac2bdb48fa4ac60442938dcc5e1379673431e576ea9f5341c6d6b14b5143b SHA1: fee9d709d2fa35d3e8b607894f80b02cd2376db3 MD5sum: 5c2ea0f8ba51dbe96cd5c4847ae3e8fa Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the parallel processing facilities. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-qtconsole Source: ipython01x Version: 0.11+git511-g039e00a-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 296 Depends: neurodebian-popularity-contest, ipython01x (= 0.11+git511-g039e00a-1~nd60+1), python-pygments, python-qt4, python-zmq (>= 2.0.10.1) Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.11+git511-g039e00a-1~nd60+1_all.deb Size: 57462 SHA256: 998bdcde58229e4a50e4e39c1fb546c6f863a29b841977bde19b46839180d16d SHA1: d7253ea6b414f99d124d9f22e4c2be548549e82c MD5sum: 6f5e424929f1d35facb1c6ed26de9b47 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the qt console. Package: itksnap Version: 2.2.0-1~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: libcgroup-dev Source: libcgroup Version: 0.37.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd60+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd60+1_i386.deb Size: 17388 SHA256: 79c3c212bbed8d8fda78f0cdcf23fd0d805e2df91316dff332a7ba1a4289ddb7 SHA1: fa4bf61d34f3afd790c38398a04b6c32fe2cad2a MD5sum: 16db1692aaf22a8036fd523f12ff2f65 Description: Development libraries to develop applications that utilize control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . It provides API to create/delete and modify cgroup nodes. It will also in the future allow creation of persistent configuration for control groups and provide scripts to manage that configuration. Package: libcgroup1 Source: libcgroup Version: 0.37.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd60+1_i386.deb Size: 34188 SHA256: 616b8eb25c7293e96d36a0239b54c9f07e77ab6a727f30a87325feac6e426078 SHA1: d33ca3927c454927021c27986fba34631521e1d7 MD5sum: 1dee764c362c214452437398a0ab004a Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libclassad-dev Source: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 968 Depends: neurodebian-popularity-contest, libclassad2 (= 7.7.1+git837-g37b7fa3-1~nd60+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_7.7.1+git837-g37b7fa3-1~nd60+1_i386.deb Size: 289348 SHA256: 5a1aea53ce023e170f895611dbbeb79b9b06682cf03a461bb125a990085caefd SHA1: b7665d51e45576318de6ec2ea7185d2505d9fc36 MD5sum: 451d0f182f95d56dc4f7483ab9324cd3 Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad2 Source: condor Version: 7.7.1+git837-g37b7fa3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 532 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libpcre3 (>= 7.7), libstdc++6 (>= 4.4.0) Priority: extra Section: science Filename: pool/main/c/condor/libclassad2_7.7.1+git837-g37b7fa3-1~nd60+1_i386.deb Size: 216846 SHA256: 9f56d469a4822062c99c5f51869ea9b19b59e9ed1cee0720b58184bb9a9b42b4 SHA1: 863c6b293eb61cd8f3dcb4374b6e76f25ecea63d MD5sum: a7cc7f214bc05b10004e0ae37a402da8 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: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd60+1_i386.deb Size: 509864 SHA256: 0d32c7166359ad5be9daceb7cddc432ab9237844a8d558b6623449c71a29855d SHA1: 99f1f3a137b7623a28a9a07e38a98448a485fb68 MD5sum: a0fc5b222e03136cab85c7c08e201b6f Description: lightweight C++ template library for linear algebra Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . Unlike most other linear algebra libraries, Eigen 3 focuses on the simple mathematical needs of applications: games and other OpenGL apps, spreadsheets and other office apps, etc. Eigen 3 is dedicated to providing optimal speed with GCC. A lot of improvements since 2-nd version of Eigen. Package: libeigen3-doc Source: eigen3 Version: 3.0.1-1.1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10624 Depends: neurodebian-popularity-contest, ttf-freefont, libjs-jquery Suggests: libeigen3-dev Homepage: http://eigen.tuxfamily.org Priority: extra Section: doc Filename: pool/main/e/eigen3/libeigen3-doc_3.0.1-1.1~nd60+1_all.deb Size: 2644024 SHA256: 695a17eef4aa0e2f79eca25972103ab07407d4cf73bc007b9fb28df0786b347e SHA1: 01875672385364e3b13d603cd81d900cfc1c8c9e MD5sum: d691c4890c6c1d5aeea56244134001af Description: eigen3 API docmentation Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . This package provides the complete eigen3 API documentation in HTML format. Package: libfreenect-demos Source: libfreenect Version: 1:0.0.1+20101211+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: libglew1.6 Source: glew Version: 1.6.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 376 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.6_1.6.0-2~nd60+1_i386.deb Size: 119162 SHA256: 87d8389ce7f3b69527d62908c9f9440528585e7bdafe094e418ecaed33fad033 SHA1: e9db378e6134c4a9f14ecd258cee28ccb208c843 MD5sum: 438ad19afeb9c09eb64228f85c1d4262 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.6-dev Source: glew Version: 1.6.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1332 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd60+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.5-dev Provides: libglew-dev, libglew1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.6-dev_1.6.0-2~nd60+1_i386.deb Size: 235476 SHA256: 6fa26ca08382fead0831e35eaf17383ea9c97102ae87d92df27cd568381f588e SHA1: 26faee6f2212e385a69c43f9e6f26709bc4b90ed MD5sum: 062b838808d1f0231ecdfa550bce702d Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development documentation as well as the required header files. Package: libglewmx1.6 Source: glew Version: 1.6.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd60+1_i386.deb Size: 105664 SHA256: 7ec80b2493adc2230fb897297adab71ccd57b2e7838b79fbde1917334a5cfb82 SHA1: 3cd4c7746f98c14875ca01d39d6c077cbfc3ea4a MD5sum: 87a0e001446761173f8910989731d94e Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.6-dev Source: glew Version: 1.6.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 380 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd60+1) Conflicts: libglewmx-dev, libglewmx1.5-dev Provides: libglewmx-dev, libglewmx1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.6-dev_1.6.0-2~nd60+1_i386.deb Size: 93302 SHA256: bc48dbe309b340b26102ff91af3d3b0a5deaa0ab5d77baf958278587f145bfce SHA1: 06b5224f911043bedbafc968601fc1748efc2cae MD5sum: f29e3d954d647d16e46e86187cfe21f8 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development libraries compiled with GLEW_MX Package: 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: libopenwalnut1 Source: openwalnut Version: 1.2.5-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4952 Depends: neurodebian-popularity-contest, ttf-liberation (>= 1.0.0), libboost-date-time1.42.0 (>= 1.42.0-1), libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-regex1.42.0 (>= 1.42.0-1), libboost-signals1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libboost-thread1.42.0 (>= 1.42.0-1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph65 (>= 2.8.3), libopenthreads13 (>= 2.8.3), libstdc++6 (>= 4.4.0) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.2.5-1~nd60+1_i386.deb Size: 1600056 SHA256: 07a1d3b2efdc9263898f6628e91b12302fc3ea7a58f92860e852b2a365134cea SHA1: 5fe75d1d5f9259cf242faa89953872728b5e1145 MD5sum: 33976f16bd8d2f826fd0d1b4caf6b3e8 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.2.5-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2092 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.2.5-1~nd60+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 2.8.1), libopenthreads-dev (>= 2.8.1), libboost-dev (>= 1.42.0), libboost-program-options-dev (>= 1.42.0), libboost-thread-dev (>= 1.42.0), libboost-filesystem-dev (>= 1.42.0), libboost-date-time-dev (>= 1.42.0), libboost-system-dev (>= 1.42.0), libboost-signals-dev (>= 1.42.0), libboost-regex-dev (>= 1.42.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.2.5-1~nd60+1_i386.deb Size: 262318 SHA256: 78ef40bb60a2a74cdd9c3c05861f9d81037b6395ea66ff3a324993c20d03d618 SHA1: 2852278fed8a167787b81f5ad3f1454da7d0aff6 MD5sum: 52faec4f788af3aec1a1ac1229e2f696 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.2.5-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41228 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.2.5-1~nd60+1_all.deb Size: 4250672 SHA256: 187d9db9af70ee2c4eed8c47e487a7b1d334f0e80b99634efb5f2569c36e7d6f SHA1: f1960a9063e1a4aaa672f01ecde74e0fba3d6c74 MD5sum: f257fecd36b6860f03e27ea4575b8c51 Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd60+1_i386.deb Size: 7618 SHA256: 90c71d1b9da201a45a899f3927e65fa2b09d7786c45cccbc2f1019808896da0f SHA1: f8f1d896274bd85e4830bfe36b233cf8b8a0a0a0 MD5sum: bf0f569cd090e6d20596e26a878625c8 Description: PAM module to move a user session into a cgroup Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This PAM module will move a user session into an existing cgroup by attempting to match uid and gid against the defined cgroup rules configuration. Package: libpgm-5.1-0 Source: libpgm Version: 5.1.116~dfsg-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 312 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://code.google.com/p/openpgm/ Priority: optional Section: libs Filename: pool/main/libp/libpgm/libpgm-5.1-0_5.1.116~dfsg-2~nd60+1_i386.deb Size: 173402 SHA256: 7525f979e98cf0f77004fc6cdd6b560c7f21692fd91a5d28ebacfd5643fb4ca5 SHA1: d121767b6975fb87b8330a40abe9c8c9bb84f077 MD5sum: 5eee85dfa687f3e9ccbec83c9456ec5e Description: OpenPGM shared library OpenPGM is an open source implementation of the Pragmatic General Multicast (PGM) specification in RFC 3208 available at www.ietf.org. PGM is a reliable and scalable multicast protocol that enables receivers to detect loss, request retransmission of lost data, or notify an application of unrecoverable loss. PGM is a receiver-reliable protocol, which means the receiver is responsible for ensuring all data is received, absolving the sender of reception responsibility. PGM runs over a best effort datagram service, currently OpenPGM uses IP multicast but could be implemented above switched fabrics such as InfiniBand. . This is the runtime package for programs that use the OpenPGM library. Package: libpgm-dbg Source: libpgm Version: 5.1.116~dfsg-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 532 Depends: neurodebian-popularity-contest, libpgm-5.1-0 (= 5.1.116~dfsg-2~nd60+1) Homepage: http://code.google.com/p/openpgm/ Priority: extra Section: debug Filename: pool/main/libp/libpgm/libpgm-dbg_5.1.116~dfsg-2~nd60+1_i386.deb Size: 224016 SHA256: 75ec87ca26bf5d0b642c7098b66bad3d0fb3102bd9809739761bd929704ec9ad SHA1: 23110dbb465f0b8c132070b01ea54660e3caed64 MD5sum: 64a0e8b9945eed4ba0714353b7a46513 Description: OpenPGM debugging symbols OpenPGM is an open source implementation of the Pragmatic General Multicast (PGM) specification in RFC 3208 available at www.ietf.org. PGM is a reliable and scalable multicast protocol that enables receivers to detect loss, request retransmission of lost data, or notify an application of unrecoverable loss. PGM is a receiver-reliable protocol, which means the receiver is responsible for ensuring all data is received, absolving the sender of reception responsibility. PGM runs over a best effort datagram service, currently OpenPGM uses IP multicast but could be implemented above switched fabrics such as InfiniBand. . These are the debugging symbols for the library and its utilities. Package: libpgm-dev Source: libpgm Version: 5.1.116~dfsg-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 592 Depends: neurodebian-popularity-contest, libpgm-5.1-0 (= 5.1.116~dfsg-2~nd60+1) Conflicts: libnetpbm9-dev Homepage: http://code.google.com/p/openpgm/ Priority: optional Section: libdevel Filename: pool/main/libp/libpgm/libpgm-dev_5.1.116~dfsg-2~nd60+1_i386.deb Size: 230920 SHA256: a33f3ebd9a7ec5b60a7e64b206996118d443377444231dd67a8782217fe3a042 SHA1: ea719d7a9db052726f1404f2de2efe768509f341 MD5sum: 9f08f5b663518e2c0ef8b5290d5e9bfa Description: OpenPGM development files OpenPGM is an open source implementation of the Pragmatic General Multicast (PGM) specification in RFC 3208 available at www.ietf.org. PGM is a reliable and scalable multicast protocol that enables receivers to detect loss, request retransmission of lost data, or notify an application of unrecoverable loss. PGM is a receiver-reliable protocol, which means the receiver is responsible for ensuring all data is received, absolving the sender of reception responsibility. PGM runs over a best effort datagram service, currently OpenPGM uses IP multicast but could be implemented above switched fabrics such as InfiniBand. . This is the development package which contains headers and static libraries for the OpenPGM library. 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: libzmq-dbg Source: zeromq Version: 2.1.7-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1668 Depends: neurodebian-popularity-contest, libzmq1 (= 2.1.7-1~nd60+1) Homepage: http://www.zeromq.org/ Priority: extra Section: debug Filename: pool/main/z/zeromq/libzmq-dbg_2.1.7-1~nd60+1_i386.deb Size: 671484 SHA256: 2a17b02473f1f4b3fb34d0622d020fa291841d97b6c836b71de6d85c2fba42bc SHA1: dc6372bdf48bfcdc6c8aa1fe3ef5d2c3bdf43919 MD5sum: 35f5823d56817931aeb55ef20d14ee1f Description: ZeroMQ lightweight messaging kernel (debugging symbols) The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more. . This package contains the debugging synmbols for the ZeroMQ library. Package: libzmq-dev Source: zeromq Version: 2.1.7-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 848 Depends: neurodebian-popularity-contest, libzmq1 (= 2.1.7-1~nd60+1) Homepage: http://www.zeromq.org/ Priority: optional Section: libdevel Filename: pool/main/z/zeromq/libzmq-dev_2.1.7-1~nd60+1_i386.deb Size: 336632 SHA256: 81183f7f8942d486fbcc88f228ea5d67db9c4383eb2968da2958264e9c100b68 SHA1: ce5be2e7219646925666d7c3f06c9ac98aefcbb4 MD5sum: 2e51a1ac43b58f1daabe4aaba90a380f Description: ZeroMQ lightweight messaging kernel (development libraries and header files) The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more. . This package contains the ZeroMQ development libraries and header files. Package: libzmq1 Source: zeromq Version: 2.1.7-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 396 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libpgm-5.1-0 (>= 5.1.116~dfsg), libstdc++6 (>= 4.2.1), libuuid1 (>= 2.16) Homepage: http://www.zeromq.org/ Priority: optional Section: libs Filename: pool/main/z/zeromq/libzmq1_2.1.7-1~nd60+1_i386.deb Size: 223142 SHA256: e1140f134cbfa2fa5a515b3fa449e0764ea8bfba382d4c58a36cadb3ab3a9090 SHA1: 9bc56eecefd9fc24e7ba7784dc72c8fc95250841 MD5sum: 2ed04feb85fa88edc93f1f47b416597e Description: ZeroMQ lightweight messaging kernel (shared library) The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more. . This package contains the ZeroMQ shared library. 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: 0.0.17~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.17~nd60+1_all.deb Size: 6714 SHA256: c9d8769cacb4434c53f934103443e67c2d7fcab602d844981859e19d5502083f SHA1: 7dab897a32b5738abfc1d0f2922dc09ceeafdfe4 MD5sum: 5cd8e52173ced3af71ff2a4fa0f5c598 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mitools Source: odin Version: 1.8.1-3~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: 2.0.217-3~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2112 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_2.0.217-3~nd60+1_i386.deb Size: 766754 SHA256: a8d842a1add5b2d940f664df47cdf5570940575a3e0f2c82d3bd6558760ee3ae SHA1: b98f99c53ab5d4f547fb3ad84e3533e6913e4e61 MD5sum: c003d19047bec91265024cbc14b8b05a Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20110812.1~dfsg.1-1~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_0.20110812.1~dfsg.1-1~nd60+1_i386.deb Size: 4077572 SHA256: 682ed00f27b623aa28fd412ff9b4a85ac0bcc114e9a78cb4e6573fc53e641fb2 SHA1: 036e6cf55ef27b309ba0d43bca060cb8171053fe MD5sum: 8ed2647d71ad3dcd6bc9c1831b4a5039 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20110812.1~dfsg.1-1~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_0.20110812.1~dfsg.1-1~nd60+1_all.deb Size: 1666862 SHA256: bded81e3b313fa771e7093c3f0bb7b02863a51b639557b449075d8c40b8db1f8 SHA1: 01ba88abd684db564ed60256faa8fa29a44a6b29 MD5sum: 90c797bbd3a1ab0d932f571e93b4df28 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20110812.1~dfsg.1-1~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_0.20110812.1~dfsg.1-1~nd60+1_all.deb Size: 738344 SHA256: 9d3809ef7908369dfcdc7031e23a3576efc6104f004dd685df7a99ead165cd95 SHA1: a7f30ea73829619c6bc057111d0ce45f0e80ae6a MD5sum: 4916863cc74d60bb0862906cafad154a 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+svn2265.dfsg1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2148 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, libglew1.6 (>= 1.6.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libopenal1, libpciaccess0 (>= 0.8.0+git20071002), libraw1394-11, libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.8), libx11-6 (>= 2:1.2.99.901), libxext6, libxi6 (>= 2:1.2.99.4), libxml2 (>= 2.6.27), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2265.dfsg1-1~nd60+1), psychtoolbox-3-lib (= 3.0.9+svn2265.dfsg1-1~nd60+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.9+svn2265.dfsg1-1~nd60+1_i386.deb Size: 696520 SHA256: 8375c321dd58ced69c4ba4a2302b16623bc5d67b87aa376db243226a2da84822 SHA1: c10f2bb6d22882f03ac09319514bc262be786bea MD5sum: 46e91faa13f4f178f371de4a9c76386e Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains bindings for Octave. Package: odin Version: 1.8.1-3~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: 0.24-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5544 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~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.24-1~nd60+1_all.deb Size: 3580580 SHA256: 085839e3b54346316ab0fb8ab75a409f9f985737e5dcfc5fb438e7094d301b19 SHA1: 364b976d9269fcb1917cb163fde9f6509cf7b856 MD5sum: 4631fc29d71b32f7fd37def9a1380d67 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: openwalnut-modules Source: openwalnut Version: 1.2.5-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13184 Depends: neurodebian-popularity-contest, libbiosig0, libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-regex1.42.0 (>= 1.42.0-1), libboost-signals1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libboost-thread1.42.0 (>= 1.42.0-1), libc6 (>= 2.3.2), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph65 (>= 2.8.3), libopenthreads13 (>= 2.8.3), libopenwalnut1, libstdc++6 (>= 4.4.0) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.2.5-1~nd60+1_i386.deb Size: 4449416 SHA256: 9af2a05fe15d85269801ab6b470cecd1af2d17c34e760721c6ac9323798de770 SHA1: 1960c7996c6eadd7ff295ec0d86e9c7b27645f02 MD5sum: 289de1d0c8f68ceca3fdaffbb67c4f6b Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.2.5-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1792 Depends: neurodebian-popularity-contest, libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-program-options1.42.0 (>= 1.42.0-1), libboost-regex1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libboost-thread1.42.0 (>= 1.42.0-1), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libopenscenegraph65 (>= 2.8.3), libopenthreads13 (>= 2.8.3), libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqt4-webkit (>= 4:4.6.0), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.0), libstdc++6 (>= 4.2.1) Recommends: openwalnut-modules (= 1.2.5-1~nd60+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.2.5-1~nd60+1_i386.deb Size: 616782 SHA256: 3f5aee32dbacd5d838489dd76dc920ebdb44c097ac030859e96964f78730e528 SHA1: 6404d4c29cdc8b3fa96a795388ddb6f70ae0d601 MD5sum: 36ab213821f85a51fcdab51fc17b229d Description: Multi-modal medical and brain data visualization tool. OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: packaging-tutorial Version: 0.2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 836 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.2~nd+1_all.deb Size: 680180 SHA256: 4f1c39bc3f108a98284df69fc1734c3eb97957be6e441928596ccbf1ba0d1292 SHA1: 1117c3ff4a15d620a0d8fc62edcc1bfcf45e6329 MD5sum: a3c8023d51d265c6a801496c98620528 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: psychopy Version: 1.71.00.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5004 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.71.00.dfsg-1~nd60+1_all.deb Size: 2655642 SHA256: e65dd8a52a15c4535baabcb74252049b753824a04559562d3c2f070f0ef44306 SHA1: 8efefd5d61bed64da431fee088fdab1cc12f2c2f MD5sum: 172cba68be68eed2c0c277e81775b975 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+svn2265.dfsg1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 54300 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2265.dfsg1-1~nd60+1_all.deb Size: 19675234 SHA256: ea36a3514a3645a802eed43edcfb90fcca2a362d78cc73474bfbfcf39c923825 SHA1: 05006a9442a97c705e65b3ec55df952e76bf9f35 MD5sum: ded9aed348f546688f5a4a021acd6823 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.9+svn2265.dfsg1-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2240 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2265.dfsg1-1~nd60+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2265.dfsg1-1~nd60+1_i386.deb Size: 749096 SHA256: c6f8d40a2b77c1c60523b49cabfb2532c203e0d98961d7ffb32544849792c649 SHA1: 86643340fa7c826d7936708cf3d8153a2a194276 MD5sum: 5e98eb99bc40c28d72a107d143e8e505 Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.9+svn2265.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) Recommends: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good Suggests: gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.9+svn2265.dfsg1-1~nd60+1_i386.deb Size: 61486 SHA256: d572ccaccaacc3ff13a51504794abaa6340540f692aa1f563e539793660dbf18 SHA1: b38fffe234a36c82e3857ff08f25b691c8cacd99 MD5sum: ef9463359dda29c3b51082b37c8d9d23 Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~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: 0.5.0-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2068 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-2~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_0.5.0-2~nd60+1_all.deb Size: 1457522 SHA256: 46325edad837ac6a4a9c49e857d85e8ea3f97c5287295c64091e041657603b0b SHA1: 9ab04398085bd6386ecfc29605de87b0374e87cf MD5sum: 59a1fcdd7103a9abd9a4e14d0e4bafa3 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: 0.5.0-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3224 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.5.0-2~nd60+1_all.deb Size: 1943674 SHA256: 7354aa71350ecee3334dbbc688bf7dde6f6cab57d3cdca5a8effc3b8c3922a3a SHA1: 5bf007b3a1694b96a555d25a70160a708fa1aa16 MD5sum: 804d946e5d628819438b23760007c57e Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.5.0-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1068 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~) Provides: python2.5-dipy-lib, python2.6-dipy-lib Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-2~nd60+1_i386.deb Size: 367942 SHA256: 0ca3ac60b5f16cb1f142d10687dd4070ae844a5d60b584915871ea6542be1c24 SHA1: 3e47f4e42f9139b2613e2cbfcf5f45089bbad568 MD5sum: 00adafebac64a1b30f27fc27ef11e7af Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.5, 2.6 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: 0.5.4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.5.4-1~nd60+1_all.deb Size: 44438 SHA256: 69f38da17592d4791db35b30332bf4d59a65f6067b06b23ec1b9b1dfb576cf9e SHA1: de7acb7437565669b409b14114816977e4276f25 MD5sum: d5288b17727fdb006a46d08240efb317 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-mvpa2 Source: pymvpa2 Version: 2.0.0~rc5-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4588 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa2-lib (>= 2.0.0~rc5-1~nd60+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py, python-psutil Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa2-doc, python-sklearn Provides: python2.5-mvpa2, python2.6-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.0.0~rc5-1~nd60+1_all.deb Size: 2309346 SHA256: f4b7f1352045c4c20027f706ff582fe59ca96162b71022c750ca4d87b5b07c59 SHA1: 1983328fc83e0b4c0d39530b50db178afe7e2f13 MD5sum: 6b3fa97dfa00d4d4723cc5cf04b0704b Description: multivariate pattern analysis with Python PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa2-lib Source: pymvpa2 Version: 2.0.0~rc5-1~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-mvpa2-lib, python2.6-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.0.0~rc5-1~nd60+1_i386.deb Size: 69346 SHA256: 843319e99b7dbef3fdb6431b1d07f4a539e3fabf1a84536a747ddfbb0ce8e3a4 SHA1: 033390c2dad3d8efa06dd99b826af633c6a9f21e MD5sum: 6395488934bda93fbd95ec8efaa38ce2 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: 0.20100607.1-4~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1356 Depends: neurodebian-popularity-contest, 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_0.20100607.1-4~nd60+1_i386.deb Size: 350268 SHA256: 6ea8eca5f252e0af09025f34f9ad58fea71fb754d3f209fc63ded99bae9eaa99 SHA1: 71ccde4501d1e6dbfbd815b724d2f5b1b2873403 MD5sum: b424cd468d1fedc7c4aa826c330510af 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+201100720-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3404 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+201100720-2~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+201100720-2~nd60+1_all.deb Size: 702872 SHA256: b06538a2746f94ad3a7335936aafc34b0809e9f4bb0e05aa4aa039c09e09cc1f SHA1: 86d7a1a6857a275ba27715f0b566b02f492fd278 MD5sum: 1acca94309ff3e10d78dbdf598f10d3a 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+201100720-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9404 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+201100720-2~nd60+1_all.deb Size: 2499038 SHA256: 8770274cf6e839f713cd3ae12de2c3f654602b57089f95b60de831747249ae5a SHA1: 0e51987975705cc3bdb7e70f3f17a0d179579693 MD5sum: 509915867894e31ae7bc4e0a71774b32 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+201100720-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4048 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+201100720-2~nd60+1_i386.deb Size: 1298650 SHA256: 5eab510c9776e66c396df4a4d9826ecdb2896750b972c859771047524165daae SHA1: cd61cb2185778fb846d03758e17e8402ce3c269d MD5sum: 3e33eddfaee99c21998d44b4f84fd664 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+201100720-2~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4336 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+201100720-2~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+201100720-2~nd60+1_i386.deb Size: 1418602 SHA256: a23a9de29012e207a5d33a420e2f155dfa7bfa41528da257e425a328447e9aa9 SHA1: b7b16eb70afc540457ff7b7be0050c2b9b861f38 MD5sum: 321a2a0444b6ac30aec15e1cc1693ba3 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: 0.4.1-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2156 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat Provides: python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.4.1-2~nd60+1_all.deb Size: 388876 SHA256: 8893491ad97bf73e0f1eedec60b6197b7b30d04e484daa8b017a26d2776b4d16 SHA1: 29da03d134150c3ba75ebc9abff9f154508b5a21 MD5sum: d302e4035b9205d9e9365cbc4d13a916 Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.4.1-2~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4188 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.4.1-2~nd60+1_all.deb Size: 999272 SHA256: 6473da0a37f1a62772ea73aba81af3c53a6b72af1e4a9720e08f6a401780a2c3 SHA1: cb1e6e4deae3e49d5ed4662c5eaaec0147c21059 MD5sum: 66fa55872ac59867bd842a3be3a4708f Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.3.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9404 Depends: neurodebian-popularity-contest, python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.3.1-1~nd60+1_all.deb Size: 3902360 SHA256: cd914d865016b42129e59cdb6f99297bb9604fe9b498fba345a431a25f434825 SHA1: 306e359a84f7c65aef4526973a25bec42d93359e MD5sum: ee0f6180d968002a8747b38906ba7457 Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.3.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6944 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.3.1-1~nd60+1_all.deb Size: 5196638 SHA256: 7cf716dc54b6f6783ac356d4f12d3dc7544a504bf3d53a4477d3f6ab4b60fc1d SHA1: c40e868d4f89f4e75668afffaab1ec560d5448bb MD5sum: a1fd0096c86853b78bdd1b664d4be6ac 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-openopt Source: openopt Version: 0.34+svn1146-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1448 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.5-openopt, python2.6-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.34+svn1146-1~nd60+1_all.deb Size: 206376 SHA256: d1b3b6379d8d46c62e5e9e5d047952c1f3ffe49ea2b8104d0b266ec8bacb737d SHA1: 544a48be67be1c7f787e3cd97aa71756436b544e MD5sum: cb479f230839071416b792363f23e650 Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: 2.5, 2.6 Package: python-openpyxl Source: openpyxl Version: 1.5.5-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 456 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_1.5.5-1~nd60+1_all.deb Size: 65568 SHA256: a094d26fa658f247c9de582685a6b3ea950f180e68e6d73c538a5810b66e969a SHA1: 70bda53bdad349a1c66df7109a576816865f0952 MD5sum: 7fe2557035d654c6a4ef7550a6189f8e Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.4.3-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1372 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-dateutil, python-pandas-lib (>= 0.4.3-1~nd60+1) Recommends: python-scipy, python-matplotlib, python-tables, python-tz, python-xlrd, python-scikits.statsmodels Suggests: python-pandas-doc Provides: python2.5-pandas, python2.6-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.4.3-1~nd60+1_all.deb Size: 261602 SHA256: 2ac99ab04d459bc6422f61f5ff1ea497be9ca29d54926fd04b3e2b3fdb0fedf6 SHA1: ba083cd891a13978fa1bf6b7e3a1b4664c0f845c MD5sum: b5fcc83e61992a11e6cb8744bba37cf6 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure Package: python-pandas-lib Source: pandas Version: 0.4.3-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1728 Depends: neurodebian-popularity-contest, 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-pandas-lib, python2.6-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.4.3-1~nd60+1_i386.deb Size: 545458 SHA256: 23c03a823b846860f8c7716ac72d180aaef3ff9535ccb77df928c6c2020ba509 SHA1: 57e6d90ece12b733cd772992655325f85ad369c6 MD5sum: 8cdbfec3128ef01460261960af68292b Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. Python-Version: 2.5, 2.6 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: 0.9.0.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.9.0.dfsg-1~nd60+1_all.deb Size: 17096 SHA256: 8cec49a06822b1db8a46490cd5a979c6199caf004b5470ce66f1b64908d28371 SHA1: 3495ba92a2f3f4ef92b9119f010e9400fe931d51 MD5sum: 668d91e7cf5ee1b06b58bf835d903da4 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scikits-learn-doc Source: scikit-learn Version: 0.8.1.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14620 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-scikits-learn-doc_0.8.1.dfsg-1~nd60+1_all.deb Size: 9030600 SHA256: a28897ce359a9e03db9a20be13be45f14beed13616b9cdec198c66c6698cce7e SHA1: 3af9eb33a4f1c7becaf6a315dd9cd92fe5d1c6ac MD5sum: 5cdbe23aace03de906cc994860250aba Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikits-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.8.1.dfsg-1~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_0.8.1.dfsg-1~nd60+1_i386.deb Size: 874376 SHA256: 3d96fcc447cf167d71b22191919efaafd8fe05021635a3e1b67198322b7e87c2 SHA1: 201a1c06b8539222681864d9ca66ccb4d144c5f5 MD5sum: cbff571aecd366f7aa2a0b649e20b3be 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-scikits.statsmodels Source: statsmodels Version: 0.3.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13284 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Conflicts: python-scikits-statsmodels Replaces: python-scikits-statsmodels Provides: python2.5-scikits.statsmodels, python2.6-scikits.statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.3.1-1~nd60+1_all.deb Size: 3100076 SHA256: 2228332531c3340ee140a4eb21306710d87ccbe81211054f9d4a94cdc37f5f08 SHA1: ede9c1cc06c65928a90288c6645c3bd63799fb3f MD5sum: 015b6306a732cb1595d5f9b99d00c775 Description: classes and functions for the estimation of statistical models scikits.statsmodels is a pure Python package that provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Python-Version: 2.5, 2.6 Package: python-scikits.statsmodels-doc Source: statsmodels Version: 0.3.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 18676 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits.statsmodels Conflicts: python-scikits-statsmodels-doc Replaces: python-scikits-statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-scikits.statsmodels-doc_0.3.1-1~nd60+1_all.deb Size: 1877016 SHA256: af9e8f12149db8daab73735f1f472d2d2cf74f20fd090514c6c50c469ed04654 SHA1: d948b27438c4626412fd4a9fbfa404761d0e71d6 MD5sum: ce20bc121630c5216ba8d600e606cb6a Description: documentation and examples for python-scikits.statsmodels This package contains HTML documentation and example scripts for python-scikits.statsmodels. Package: python-simplegeneric Source: simplegeneric Version: 0.7-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Provides: python2.5-simplegeneric, python2.6-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd60+1_all.deb Size: 9802 SHA256: a1f16f30724b88550716edbaacbaedaea6dbcc88a2a5e22f375896ba31e71c5e SHA1: af5b697130da85854bdb717319c7ae2aa719b9ae MD5sum: 34b6361e577be81e7cc33b0597a0b491 Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-sklearn Source: scikit-learn Version: 0.9.0.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2452 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.9.0.dfsg-1~nd60+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.5-sklearn, python2.6-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.9.0.dfsg-1~nd60+1_all.deb Size: 770552 SHA256: 73655622749cabd0f9cb3240d973e58d0b51dd9b3930e088f61462934df927e2 SHA1: 82ad490eedb3625c527ef1fdbd8dcde13debb71b MD5sum: 352dc681f5b092061062d2d48a2740b4 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-sklearn-doc Source: scikit-learn Version: 0.9.0.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21628 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.9.0.dfsg-1~nd60+1_all.deb Size: 12871374 SHA256: 4662aae3f7847670914541d44a8ba081662f4ca21a8a70d2178a9363e3f7352a SHA1: afd9889d09bc762910efe5a9c1c5cea150e77b2b MD5sum: 9325b95da761e3d8ddf99b74b742dd8e Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.9.0.dfsg-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2776 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.5-sklearn-lib, python2.6-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.9.0.dfsg-1~nd60+1_i386.deb Size: 1017326 SHA256: 8e61f5e58b37df8c1a97ec66d32ec7f367c744d73160c5766a105c882d3ba844 SHA1: 3dc90db36bccf05cc50f9081da8786d3f8b40b36 MD5sum: e2f3f25e56bab28f50948a1970274a04 Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 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: 0.10.18-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 488 Depends: neurodebian-popularity-contest, libc6 (>= 2.2), libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python-numpy Recommends: python-matplotlib, python-scipy Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.10.18-1~nd60+1_i386.deb Size: 221414 SHA256: 5fc4311c401fedef756687e0edc91c28202b80e060e06be4641353c0575b6c7f SHA1: 028d5406abdef9af5e2ba09fcb55707357b11166 MD5sum: 5b84055f3e045777de0ef29ecf910038 Description: A Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.1+git21-g55debc4-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 124 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.1+git21-g55debc4-1~nd60+1_all.deb Size: 21884 SHA256: 1392484fefab1ea5e5ce5773e6f06fd0870b2afd798e76d5c206db89e96829a3 SHA1: fbb62e3e6965f0bc36b184327229fa6f7225d548 MD5sum: df1682e2c3064438e72654dd36adb6c1 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.5, 2.6 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: python-tornado Version: 2.1.0-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 956 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), python2.6 | python2.5, python (>= 2.6.6-3+squeeze3~), python-pycurl, ca-certificates Recommends: python-mysqldb Breaks: python (>= 2.7), python (<< 2.5) Homepage: http://www.tornadoweb.org/ Priority: optional Section: python Filename: pool/main/p/python-tornado/python-tornado_2.1.0-1~nd60+1_i386.deb Size: 225880 SHA256: 2b4c0638b613d932c6aacf5bcfd223ad787becf3fe2c4fa61da05acd4bc1c2c4 SHA1: 9eb06cb9fba31fc35f2248f8a95538f54e99dd2e MD5sum: a4ce3b5c07fcb82a663866c72b7f674a Description: scalable, non-blocking web server and tools Tornado is an open source version of the scalable, non-blocking web server and tools that power FriendFeed. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the underlying non-blocking infrastructure. Package: python-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd60+1 Architecture: i386 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 2216 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd60+1_i386.deb Size: 380508 SHA256: d7ee493025ddf2d471587233bf0066f8f95c32708576e507dc88a65b3fabe08e SHA1: 4069a834a800297b6d3fba47d2a80f86c55abdf1 MD5sum: 64192ea2b1596f3197799ca79e3cd996 Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python-tz Version: 2011h-0.1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, tzdata, python, python-central (>= 0.6.11) Homepage: http://pypi.python.org/pypi/pytz/ Priority: optional Section: python Filename: pool/main/p/python-tz/python-tz_2011h-0.1~nd60+1_all.deb Size: 46922 SHA256: 358ffca351d867546f34bb4e9393d6944e63e7a817f3a1eb704396a28faa3bfc SHA1: 1f3c649c4ec7910443ecc3b70d458f04a118e77b MD5sum: 4eabe87106517e2815abcd9c5f491784 Description: Python version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). Python-Version: all Package: python-zmq Source: pyzmq Version: 2.1.7-1~ndcustom1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1076 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libzmq1, python2.6 | python2.5, python (>= 2.6.6-3+squeeze3~) Breaks: python (>= 2.7), python (<< 2.5) Provides: python2.5-zmq, python2.6-zmq Homepage: http://www.zeromq.org/bindings:python Priority: optional Section: python Filename: pool/main/p/pyzmq/python-zmq_2.1.7-1~ndcustom1_i386.deb Size: 298724 SHA256: c0bcb7fab8826008b4fbaea2a8a0a95540ff78a50f41593e4a22f4aea27271fb SHA1: 713cce6606910227a4227086c0268bf91e7ba82a MD5sum: 9a0d00823d5a011d7f8506c56b3af78b Description: Python bindings for 0MQ library Python bindings for 0MQ. 0MQ is a small, fast, and free software library that gives you message-passing concurrency for applications in most common languages. . The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more. Python-Version: 2.5, 2.6 Package: python-zmq-dbg Source: pyzmq Version: 2.1.7-1~ndcustom1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2088 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.6-6~), libzmq1, python2.6-dbg | python2.5-dbg, python-zmq (= 2.1.7-1~ndcustom1) Recommends: python-dbg Breaks: python-dbg (>= 2.7), python-dbg (<< 2.5) Homepage: http://www.zeromq.org/bindings:python Priority: extra Section: debug Filename: pool/main/p/pyzmq/python-zmq-dbg_2.1.7-1~ndcustom1_i386.deb Size: 804514 SHA256: b17cf9674446fa7a927c0da2c468db1b937ba411c630aa69caf40a637247fcc6 SHA1: ec0e9a17f61041394485aeae1d0d3d560431b8b4 MD5sum: 9e1201673613252bfa881489e8561b08 Description: Python bindings for 0MQ library - debugging files Python bindings for 0MQ. 0MQ is a small, fast, and free software library that gives you message-passing concurrency for applications in most common languages. . The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more. . This package contains the extension built for the Python debug interpreter. 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: stabilitycalc Version: 0.1-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd60+1_all.deb Size: 28608 SHA256: 997379d03b4381e98ba743db58b918585f79a077ba7dbb726e745841a0ac402e SHA1: 1efb3b900d33eec54f3893e4affe87eda15bd8d2 MD5sum: 66d13f8fbd8d79e87fa99a0e8cab8cd0 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.5, 2.6 Package: stimfit Version: 0.10.18-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2008 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_0.10.18-1~nd60+1_i386.deb Size: 758590 SHA256: b8432f082311585fb16cf3d4702256842b6564752024c481def6a999aa7962d6 SHA1: d828fe87778957055a4833b614805d721e2f7b77 MD5sum: 0896f4cf07879c5a7dd4c45068de08a3 Description: A program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.10.18-1~nd60+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13096 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.10.18-1~nd60+1_i386.deb Size: 5020690 SHA256: 3aa620588ce06bc944245384a552db1888ef65ef2c742d55ef2e786a4bff8012 SHA1: 975b4e03c8393e34122d589ce937c11d6bc739e4 MD5sum: acca91b2d5e0637232d53ef0f9d39b96 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: ubuntu-keyring Version: 2010.+09.30~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd60+1_all.deb Size: 11798 SHA256: 6cbcf7d81718e041431125e45215b746615d2012dc64a2a6c9d2a30e4826fed3 SHA1: a7ba0e713d1052a7aa26930c48dc4aaf6e97bbd1 MD5sum: cb5b41c6b935192df8432bce736f15b6 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: 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.