Package: ants Version: 1.9.2+svn680.dfsg-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 35740 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.16, 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~nd10.04+1_i386.deb Size: 11189982 SHA256: 7e0423f00ae5237f7c82376e901e9555a7d92ab63880f7186458e5bcbadd6295 SHA1: da8c7253556f9cc039f3f40b53cd01ac65849034 MD5sum: bda1cd71c48c719d6801ad003d4fbf33 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~lucid.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~lucid.nd1_all.deb Size: 132470 SHA256: 2e22eebc483d94eeac7b8dede959f75add3268e432e7a878c5d39e61a129c58a SHA1: 51c20f3f9a968af47adc9bc6dff312a0ad1abd2a MD5sum: b24e68173b3ce290b28f85c017f3a7b6 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~nd10.04+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~nd10.04+1_all.deb Size: 72976 SHA256: 766a04a0c3afdee01758bfb82390e4b8dda93cc48112d6326bb5b221693a1efd SHA1: 5549c54091c9eb5526b080ca8368a98573da91a3 MD5sum: a91ae7c928212a4367d8b2d60ed7e7fc 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: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 652 Depends: 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: science Filename: pool/main/b/biosig4c++/biosig-tools_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 251294 SHA256: 224775c1d9b281d05449eb4df53f299bebd8daae17bb11cd8e63c767c091ad99 SHA1: 86f8d31a5dec198226e0941f1ac860494ce4b11a MD5sum: 67568575bdd8ee369846de31064e04b4 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. TODO... Extend? ship client/server? Package: caret Version: 5.6.2~dfsg.1-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18724 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvtk5.2, 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_5.6.2~dfsg.1-1~nd10.04+1_i386.deb Size: 7293354 SHA256: 949fea3f4ac197690a36da7c3ba6c29bd535a5597414184ebebbaf6466fa61e8 SHA1: 3bf4458b8d1cfa4ce8eea9d8ade184a919d2052f MD5sum: 46af5e019d7e5a49fc33417f2a6c3a68 Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes: . - Map volumes to surface via PALS atlas - Multi-resolution morphing - Projection of foci via PALS atlas - Surface-based registration - Surface flattening . Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more imformation. Package: classads Version: 1.0.9-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 124 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libclassad0 (= 1.0.9-2~nd10.04+1), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: misc Filename: pool/main/c/classads/classads_1.0.9-2~nd10.04+1_i386.deb Size: 36044 SHA256: f759eaa01e09d47b5d330ae51b85420f4c9015d22d65402e4e7c9eae40dd4c0e SHA1: 4d575a1802e6d704b8442cc5815042d019bae3eb MD5sum: ba78b8ce13a556867a9ed9dd5460f090 Description: Condor's classad utilities A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides command line tools to manipulate, test and evaluate classads. Package: coop-computing-tools Source: cctools Version: 3.3.0~svn1179-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3404 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.21-1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Suggests: coop-computing-tools-doc Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.3.0~svn1179-2~nd10.04+1_i386.deb Size: 1276646 SHA256: 33c728e1080afeb35f400cba582384356cd53a8d8f086f87b92850409f817bab SHA1: 2a52deae82b07a557d96d0b3c9895a47769b9ac1 MD5sum: 49242ccd333bc239e2da23bdea84332b 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: 3.3.0~svn1179-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 952 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.3.0~svn1179-2~nd10.04+1_i386.deb Size: 217376 SHA256: 6d4b77fac60e366c0f5110abc191ceada1a5428b99a88a4afa1040f06603d5e5 SHA1: 0122f5dd93a81084e668416aa2dee5febe6e12f2 MD5sum: 43602c535b040cb1df176a29d7bfa27b 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: 3.3.0~svn1179-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2304 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.3.0~svn1179-2~nd10.04+1_all.deb Size: 254172 SHA256: 46ef2a3123a768dfe4fb1c72c50b42f988eab73753538b3e2fd4d6e88234a006 SHA1: 24db42c1125fd1d2f48a4d3ec1524918bcd910da MD5sum: 8529ca7122076376109e583b9a260160 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3512 Depends: python (<< 2.7), python (>= 2.6), 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~nd10.04+1_i386.deb Size: 759852 SHA256: c2752a731e141b65f84449be53523d1d6baf4cbea8cf0cdf72c25c313a26c6e9 SHA1: 6d35074108f6e17f84e2fe58794fec127542074a MD5sum: e25caa29d83594c924916bd1b696a6f0 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: 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3880 Depends: python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.3.6-6~), cython (= 0.13-1~nd10.04+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd10.04+1_i386.deb Size: 1462760 SHA256: acfc50c4c8093bc8c94f0d5bbfe5120c5499bc4bd7cc01466bb1ef693f9cf525 SHA1: dab6a7a045d5ed2830dd1a7721d6b6df9c0a321e MD5sum: 288e021b3b6a518da81bf2e5d86fa004 Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.6 Package: dh-autoreconf Version: 2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, perl, debhelper, autoconf, automake | automaken, libtool Recommends: autopoint Enhances: cdbs, debhelper Priority: optional Section: devel Filename: pool/main/d/dh-autoreconf/dh-autoreconf_2~nd10.04+1_all.deb Size: 11738 SHA256: c47050d04ce742d3c4e886daba983267582b31f5cac01cdd1081e2ecb1d1691f SHA1: 4411d982dbf0e6baf3f74f0522324e685b7b18cd MD5sum: 69a117df6db798378a5a6f6f5e071e18 Description: debhelper add-on to call autoreconf and clean up after the build dh-autoreconf provides a debhelper sequence addon named 'autoreconf' and two commands, dh_autoreconf and dh_autoreconf_clean. . The dh_autoreconf command creates a list of the files and their checksums, calls autoreconf and then creates a second list for the new files. . The dh_autoreconf_clean command compares these two lists and removes all files which have been added or changed (files may be excluded if needed). . For CDBS users, a rule is provided to call the dh-autoreconf programs at the right time. Package: dicomnifti Version: 2.28.14-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 488 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.4.0) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-2~lucid.nd1_i386.deb Size: 147288 SHA256: 32d7c06f235aadef2661127a3dadc47e9c687606395ec6cdada6e01f6dbdb4bc SHA1: 849f406f97486614edf4030d2fd21c602061a8d5 MD5sum: 441088f81f320a45382a38b4494c5d3a 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: eatmydata Source: libeatmydata Version: 26-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 28 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~nd10.04+1_i386.deb Size: 8002 SHA256: 140291df087c22958282fb37a5837ce095d5e9a66e200ffe679d47f216828165 SHA1: 1042cb57472da5b720dfbb4f59e132fe8dacb502 MD5sum: c2884d9a0655fba7273fc7faf06e7613 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~nd10.04+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~nd10.04+1_all.deb Size: 98012 SHA256: a1e677480e2dd8f4a3a24bad8e1584300ef0acf3bbd0409e583ba6bf9e6185c6 SHA1: 78cae39933f68b734a0398cfaf5946bce6eb0ffd MD5sum: 7f083d11956584ab43fe787a6bb72112 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~nd10.04+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~nd10.04+1_i386.deb Size: 1582 SHA256: c79325026f4b63d745ed3beb64fbdecbef9f73889dc803f0003be5ea327da645 SHA1: 4ea4b571e27a981f365b5b00b9da3e080d0e1f71 MD5sum: 64f0ccbb8dce21b62918860c842092c4 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: fslview Version: 3.1.8+4.1.6-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 3868 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8-b), libqwt4c2, libstdc++6 (>= 4.4.0), libvtk5.2, libvtk5.2-qt3 Recommends: fslview-doc Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_3.1.8+4.1.6-2~lucid.nd1_i386.deb Size: 1494522 SHA256: 877f065cbfd64f57c77bf8dc7ad531d771c76f512425bb51109994e909d6bed6 SHA1: 7028f20335cbfad7a00b1f60644a053eba0382d8 MD5sum: e3f52768d578b4ae2fc0da341b9dc0f9 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.6-2~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3216 Depends: qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.6-2~lucid.nd1_all.deb Size: 2378978 SHA256: e281d1abfbaced29fa7c68ed41607acf19ebbd20e5e0a77a024717153dcb658c SHA1: 2f911edd963e4a484195d720ad3fa669eab86a48 MD5sum: 221a08bcb9ac0db48525a6b7e6e4bed2 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~svn62-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libboost-filesystem1.40.0 (>= 1.40.0-1), libboost-program-options1.40.0 (>= 1.40.0-1), libboost-system1.40.0 (>= 1.40.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.1~svn62-1~nd10.04+1_i386.deb Size: 38258 SHA256: 6c8da33b7df7f3ce89687b4575fa7a878d0a77c694c5546a6e920522711a0175 SHA1: 1a7cfcb8703dd79c15cc69430bcde14763c73f3e MD5sum: b553f7dc2b57764ae7fbc101f4bdd5c7 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 128 Depends: libc6 (>= 2.3.4), 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~lucid.nd1_i386.deb Size: 28726 SHA256: 8810eebe967dc7e1ec48ba779a5478d5c582cb6f03f0fff37c486ad71863b3bd SHA1: 9c34ccec417e753168fdca17ee0def6111a22c26 MD5sum: 38692e05685cf00a190df559af49347b Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: itksnap Version: 2.1.4-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8260 Depends: libc6 (>= 2.4), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.16, libstdc++6 (>= 4.4.0), libvtk5.2 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.1.4-1~nd10.04+1_i386.deb Size: 3658824 SHA256: 89939622cdc9189f7282ae33dfb983f71ae4086cb8c311a67f86787e95f3550d SHA1: 5c73c72ffc57792b475964b997a5026501ceb9dc MD5sum: 96ab9929d9da7b2aad59a8c3589252de 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: libbiosig-dev Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1244 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd10.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 369200 SHA256: f2e04be79175b0576b3b1767980c21637f79f0b2bfbffafb17cc6457b092a639 SHA1: ba5c9236b713f3d4fd7f4060e6a63ac395e20de3 MD5sum: 3d9f1cd958759e6f72a73bd8c7acf9d5 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://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig0 Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 780 Depends: 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_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 291752 SHA256: ef5bee174f600c7b62bd09d5b18d8731ca534dd836be06b7f4910f9a3b75e24d SHA1: 987e194740962d11da9c18d0d5db893a93f68622 MD5sum: 67fe90580e46afce69beded9b0560d76 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://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig0-dbg Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 640 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd10.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 179036 SHA256: ab45af6fa5c70a5171e6ecf6b2d9cdbfc785e64d14ef2a947457b00c68a2e44c SHA1: f016deb3053b0edf2aa70fcd510e18ed0164966a MD5sum: 33203591e2c52e0285822eab909ddab3 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://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides debug symbols. Package: libclassad-dev Source: classads Version: 1.0.9-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1696 Depends: neurodebian-popularity-contest, libclassad0 (= 1.0.9-2~nd10.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libdevel Filename: pool/main/c/classads/libclassad-dev_1.0.9-2~nd10.04+1_i386.deb Size: 529376 SHA256: cc7ec0a8518474395197d13ed435895a955b6002b9ae97c1b283edb7aad500ad SHA1: cf97817c1d7ccdc290ea75d2eb0187a0fea0634b MD5sum: 2083ffb17ae9581df3edf5fac8fd6ec6 Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad0 Source: classads Version: 1.0.9-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1056 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libs Filename: pool/main/c/classads/libclassad0_1.0.9-2~nd10.04+1_i386.deb Size: 424870 SHA256: fe9b0ba8dbf9d6acbb211639a530e1fb0934db3552464008dcf793bda434e85f SHA1: a7df65714a001f375688ecffd25ffe94774eac8a MD5sum: f1f3de884fe9a666ce8eb06f8a3b91f0 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: libfreenect-demos Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 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 (>= 2:1.0.6), 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~nd10.04+1_i386.deb Size: 23042 SHA256: 673e44e874a9f9bc187f78c184c5d1a0e487fd5513f70838295dd2e9fed47382 SHA1: 698cb326e14bb7bdcd2f56def5b7d6f2f4648a1d MD5sum: 475bc7e0ca27d183791184000893b53e 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~nd10.04+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~nd10.04+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+1-2~nd10.04+1_i386.deb Size: 21206 SHA256: b36601f37059a25ad3af484256d57ea8bc2d0b57dfa683e082369699080a4a8f SHA1: 87c6030388135bc345c94bc7f38806b7845da4f1 MD5sum: 7e8e28c8446eb55e83bb13e3f98526e6 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.6), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+1-2~nd10.04+1_i386.deb Size: 24374 SHA256: 6b1025e69186ab28d7eaa0df5f653cbe885ea7581e8457f7e51e092f6f06b48a SHA1: d0ff78b22783cfe04e16cff03688c3236cfd073e MD5sum: 5b89e361ac3b7a123afa78bed1a08880 Description: library for accessing Kinect USB camera libfreenect is the core library for accessing the Microsoft Kinect USB camera. Currently, the library supports access to: - RGB and Depth Images - Motors - Accelerometer - LED Package: libgdf-dev Source: libgdf Version: 0.1.1~svn62-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd10.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1~svn62-1~nd10.04+1_i386.deb Size: 18018 SHA256: f4212a2de1ee7f7bf1af42583817d31701158a4c85394de330f86ec5f509f941 SHA1: fdafd684e253f369438bcb94a3e6412f060195e1 MD5sum: 48e7a82e87e0b4cdff06069a2a5f97ef Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.1~svn62-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 336 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.1~svn62-1~nd10.04+1_i386.deb Size: 106156 SHA256: 03198ed3fb4861f638a8aa46e55d50d6438a6807911e5a84e38007374fbc6ba7 SHA1: 62cbacd8dfbc3d6a5498da7e94411ca5c4a9496f MD5sum: 6aaf83203b73adc36d09f3df9b850b2e Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.1~svn62-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3668 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd10.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1~svn62-1~nd10.04+1_i386.deb Size: 1086728 SHA256: e337c51816d7c28f3d03f407ccda8bf3d70aab63010a77224b6933559fad50ea SHA1: 611eaef4b4996d848cc7422fdf59275fd383b98d MD5sum: 1ae9de660018dcc2fa38c14de2fdab32 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 208 Depends: libgiftiio0 (= 1.0.9-1~lucid.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~lucid.nd1_i386.deb Size: 62658 SHA256: fed86f601c429a8a28f88aaed8e6c712fc5103d3d47aba04d8571ab2bd338986 SHA1: 50d9edf5936ec2a9b007e21fd1c4364877b6632b MD5sum: 93a626fe23328146841ffa44639757c5 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 180 Depends: libc6 (>= 2.4), 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~lucid.nd1_i386.deb Size: 57436 SHA256: dfa37e83dd839851f53c608ec8d7ddeccd77a5db9cf4884bc835b4eff3cb5fd2 SHA1: 3b40a0b537ab614d66d7c4a799197ac0f93a62f9 MD5sum: 70a761d68eb1c98296554f441e4fcdd2 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libnifti-dev Source: nifticlib Version: 2.0.0-1~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 464 Depends: libnifti2 (= 2.0.0-1~lucid.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~lucid.nd1_i386.deb Size: 151538 SHA256: 88cdad9f224b4ba27f2acf08791c1a034e39ac1b2088b391a7c4df75b97ba93d SHA1: 48ab980aadb2479d14a5780d54ce95825d49c54f MD5sum: 8fa0bbffe17506bab71a628d482af628 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~lucid.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~lucid.nd1_all.deb Size: 245482 SHA256: 8532e280818991cfdd6fe8e883f0bb5b3d0ca9bb86360cd2fcb98a2750f01720 SHA1: 39744b584b030525f62bd876863ebfadcac7e9ff MD5sum: cb7b7605b2710de9700586340deca337 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 304 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~lucid.nd1_i386.deb Size: 107418 SHA256: e778b3bd3b89599aee041cff9872331bc4f800aba1a95d780c509742d173c28f SHA1: 6fc543bbc1e61ff3fb57254db869f3c628ffd0a6 MD5sum: 6f7354ee6b0164563e5a57b7878b8c0d 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~lucid.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~lucid.nd1_i386.deb Size: 4028892 SHA256: 791e7030921a9caade805ea347dfbe98d5f9b51be92e4cfd2c3b6d356c510c1c SHA1: 59f7ebcc5aa2303465e3dad6936d512140c8293f MD5sum: bb57a6d33d3b143e184774d532a429c3 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-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 276 Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-2~lucid.nd1_i386.deb Size: 43854 SHA256: 703c7e67bff1a7419240313e5b90187fbb0c9a4f5bfda653ec1fa7318be19d50 SHA1: 247e856f877b8d29b1c51803c2d5e843d8141c73 MD5sum: 2017cb50f958dc3dcb866fe796cf8c39 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-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 824 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, 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-2~lucid.nd1_i386.deb Size: 230648 SHA256: 0b7c79c917c6315b14ff518ba73746ed8b6fdafee5c00003ccf2251ccfb59130 SHA1: 05ab3ef5666f30d479b6a476c053c324d89b9f81 MD5sum: ee01b8a7bbc28e49097d91793f847003 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: libsvm-dev Source: libsvm Version: 3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd10.04+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd10.04+1_i386.deb Size: 28198 SHA256: 5edc8eacdb456593eebb4016d8d1ca22e059230957802689aa8c040030fe3934 SHA1: 0c8c8b4102539b60b729ec23f7437277789bcc13 MD5sum: f8452a57ddfa47fb273373632b024828 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~nd10.04+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~nd10.04+1_all.deb Size: 2070 SHA256: cd2a86db92cc66fbb16350a64ab624f2511dcc74206606d4f824709995a9f60c SHA1: 48795086f73056edc3a91a03dfa0a68c01d54ab6 MD5sum: 30257da2669fedaca525b0b2394ff957 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 112492 SHA256: 831ee1bb88cf2bda5d70228306fa8e35056d1ef4b9f4dbaafe16f3859725bdc0 SHA1: 3462bfaee6621eb30236390b9c062ce2fe8cf934 MD5sum: 09cb5245618baf76785495939de4df20 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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~nd10.04+1_i386.deb Size: 43082 SHA256: 422c6c1572b5d528a8309c54c70fe2ff75daeca639f9366692992aeb322d5ba5 SHA1: b97111930d3c68f075c75c27fd62ae71118e408f MD5sum: 378b6a250383093ae3c713f4f710181e 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~nd10.04+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~nd10.04+1_all.deb Size: 60476 SHA256: e764602df3fd3e56e22b684e094974116883ad0e0ba3fd85d6eb650a59ab33e9 SHA1: c4532f5c5c7defa06c81962d2bd23db9164b85de MD5sum: de7bd41053daf8de4d5bebb3578df435 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: lipsia Version: 1.6.0-4~lucid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3620 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 (>= 3:3.3.8-b), 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~lucid.nd1_i386.deb Size: 1275324 SHA256: b4ce1f08f3d5c7e535bdb95ece4f8df517b32b22cae05127790a052d46cf85f8 SHA1: 38d5698247747783e147ad72d72cda4f10de105d MD5sum: 605f02cf5b63c84f4c6221515aaecfb5 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~lucid.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~lucid.nd1_all.deb Size: 5539278 SHA256: fe6e759a40698cc35033edebd496733ddbb082eeeda66fcddb091906f0f1238e SHA1: 435a391bce4fdc0bbb017bf0214f4f42e18bec55 MD5sum: 2dddb5c30d3c0cbdfaa56523cc87dd21 Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: matlab-support-dev Source: matlab-support Version: 0.0.14~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.14~nd10.04+1_all.deb Size: 5466 SHA256: 641583c5142535133ed0135cbf83a2cf845ded44d63cf8ba5fab07a0d1c3b5ba SHA1: 613a29a7f1a2f2f91687163a92bbf722ccf3ba58 MD5sum: efba16058b109d81e623e3a5a5b1cc13 Description: helpers for packages building Matlab toolboxes Analogous to Octave a Makefile snippet is provided that configures the locations for architecture independent M-files, binary MEX-extensions, and there corresponding sources. This package can be used as a build-dependency by other packages shipping Matlab toolboxes. Package: mitools Source: odin Version: 1.8.1-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 6184 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.11), 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, libvtk5.2, 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~lucid.nd1_i386.deb Size: 2337796 SHA256: 8fcac83fd736a862ec21ca239b983681bd6bb8d1950d4adf425bbc6c394abd63 SHA1: 7c88f3430b4c2174f51d7cba6c39a8c191a85b24 MD5sum: 9ebcdc86e53f6e0a1b1b5884530dcab9 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: 2.0-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2140 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0-2~nd10.04+1_i386.deb Size: 761860 SHA256: a126d4ae16b2408cf772294355813fa7c53d39bcb85597f2d16c66c31cc8d407 SHA1: cb853034281df9e0356d9e04f3e202ad26a97645 MD5sum: 016b2fcbb0f96ad65bcb090eaf4ad5a3 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: 0.20101102.1~dfsg.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10720 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 (>= 0), 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_0.20101102.1~dfsg.1-2~nd10.04+1_i386.deb Size: 4042968 SHA256: 11ca4fd820a7de9bcf65415a9f10df5d32d5c960a457834894c1750fae653508 SHA1: 7ecb99adb0bcf78c52cb3f49288ed230d40c1350 MD5sum: 2dbad211df5ab10bcb845c8027490e01 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: 0.20101102.1~dfsg.1-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1852 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20101102.1~dfsg.1-2~nd10.04+1_all.deb Size: 1666052 SHA256: 63840c337c0f3f305ee8c92d73a22bef37241c9870608cf66b15c6fc57a743e8 SHA1: e0b610f7b6fb65ed69d01e33cc272d7c782a4211 MD5sum: b23b8ec4eabbeb5caf80313b79730ba3 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: 0.20101102.1~dfsg.1-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1220 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20101102.1~dfsg.1-2~nd10.04+1_all.deb Size: 737630 SHA256: 2ffc6eb4cb8152f4a56b2f15ba5553c326167ac72fba8586081f5f0ff1e20a89 SHA1: ccdacef76ca6fdf0bf5020e63f28bec02cbf4cce MD5sum: c63bb65dd41cac7333b7a074dcde302d 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: neurodebian-desktop Source: neurodebian Version: 0.24~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 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_0.24~nd10.04+1_all.deb Size: 113108 SHA256: 05c12694e9aa2f5616c92836d0a2e8ba9d9fee34460ec860ae48669f8ac0434a SHA1: 8e1b1f4849e3f7b28f53ff7c4abf3a9366e22353 MD5sum: 0fa5e9187a88b0220fffdeacd4f13de5 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: 0.24~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4400 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.24~nd10.04+1_all.deb Size: 3794960 SHA256: 8abc7a3c0efbcb3c25f4c314d25975dd7809642cb1a1f8bc0d69818a7428d0b5 SHA1: 6c328dbe84d26de40984a3ace502ce996c69b15a MD5sum: 829a5965246f8c39283e64e936044688 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: 0.24~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 236 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_0.24~nd10.04+1_all.deb Size: 12716 SHA256: 12a17f18cc3587ffd01f81f069e05404633137edb89b2193d050221a6436ea98 SHA1: db57d6d179b8bc64baabd055c91d9a7e2265074f MD5sum: bb25f7caab80317dabc72cf7ad57c469 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: 0.24~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.24~nd10.04+1_all.deb Size: 5792 SHA256: 7e3ceee3f206df7f6bcb38e89ef1fe5e7a2a3b235110ed7410bbce2b61ca3088 SHA1: dcb292882dfca40bb9bbe26b0928b201b65ef0e7 MD5sum: 7dadf4cf7401d18eff9ac77742c71d86 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: 0.24~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.24~nd10.04+1_all.deb Size: 4960 SHA256: c79cfa943ecd859440bb21d7b99e5d596141cb4f6590fceb0f68e34d34df4e7a SHA1: 736bc5c9fb3e60e4f30412830d54ccd069206101 MD5sum: 31a9687ee595ed93e529bc04859c0b54 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 200 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~lucid.nd1_i386.deb Size: 59304 SHA256: 409ea1817447802a46a94084b2c278ceb197a934aece3262cc6e1c99806e3863 SHA1: 6bc623df2532ebda6606e264b7da98e6a37b0733 MD5sum: be175735d76d824c0719f942f13f6946 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: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1440 Depends: libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.7), 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 (>= 5.6+20071006-3), libreadline6 (>= 6.0), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 561242 SHA256: e37c023fcd489fbe0850bdeb5855b426a21cc4e3fa73eb84719cac787bfbde8a SHA1: a74882145a8e74069108aa6efaa1fbb9335f4e58 MD5sum: 4d7ffb7cb8d4b60f66797de57ff2a263 Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.1~svn62-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 392 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.3), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.1~svn62-1~nd10.04+1_i386.deb Size: 131800 SHA256: 8bc400bee9359cb3366e728d849bd1bb55ce6cd26a33658f25af50c51ed61b12 SHA1: 72987b4c8f75e20417f896fbaf232728edd84c14 MD5sum: dbf3a4fa05ac4e455335ec0ed073bb14 Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. . HIGHLY EXPERIMENTAL -- USE AT YOUR OWN RISK. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2284 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.3), freeglut3, libasound2 (>> 1.0.22), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.5 (>= 1.5.2), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libpciaccess0 (>= 0.8.0+git20071002), libraw1394-11, libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.6), libx11-6 (>= 0), libxext6, libxml2 (>= 2.6.27), libxxf86vm1, psychtoolbox-3-common (= 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1), psychtoolbox-3-lib (= 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1) Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1_i386.deb Size: 678710 SHA256: c601117be07c57247dc65136d39c5e83deb916744407cf80fb3d7662dc2e4ea9 SHA1: 66c4873e09a6359ff7bc550b0a13b396d860da5a MD5sum: 8ff63434578d27fbad7a1e0202093343 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains bindings for Octave. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: odin Version: 1.8.1-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 4016 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.2, mitools (= 1.8.1-3~lucid.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~lucid.nd1_i386.deb Size: 1548012 SHA256: 338fa901998f8aabeddee1c42439003ef873a48a25c1e55f9178fb804af2376e SHA1: c74539a99013b8f3c7619d89c5c015e32e82011b MD5sum: f524d75bea815548a4bb311d237be542 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: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 556 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, 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-2~lucid.nd1_i386.deb Size: 152040 SHA256: adc851c42b9f6b3282eba80819b552f1dc1ab057004f99ff9869c8a3ede5288a SHA1: 2c030a165b5374f123f92406e392ed828b7e310f MD5sum: 490baf793bf7bd2be6ea1e58b657d785 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: 0.22+git9-g8633c14-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2504 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~) Recommends: python-serial (>= 2.3~) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.22+git9-g8633c14-1~nd10.04+1_all.deb Size: 711708 SHA256: 389e57e0e2b876f118a0a0b5dd097d379896c1d2daf73e87aec7b6e701915270 SHA1: c4e52ed50c4f04a5c66ae5dd95b2439e1c3e390b MD5sum: 191ce55b7d8693d795acc9a56dab7b71 Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Python-Version: 2.6 Package: psychopy Version: 1.63.04.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4480 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-scipy, libavbin0, ipython Suggests: python-iolabs Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.63.04.dfsg-1~nd10.04+1_all.deb Size: 2370876 SHA256: 733875ea4433513a66dc21aaf1550bd8b5363b63a44b720a5548cc63daa78707 SHA1: 77338ed55e2c6d9cfacafc484a2edae4f5ed5b11 MD5sum: 10c59b4e5c734978f746543124a1d948 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.6 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31372 Depends: neurodebian-popularity-contest Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1_all.deb Size: 13338554 SHA256: 3a967f5b05e1c71ca04130ce6e6339a5ee2dda2f1549586a0b159fbcaa02781d SHA1: d65ea1b0706f1b49fcb1ffbf02e14fe1bef15b52 MD5sum: 5c228598b53ea1c6b9f845463f9f7cc7 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2476 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1_i386.deb Size: 776256 SHA256: c01c460b07d8307f7348d80391c3d58e04a988f2fe92d7b896ac75e24b2b9b18 SHA1: 715e94aa4253d9aea9de2dc0a95647f21a536e6c MD5sum: e23bcf70736a14f090ef6f763130c920 Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 240 Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.1.1) Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.8+svn1934.dfsg1-1~pre2~nd10.04+1_i386.deb Size: 60986 SHA256: b2d378f86a37a6d5076baf7c7b28f1971a42aa3e7139343b164b0ee27e661841 SHA1: 2357615b8d61d05963e7bc23b46ab9d372f0117c MD5sum: 2ee70034a5d71d75d5e57d3790755656 Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: python-biosig Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 912 Depends: 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: python Filename: pool/main/b/biosig4c++/python-biosig_0.94.2+svn2552-1~pre1~nd10.04+1_i386.deb Size: 324706 SHA256: 8c4862f9df28f6df3610f2e9f094e4f055959fa77a908af61ac568cd077a7c03 SHA1: ffdc4f35ae63f9d8aaa522caa1d9149ef52c11ae MD5sum: f9984b14174659a081759e5a4dc35644 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: 1.3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1788 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.0-1~nd10.04+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_1.3.0-1~nd10.04+1_all.deb Size: 313352 SHA256: 775a8320a0aed28a7acb225165f48f7f5b0b46cc8f1f7d72d16fdc9e839cbf4d SHA1: ff24f43981502a155ddd1328d8fa6cc6870c488f MD5sum: 62b89312a2fb57f85b240dc666eae136 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: 1.3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5444 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_1.3.0-1~nd10.04+1_all.deb Size: 1688130 SHA256: 1f13ac4840384206a181a343e4bbd474b5253ea73f85059bc444cefdd9563692 SHA1: 0444f5c1b5a7f520e736c41935cf4740e960af5d MD5sum: 1a08205bd0a61edffa9c2e3c6fb3b840 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: 1.3.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.0-1~nd10.04+1_i386.deb Size: 53180 SHA256: 7f4d782df4e0ecbc94e006a466241fbd49d766a075eb408bc9316c428f7915a0 SHA1: 07df0f1a1d81efafb249ca53cbc4cca02c2d850a MD5sum: d02525121d0a51aece385261d3253439 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-dicom Source: pydicom Version: 0.9.5~rc1-1~lucid.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~lucid.nd1_all.deb Size: 372938 SHA256: f69403f36f3840a1b00833c53b9d5423ad12355073192a8245781a34954569bd SHA1: bda525b6678d316b2c50a3f9d3de8517ab999de9 MD5sum: 0c83a634b771ca0cc6de5bf844aabec6 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.5.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2204 Depends: neurodebian-popularity-contest, python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-1~nd10.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.6-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-1~nd10.04+1_all.deb Size: 1459144 SHA256: 71ede7a2041ae54687ce69c3baf61754170bd199b8cc0f22a93aad6362d81254 SHA1: af1ea2a6a4bcf1f79fb8294fd39508e8709ba109 MD5sum: db8e6eb41cd922c18ebecba281e3b801 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.6 Package: python-dipy-doc Source: dipy Version: 0.5.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3292 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.5.0-1~nd10.04+1_all.deb Size: 1950834 SHA256: b519b7814dcc308e808503ae39bbccf72a896ef70f5f466a8df862e049b980fc SHA1: 35fe0fd21b24c7b4757e1baeae09c226e68dba29 MD5sum: 46ad25359b198ee642fd02fc610b8f06 Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.5.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-1~nd10.04+1_i386.deb Size: 3430 SHA256: 783cf2658ffdb428baafbaf1fcd2a7a980f06ebec61813599ad553043a884dc2 SHA1: 4a3fc9c7fa7ae5ebb526d3698c5edcef01a0e8e5 MD5sum: f9aed76617860ab651f46c738b5a4fb6 Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreenect0.0, libusb-1.0-0 (>= 2:1.0.6) 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~nd10.04+1_i386.deb Size: 26704 SHA256: 80703b8d870449cacf590b4bbf264a26a128a69f110aa6ff7576cf2c97d02cd3 SHA1: 1ab415c8057acb0b8161f073675046a7910e9f2c MD5sum: b12496286515c7537e3e456dd70196ce 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: 0.4.6-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: 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_0.4.6-1~nd10.04+1_all.deb Size: 38680 SHA256: cc7b595677e9f715d1806fba4cf07b1871dc48815f77a74d45aa2bdd8360bbf5 SHA1: 15366b84f0a3688be5c3e2ae9fcb08a8f994eb42 MD5sum: 2403f989196c8eace8098be253a93413 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd10.04+1), python-support (>= 0.90.0) Provides: 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~nd10.04+1_i386.deb Size: 7610 SHA256: 22ae8a50250d592283719779bdf25e9d09774883ab6df4f628a95dda65f4748a SHA1: b522df6f64dbeb91a4aa0e747a30ebbe8d2e2f29 MD5sum: 762130f8ebec76d175ab3c3724501f37 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: 3.0+git8-g921253a-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1872 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 Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.0+git8-g921253a-1~nd10.04+1_all.deb Size: 450952 SHA256: f0b8ac85f8de699d0b0824c40a7275dd905b7473238d691406a9a49ec369fc2a SHA1: 4b581210dc160e498ad97c3034178d9433e334d7 MD5sum: cef3f48e247b16b24910e695d7e51b63 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~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 424 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mlpy-lib (>= 2.2.0~dfsg1-1~lucid.nd1) Suggests: python-mvpa Provides: python2.6-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy_2.2.0~dfsg1-1~lucid.nd1_all.deb Size: 55840 SHA256: baccc7f46670565245f2d9aa65acaea015872d8bb7bf398642a714a9fea52a2f SHA1: 38f57e733f49c401922c25d85a89b5044e68181b MD5sum: cd3699a47eb5ad404aa7864cf95d69ea 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: 2.6 Package: python-mlpy-doc Source: mlpy Version: 2.2.0~dfsg1-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1132 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~lucid.nd1_all.deb Size: 478768 SHA256: 57a934ed3182a9624128bea20def7710fd79b49a10356d8a04a243aeb6ca6a7c SHA1: d9e6be19ce66c9a83358c704eed4daa666588a1d MD5sum: 24528b12939bcd8156611770fc0162e7 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~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 292 Depends: libc6 (>= 2.3.6-6~), libgsl0ldbl (>= 1.9), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: 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~lucid.nd1_i386.deb Size: 61894 SHA256: 6964974dad0516bc5e5238a3cd08e905c393664f41a846bc7611351690bba9e7 SHA1: f53b38aec69597ed93c23aa1ccf0dd6fb3ac4914 MD5sum: 87184a9e1df82a989bd247c839eeebd3 Description: low-level implementations and bindings for mlpy This is an add-on package for the mlpy providing compiled core functionality. Python-Version: 2.6 Package: python-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 992 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.3, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~pre1~nd10.04+1_i386.deb Size: 277200 SHA256: b2859b263b7ba63bc86bf42363520106cb33c9a4e2805d5c7e23b9f43e32f60d SHA1: 850934dc17a7376715f0549e8df6b19c5f2c7ae9 MD5sum: c9f514b1d1a5259b6511291f70d03c8e 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~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1364 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd10.04+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~nd10.04+1_i386.deb Size: 509736 SHA256: 52b27cead00055e097fce5b4369673b9c4a0e9cff1c993adc1705243a3c3f0c0 SHA1: fa3c3f0e47252fd6e796c9e72eb4d403f23ee1ef MD5sum: 4965f55d51c098ad48abb168163d3f72 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~nd10.04+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~nd10.04+1_all.deb Size: 54816 SHA256: a55e11c01ac8a5e1ca5bc442a860a919acb05e57760750bc31aa3f20f1a381c7 SHA1: da3e4a0c0f25b2fcb30fbb885f64d8bce56f3309 MD5sum: 70814f5b07427ccc2a1bb8977894688b 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: 0.4.7-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4064 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-1~nd10.04+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: python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-1~nd10.04+1_all.deb Size: 2188402 SHA256: be0eefa24af7717fe4378b81f0a71302068d5999bf6ba7b0b81f69a11cdc5490 SHA1: fea13a869ec22820f8166f29d41832ea37917bcf MD5sum: ea52667d93e2f512a1d2fd583fa37494 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: 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40600 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_0.4.7-1~nd10.04+1_all.deb Size: 8691038 SHA256: bf6784a110ad900f386f4da5d9110bddd777aab831bebec2de124c284b6290c0 SHA1: d1b50b450c137b8c27197b448b4df33370dfe6f1 MD5sum: c8709a76d625ad4a7bc96e4910b7c266 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: 0.4.7-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.7-1~nd10.04+1_i386.deb Size: 34566 SHA256: db1e0affa6c2252fda1526b9024c98185992f1b084458f2d486e36f8e6cc9235 SHA1: a01bebedec2eeeb6a00acf15fda9cdd5a7eee12a MD5sum: c4072631c96ca34b25599f6a0dcda02a 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: 2.6 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.6.0~rc2-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4644 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa-snapshot-lib (>= 0.6.0~rc2-1~nd10.04+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-scikits-openopt, python-rpy, python-mvpa-doc Conflicts: python-mvpa Provides: 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~rc2-1~nd10.04+1_all.deb Size: 2286982 SHA256: 03208f26e7faa988c800da98ef7a5d408530a8c6b013da515bb52dd279d95780 SHA1: 7db4fa026e37569c21116ff9631386e0b507205d MD5sum: 98bb3ec7f73f975091c73c8cde8c484e 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, 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 snaphot. The latest released version is provided by the python-mvpa package. Python-Version: 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.6.0~rc2-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 164 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib Provides: 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~rc2-1~nd10.04+1_i386.deb Size: 32712 SHA256: 0163b35bc8dcfaab1b8eba297a5f782850742993f2497a454d5e18f2f0b31f3c SHA1: 6bda1c17bec0d54d3a6d6074c23006fcaf45e006 MD5sum: 1c98e912dcba6eda90fe805ce18e7004 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 snaphot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.6 Package: python-networkx Version: 1.1-2~lucid.nd1 Architecture: all Maintainer: Debian Python Modules Team Installed-Size: 2628 Depends: python (>= 2.5), 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_1.1-2~lucid.nd1_all.deb Size: 679700 SHA256: 3b794d495a6f1402468c60983b75a41ace947be4219d2708c30469d700ae4f86 SHA1: e3e60ed53545f966ce1b2bef6b05b7cbb35d65b7 MD5sum: b12742ab70af33463e848ecf7cf0d6b4 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 we mean a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network we usually mean 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-nibabel Source: nibabel Version: 1.0.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2784 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.0.0-1~nd10.04+1_all.deb Size: 1061204 SHA256: a1860b967241be2e82da0866817497c2eae53fce4b7651b73cd3b382614b85be SHA1: 1f398f07b9a9e6a33191a0c20b26d319448d3945 MD5sum: 006d54fdec6d45901107fa9446a30510 Description: Python bindings to various neuroimaging data formats This package provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.6 Package: python-nibabel-doc Source: nibabel Version: 1.0.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2724 Depends: libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.0.0-1~nd10.04+1_all.deb Size: 404032 SHA256: f44ba0faea0b3c14b57d41fa7610576d32d0e91c08935439b7359290bb7be12d SHA1: bc11bc63614912287cfeb039e1d193dae04130b5 MD5sum: de39e6259816aa6bedbc506ca02180b3 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nifti Source: pynifti Version: 0.20100607.1-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1084 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libnifti2, python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python2.6, python-numpy, libjs-jquery Provides: python2.6-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-2~nd10.04+1_i386.deb Size: 279600 SHA256: a22698e02930b4576e0aefcf5b04600af74d6b30cdf83826fdede976d8e89b14 SHA1: 0b4c5c8d5ba1b18e608282a8e38392b5ff7bb17f MD5sum: 7d9e11ba0e6bf41899c8c4d65f6e7b89 Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.6 Package: python-nipype Source: nipype Version: 0.3.3-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1752 Depends: python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits Recommends: python-nifti, ipython, python-nose, python-networkx Suggests: fsl, afni, lipsia, python-nipy Provides: python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.3-1~lucid.nd1_all.deb Size: 277548 SHA256: e4a925dc3e2675271763c1b8a4248d73a2d38b238961a111ed182bd3c5d84020 SHA1: fec3ab250c45a1d74b28bb0a37cd7908d2224faa MD5sum: 0a4bee8815bdcc05d9c60d7739b81b9e Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.3.3-1~lucid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3640 Depends: libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.3-1~lucid.nd1_all.deb Size: 840644 SHA256: 465c043ca61af61479dbdd011fd350442d20a2a8b08212bf7c8adc709756dad3 SHA1: eba0a4d1ca01aab7eb6d0aed1161df8d86c6ed2d MD5sum: a283b2cea992bd74f4c8017b7b23b62d Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.2-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 752 Depends: python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.2-1~nd10.04+1_all.deb Size: 312890 SHA256: 08bc683cc3e1dd08eeafbeabd00aca2a78a894457bc95b8d9c74a33a4c96851d SHA1: 045ae2bb6f71f0c9097094ee9c63322fd20263cb MD5sum: d434630b1977ec754c48b15baaa2cc9b Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.2-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4064 Depends: libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.2-1~nd10.04+1_all.deb Size: 2629310 SHA256: e2795895b936d7e1f4fddb76dd840a81b4ab752a09a3e3bf4fb24abbe8ee8753 SHA1: 01c630f63f90db5afe9f99488fe91325a3545ad3 MD5sum: 4d2e87cd2816fb4df284f472efff57ea 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-2~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 560 Depends: libatlas3gf-base | libatlas.so.3gf, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, 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-2~lucid.nd1_i386.deb Size: 148704 SHA256: c8a75bb8c80b5a2ded29980a7a8c0811ee9479d4269fc7f63876511a54df3833 SHA1: d66632405a838295ecd9ce0cd99fd7cfd4cb80d2 MD5sum: a6075cfdac7e0f8fd364232abec716d6 Description: Python bindings for openmeeg library OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides Python bindings for OpenMEEG library. Python-Version: 2.6 Package: python-openpyxl Source: openpyxl Version: 1.5.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.5.0-1~nd10.04+1_all.deb Size: 57462 SHA256: 71f3e2da160956202de8bffb5735f13667c91dc412d645d13f9428dc4039c33b SHA1: 346a6bfcc6c28bfab79c37645371c525a2e191c7 MD5sum: cf2c1577929e4197cc1518fdd9b42c8f Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pyepl Source: pyepl Version: 1.1.0-3~lucid.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1584 Depends: python (<< 2.7), python (>= 2.6), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~lucid.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.22), libc6 (>= 2.4), 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: python2.6-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0-3~lucid.nd1_i386.deb Size: 349202 SHA256: b3579b21da0f1c7b85c2c4ba49e63fc62c6555021415eb3b3b6729d9393c43a8 SHA1: 67a655fc650d9e241c1850a0e95f56f8a0d8e7a6 MD5sum: 18ea3054702878c7580600a21463f98e 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: 2.6 Package: python-pyepl-common Source: pyepl Version: 1.1.0-3~lucid.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~lucid.nd1_all.deb Size: 817818 SHA256: 774bf05fe607359b31db378294947bcb52fcc9389f4401c967a172845766d9b3 SHA1: b50b0ce486acdaa088a42413d55ea9b1fbe99cb2 MD5sum: 4f523a841595f99e74aad775107bfbc7 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~nd10.04+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: python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd10.04+1_all.deb Size: 972204 SHA256: c0a0710fc32967b41456e40df7770178d8442555aaa2037bab4a3f437d5da8f7 SHA1: d6b2bc7d9dc785cc5f9cef1c258ea48249921728 MD5sum: 4bf7272cae665691f702fa30fc9b9f79 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~nd10.04+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~nd10.04+1_all.deb Size: 187334 SHA256: fa49550748a1c9071f1b4fb6b82b07a2aa7a20dc89d936e9bed78984cf034313 SHA1: f2af1366a8b41a86c9681735ee312ca551a6169f MD5sum: 6329589ccb640ae0152f5dea5091cddb 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~lucid.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~lucid.nd1_all.deb Size: 6938 SHA256: 19de2c227b5d42bf669a9f17fe2b57a673389f897f5cfc38c36c5561f4a8d688 SHA1: 3a8e1f8a435a5f8c8c73e694284096d4df474f02 MD5sum: 72a4517f5c3bc2eb5154b247fc4e12c2 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: 2.6 Package: python-scikits-learn Source: scikit-learn Version: 0.7.1.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1236 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-scikits-learn-lib (>= 0.7.1.dfsg-1~nd10.04+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.7.1.dfsg-1~nd10.04+1_all.deb Size: 270396 SHA256: 1db41ac8e446906126704d2b49fa62134e2f4f0dc4b7acd4ee37fcee5b4f4dd6 SHA1: b73193bde572a3489228d95cffe4acbe7406e8be MD5sum: e348ccf034b26dfeedb2b9d094f6c1a9 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.6 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.7.1.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9064 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_0.7.1.dfsg-1~nd10.04+1_all.deb Size: 4465462 SHA256: 730584c9627675f2f7f5b1e473edaf8c3555615232fa43dbb2008a5682ccbd4f SHA1: 26e32fdafb7e013d6334de44b2155bb2062c8ae2 MD5sum: 10cb3ff7bda7a06d37c3cf8a7d5e3cc9 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: 0.7.1.dfsg-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1104 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: 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_0.7.1.dfsg-1~nd10.04+1_i386.deb Size: 394834 SHA256: 0d564d0d1c926bc614aa844bd6bbc9e324eafe8b9e4d63ed52fdd1bc58014291 SHA1: a007697d0cf5936cd34488151e39d9c7d4b19b59 MD5sum: 66a25dffb8ed6c06aa0a5ea85a9cc004 Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.6 Package: python-scikits-statsmodels Source: statsmodels Version: 0.2.0+bzr1990-1~lucid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 9624 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Provides: python2.6-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: python Filename: pool/main/s/statsmodels/python-scikits-statsmodels_0.2.0+bzr1990-1~lucid.nd1_all.deb Size: 1874514 SHA256: d2c2c1010f11027fbdece0919ff27d9b733377f5426cd44b1518aa2a9ec43e58 SHA1: cb3452ecc1bb014bdf5b694178f935c375621d5b MD5sum: 45560609f527ffd385fca31ae084523c 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 avalable for each estimation problem. Python-Version: 2.6 Package: python-scikits-statsmodels-doc Source: statsmodels Version: 0.2.0+bzr1990-1~lucid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 2184 Depends: libjs-jquery Suggests: python-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: doc Filename: pool/main/s/statsmodels/python-scikits-statsmodels-doc_0.2.0+bzr1990-1~lucid.nd1_all.deb Size: 307516 SHA256: a21a5c3f213685a246aec2728f360ae20eaf22942a867581bf339b744aa254c5 SHA1: ee3ea925e350a73677a9a588a48bf4891c989ee5 MD5sum: 6bb2b036b77d4fd62c57f4211845349e Description: documentation and examples for python-scikits-statsmodels This package contains HTML documentation and example scripts for python-scikits-statsmodels. Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd10.04+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~nd10.04+1_all.deb Size: 1260344 SHA256: ed112ff459ddd78efa87cb949cfbae5459a3412165fa8b4973e8a76ab824173f SHA1: 6511865f2ce2d04b056d4fa5f6ac05e5eb60b26f MD5sum: d083a49b7b98dab935fd7d603aa548af 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: 0.10.12-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 516 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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_0.10.12-2~nd10.04+1_i386.deb Size: 211624 SHA256: f5b65f8106c3f96eab253903817ae129bb8fa83dad5a9378bc5476a3a50d990a SHA1: 7aad98f8f0b4e60b7650e1013683278e3721dd73 MD5sum: 1ce1a8171d379a3703f2faee32b5e668 Description: A Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-sympy Source: sympy Version: 0.6.7-1.1~nd10.04+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~nd10.04+1_all.deb Size: 1696380 SHA256: 998b38bfe45696bbeced69358a5620c9dde141bdd5be2640797b384bff6ddd2f SHA1: 53543ef42b225f2b190593f7df8a5b869933069a MD5sum: 68e7f81588ef209c34224974fd3f1c63 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: sigviewer Version: 0.5.0-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1052 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, 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_0.5.0-1~nd10.04+1_i386.deb Size: 439474 SHA256: fa4e60dfcfc6509fe8f212b84065ab71e5be8f1292e55a3d847a7b8259a65a7c SHA1: b5ddbcb9104806f1b61e33265eec6666fbabaddc MD5sum: aa9bf89fd30b6f5d9e6830862587382b 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://hci.tugraz.at/schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: spm8-common Source: spm8 Version: 8.4010~dfsg.1-4~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21124 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4010~dfsg.1-4~nd10.04+1_all.deb Size: 10087676 SHA256: 8221fbe2c1f5a71ce0598577f891029d65a75ac43146cbbbaa1c1810e4db3efc SHA1: 94bc3322091015e95f92485f5e3c9d375e835cc1 MD5sum: 4ee206e418f727fa199260ad4b70d2f0 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: 8.4010~dfsg.1-4~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73316 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4010~dfsg.1-4~nd10.04+1_all.deb Size: 52168464 SHA256: f2b2ba3632ed430ce701e1ba2435ae82ddf0c576186de08d8175f821edf4d2dd SHA1: 469d89d0b42063832c3b31022b70c06e92243be2 MD5sum: f203c4fce1900a495ba4d58bc1088624 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: 8.4010~dfsg.1-4~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11288 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4010~dfsg.1-4~nd10.04+1_all.deb Size: 10423804 SHA256: 7e0d823b7a24c125b8e9d621fe5d5d5773176d0b1282797ec7f11c8f3b7be62a SHA1: 8f707e17772ae35c2b611fc50d6d483d4da65c3a MD5sum: 6d0901bfa71f718569a21df4d7ad2fe2 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: stimfit Version: 0.10.12-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1988 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libpython2.6 (>= 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_0.10.12-2~nd10.04+1_i386.deb Size: 728064 SHA256: e37255c0a929e9e653c392c892ced3edb2f6d7e49e91c2ab97846712566cfbf7 SHA1: eeaac0d2ecbb346bbab95d726ce2df7a6e7f50ae MD5sum: 6eff6936ef8424c2a6f827a9977c3035 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: 0.10.12-2~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12752 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_0.10.12-2~nd10.04+1_i386.deb Size: 4855118 SHA256: 3a52f0138455d49fea8d288551db621296e7e137951ed94e69782ec64cb17ff9 SHA1: 54675ff3aec0916ad896edc76eda49143e622831 MD5sum: 3b8d07c5f959e710ed4aecb1a8d139fb 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: voxbo Version: 1.8.5~svn1246-1~nd10.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9868 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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~nd10.04+1_i386.deb Size: 3702056 SHA256: 584b21757af4af75c4c2535f319380a36eb1fab0edb368f52a3d3b9008b13ac7 SHA1: b02308e75f4f8c7e54bbee700838eac3820191f1 MD5sum: b032b8a251a1ac33a460613832948216 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.