Package: ants Version: 1.9.2+svn680.dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38588 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.18, libstdc++6 (>= 4.4.0) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-1~nd+1_amd64.deb Size: 11489378 SHA256: 04bf6bcd6e4086fe1b677c11a1a6faacfd44aff2a25e4c164c86e589da9dbf3f SHA1: e1a3c31c88a4c486517224d74d741c0d6b7f0c8c MD5sum: d74a87fe90bcd30e081a421a362c3020 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~sid.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~sid.nd1_all.deb Size: 132466 SHA256: f27127b8c1dc917c0286a9387f8fa457376ded10b07a5908485636c27a2a14ff SHA1: 696de58c79bec6fd3efa3cf7dbbeecaa18d1ea8e MD5sum: da7a5641d17921fad83cbb534f2ebb22 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~nd+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~nd+1_all.deb Size: 72956 SHA256: 7666bac3385b0b20640e015f8a83c4b553caf47a13f951f9b4f9c81dbbb74b76 SHA1: b565f24c8d243d0f1eb9aad3b5a2398ddbfab598 MD5sum: 12baf584e618512906617ea2a38972fb 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 656 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~nd+1_amd64.deb Size: 252988 SHA256: 5f7badd9121560f7eddc72cd2ab31fbe3b3a25df204583eabd91fbe2821f3097 SHA1: 2c82c269d1137b2f3369b8a9b0cc3dcc7977f42a MD5sum: 33a8bb49e17c96ca6cd403574650d36d 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.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18284 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.5), libvtk5.6, zlib1g (>= 1:1.2.3.3.dfsg) Recommends: qt-assistant-compat Suggests: caret-data (>= 5.6.2~dfsg.1~) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.2~dfsg.1-2~nd+1_amd64.deb Size: 7233976 SHA256: 8b4dcb902507c7969e89485ca17c48575013d936eb7fe908469a971eab0855a5 SHA1: 2e3cca7944cd0fd42ee4ea4fe2b6b7193e9f4733 MD5sum: 3dcfa8b1f7908a0fb86303081e0569f0 Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes: . - Map volumes to surface via PALS atlas - Multi-resolution morphing - Projection of foci via PALS atlas - Surface-based registration - Surface flattening . Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more imformation. Package: classads Version: 1.0.10-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libclassad1 (= 1.0.10-2~nd+1), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: misc Filename: pool/main/c/classads/classads_1.0.10-2~nd+1_amd64.deb Size: 38240 SHA256: d55c81aa187e8547abb4acb015f049291cadf45a3703e7fa2f69b42cb0ef8e6b SHA1: 785667783bf33c9e16e93a6a2c478d5a4d5d5bcf MD5sum: 5fb3095f75647b7689a991cee48dec36 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2800 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfuse2 (>= 2.8.1), libglobus-common0, libglobus-gss-assist3, libglobus-gssapi-gsi4, libkrb5-3 (>= 1.6.dfsg.2), libstdc++6 (>= 4.1.1) 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~nd+1_amd64.deb Size: 1118608 SHA256: 56da574f837fb25ef604c386b0451aa2e83cd19b27acef1e3f59b77ea374a3ca SHA1: 99efcdf4be6e22dcb136523be7ec39799ddb93ad MD5sum: b8a5692da05658c974e55f6012206e70 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1064 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~nd+1_amd64.deb Size: 224230 SHA256: 9c8b8ed973cc00ff8ee36180fef4e8916b9b3981f1558f363c247a2c4e5eb5db SHA1: 09819ce720947322e2d600910b68ce126a5368c1 MD5sum: 2ff98b8f2745dd045ca6b741d4a8e6eb 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2364 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~nd+1_all.deb Size: 260782 SHA256: e9723fe38305113d46ce75598d81ac788f9c29c9204de07601ab489f5f2f062e SHA1: ae1b7ce61dcab8473538e047d6083b249b52193a MD5sum: 8ec3527332f24bb2333ba60c007f646a 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4924 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd+1_amd64.deb Size: 1331846 SHA256: 340cb1e470f0ab638c1749452199ae2f2516fac9a8152e5c5c8c15124e2fd662 SHA1: a348afb03c532dea466aab9a642a95188e3e222d MD5sum: 8dfc10b6cf44d65866b45a1880d617e1 Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10552 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3), cython (= 0.13-1~nd+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd+1_amd64.deb Size: 3422252 SHA256: 3a8617e19420cda0a3d5f6c4d52e5d4503fa1d1606355ddb7f9f8b2140fc2548 SHA1: 995dcdf86f109c46c013af8da69b15a78b6a7faf MD5sum: 6ddc22d8e8982d79f4c6d9df3fde309a Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.5, 2.6 Package: fail2ban Version: 0.8.4+svn20110323-1~nd+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~nd+1_all.deb Size: 97950 SHA256: e0e1262227ba72bda4d223e33349c278d34846b0da6c96e6671618b1f59edb61 SHA1: 50440e1dc1aa832bba1845b7d1521e1d652fe7db MD5sum: 1a0aad91cbf67c3706f4665ca04701ea 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~nd+1 Architecture: amd64 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~nd+1_amd64.deb Size: 3118 SHA256: 1f5fc1a3873aec26aa7c6f54e86d766e4ba6df7a27b255f78b88aaf06fb931bc SHA1: 408808d2ff64512435a7d9dd7d477557885e2d22 MD5sum: 7020fc22688ab664db3a67cb5bc8f1d1 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: gdf-tools Source: libgdf Version: 0.1.1~svn62-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 156 Depends: neurodebian-popularity-contest, libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-program-options1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 39390 SHA256: a945d5d557d57cfe1269d1d19203bc3fd7bc28647c0307c2f25ea3422a362a1f SHA1: 7ebbd9885d5110f9a9084892a750db626e5892c1 MD5sum: 2fc7bd2be1779ef9b4bcc303949e468d 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: itksnap Version: 2.1.4-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8652 Depends: libc6 (>= 2.2.5), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.18, libstdc++6 (>= 4.4.0), libvtk5.4 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.1.4-1~nd+1_amd64.deb Size: 3707206 SHA256: a5235e27b947aa260b096b3b82285b952f7f35e8c8d958c3a79b8c088f28a58d SHA1: 9bcc48493198a6ad51d718cedf479313fa4ee623 MD5sum: 5cd6e353618e15542bf48e3fa86b4663 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1612 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 379236 SHA256: a665a5bffeb961942abc2518740d909e8e592e1736cb1a500dac23647d8aeaa4 SHA1: bee2618edd742effb4ee6f2fdad32fb02825be18 MD5sum: 176ffc6caba0fbe1cae4cfac54b7a85d 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 888 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~nd+1_amd64.deb Size: 302784 SHA256: 57d7d418db3653ca09682b35be21af90975f48cb25afc466133815f097e85c51 SHA1: 08d26dcd7091dd7e4ab2c7e2e7d7284ebd3ec8b5 MD5sum: 13e05b4b127db507b8b723cf25c63185 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 712 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 171850 SHA256: 07de31c3e4cfd4eea206acaae5a87c2ce1f054a4368aba0656cbac646b219f78 SHA1: cab06bda102c936f43eb512bf6c84ef56edda6fb MD5sum: 1142ba816c57d618b673d1847fde8715 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: 1.0.10-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2184 Depends: neurodebian-popularity-contest, libclassad1 (= 1.0.10-2~nd+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libdevel Filename: pool/main/c/classads/libclassad-dev_1.0.10-2~nd+1_amd64.deb Size: 571012 SHA256: a60480244ed38fe5f66f97d1de7ac7181489dcf80e3caf8c9b46fadef95a2a9b SHA1: 90faa59f606e7d2b13febab610907093750a6b88 MD5sum: 917b9e223454cd1eb512206604781e69 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1072 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libs Filename: pool/main/c/classads/libclassad0_1.0.9-2~nd+1_amd64.deb Size: 428734 SHA256: 28c36fc5cb06289f9ec71a6ed8a8d3a9eb392020fe610ebb51dfc5fdecc3ae42 SHA1: 373fd0b6bc6ff856675d1d0e1f9f12dbf3ac1130 MD5sum: f5ea3e78082420a91e5e77afe83c3e8b Description: library for Condor's classads expression language A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the runtime library. Package: libclassad1 Source: classads Version: 1.0.10-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1016 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.5) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libs Filename: pool/main/c/classads/libclassad1_1.0.10-2~nd+1_amd64.deb Size: 417868 SHA256: 55303f65d045345c1835d92539df557fea78b6790f197beb5ad4447837870983 SHA1: e65da58f06a1cf67657a2cb596f9560dcf739bb0 MD5sum: 1bbecaafc56e9a6a2d051921b0361d55 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.2), libfreenect0.0, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libsm6, libstdc++6 (>= 4.4.0), libusb-1.0-0 (>= 2:1.0.8), libx11-6, libxext6, libxi6, libxmu6, libglut3 Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.0.1+20101211+1-2~nd+1_amd64.deb Size: 25960 SHA256: 250c4f8ce3b71ff5c41cdf0a8bf5bf0ca3780d465823e3c9bbe4678ef300b0e7 SHA1: cc0502c7553a189b6df504e2cac73eb0074b85bc MD5sum: 521df738efd905afbe03fade82b50649 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+1-2~nd+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+1-2~nd+1_amd64.deb Size: 25252 SHA256: fe735bd5f8bd97f1023cb14655f00669e726b2f6705ac78044f2d4c4902b0657 SHA1: 9ca3709ea680f0c42a74e52beffdf418f647e65f MD5sum: b8ffd9932f472757be074f1e5468cc3a 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8), udev Conflicts: libfreenect Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.0_0.0.1+20101211+1-2~nd+1_amd64.deb Size: 26114 SHA256: 1b6d16a09323851c1ad0b419d73eb5c20521c7fc2322ddf1d11108bbe4f82950 SHA1: 2f95c519f800684676da69c0a6f37b3d8ea11b5b MD5sum: 94ad64d425535496a0c7db743bff3a14 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1~svn62-1~nd+1_amd64.deb Size: 17996 SHA256: e2c8ff9721e861f8df6d34c393c72858eedf31b97c8279ab585928196865e5d1 SHA1: 167cfa0a8fcd09abac8a5f81f764f9090b0c14b1 MD5sum: 8e9ae48e6eaabab083d8e07f7e179025 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 364 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 104564 SHA256: ce6916f27d26dd642f4dbe27b2717e243ab0f6ec5aaf08380a21ac30764e57aa SHA1: 861440b371f73e25bbcd2c90b07b70fbd4fe55a8 MD5sum: 86d755c8aa476ad8f0fef020a9a93df3 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4156 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1~svn62-1~nd+1_amd64.deb Size: 1106310 SHA256: b7decedc2cc43c894f43b1a3a594f018ec3cdc18c230a9c0c9534767bc2c642a SHA1: 8045a6e6ab409f8b5abd148ab615a5d83226fcee MD5sum: c441acb411a6fe9a7ac8163bd22f11d0 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: libjs-jquery Version: 1.2.6-1~apsy.0 Architecture: all Recommends: javascript-common Conflicts: jquery Replaces: jquery Installed-Size: 240 Maintainer: Debian Javascript Maintainers Source: jquery Priority: optional Section: web Filename: pool/main/j/jquery/libjs-jquery_1.2.6-1~apsy.0_all.deb Size: 65238 SHA256: fa858cf809b1885439cfb0d6e8ba64021a732b2e9b8493027f5d767973268d22 SHA1: 19177bbdd00962ac018ffa081149840aa7bbc469 MD5sum: 6dc346b0c5ffacbdf0e63f00d1f18485 Description: JavaScript library for dynamic web applications jQuery is a fast, concise, JavaScript Library that simplifies how you traverse HTML documents, handle events, perform animations, and add Ajax interactions to your web pages. jQuery is designed to change the way that you write JavaScript. Package: libodin-dev Source: odin Version: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 21016 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-2~sid.nd1_amd64.deb Size: 4198702 SHA256: 7c95a47eff2385fd30f2f25a4a2eb96a311502434e9fa3359e1d8b325a018cc5 SHA1: 8421c56b808b02c555cfea79c7f9b10d3364aa27 MD5sum: ca84aa498b3cd88d7e207da7c7867927 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: libsvm-dev Source: libsvm Version: 3.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd+1_amd64.deb Size: 39858 SHA256: e60901ef45ad48ddab8e9ad01e145ec1b9376d6d851a4a75597e42690037ba2b SHA1: b3c9da08c1ea22891ae3e92fe026aa53783df252 MD5sum: f22e3b3a170b76749aac93569c5365ea 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~nd+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~nd+1_all.deb Size: 13482 SHA256: 1492b2687984b9a78136924b2b39e6e61aa7cce3db838336fee65922035b3ee0 SHA1: 13a26757ee98ac492d11734e3a474b294266c9f2 MD5sum: 98d98d2c95a2b57a1d0f0fd2ccbf5e27 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 120618 SHA256: e1d145faa6c9fa5b18db06bb0be9804232915e72b0128f10a9cbd82a5c7cac52 SHA1: 47d6d9085d066923fe71a3b03439679572b21444 MD5sum: 7d92190fb1e31c0bb11798024b5bf098 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 46474 SHA256: 0c65840f15685c1bfc5e764f04d51f8a3963b6054164f9a562c29598db84e97c SHA1: 010513765f68d322979ed1c2230cdbac05464646 MD5sum: be36569a5174603abfb6c0381dcde4c0 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~nd+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~nd+1_all.deb Size: 60478 SHA256: 801debe37d8eb71cf96cc8acb1f192c1ff8b0a237ff08c17575a3294f5f65b68 SHA1: e237f6806ac39e2fccaca7e875b4a02449cb425a MD5sum: 5f50baac283e77ea67d18c68132f91b8 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: matlab-support-dev Source: matlab-support Version: 0.0.14~nd+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~nd+1_all.deb Size: 5462 SHA256: 01b1a7e67b48680db5d1d4dcb5d05e6517524c395f0800f79aff387ae1cbcc1e SHA1: 7aa4a6e4e30e4339ba6e5c32589c646cf60bd4da MD5sum: 9893de8d0856b9df3f664cdf6a2f8b7e 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: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 7100 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.3.2), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti1 (>> 1.1.0-2), liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-2~sid.nd1_amd64.deb Size: 2438996 SHA256: 1490445744b92fd868bcdd708acc68d538591a1add3dab7d5a4c797674da7d3c SHA1: a866a3fc54472b2500da32e21a9346202f1469fc MD5sum: 3f726319ab05321791c9a27097508604 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mriconvert Version: 2.0.203-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2288 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.10.1), libwxgtk2.8-0 (>= 2.8.10.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.203-1~nd+1_amd64.deb Size: 808632 SHA256: 16e51b598ea7b30d0468720122f10083b933c7bc61e7250f5b267fd670c4b743 SHA1: 92380eac582e06cbdecb784c7cadd62ecb46b470 MD5sum: 374915bf65045ab3d7e2cd8bcd16793b Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19496 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20110413.1~dfsg.1-1~nd+1_amd64.deb Size: 6376742 SHA256: 34aa5af6bf77ca15bf0bfc7d566eaf96e3f1689c476fdab121f8a4bab0b2370c SHA1: b88c757c4eb530a430baf281d32c21e476c6add3 MD5sum: 9d191e94412d859a943185c5210f7904 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1808 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20110413.1~dfsg.1-1~nd+1_all.deb Size: 1666546 SHA256: 584a18d0aceacf730b1fa4f792a4f9fb6456b6e8b9bc96e8ca7b899c5711fdc8 SHA1: 1b1c7a0f9d562b955dc7c6a7225094bb5de72933 MD5sum: 92fe3b8a72176d0d4247156799763be0 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20110413.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1180 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20110413.1~dfsg.1-1~nd+1_all.deb Size: 738184 SHA256: 5640e7c0541b9b1725043419d2b51b57a034fe8525ef0868349fe5c50f92641f SHA1: 3f42265352fe9e32a486954e7c1a74780ae8a0a2 MD5sum: f618965068d7ec5d12d74ad5825feab0 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: 0.25~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 268 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.25~nd+1_all.deb Size: 113488 SHA256: 7260f058139ae85439bbdf074bb46e648487ea059aa9fa9bb5f15ef00333794a SHA1: c367a9d10ccaf8d6c33459d332705285a7368e4d MD5sum: 77f1e369c7a1f3dc6f300882d8a9a789 Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.25~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4408 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree, moreutils Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.25~nd+1_all.deb Size: 3845802 SHA256: bc558e95a890d08a055c6b82424f1adbac9e2db2af617d8891728d66d3cb33a5 SHA1: 0690866b099abf539e6aa52b1af8094a48d528f0 MD5sum: fe3579f07d884d9c1cb91ca4650f2986 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.25~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.25~nd+1_all.deb Size: 12812 SHA256: b016296a1a6ca1048a9491a9674a730eee52bc1338ebe45515f16b225292b4b6 SHA1: bad5146819cfe3e39a028b6c166c811fd234a1c2 MD5sum: 335555754c2d181228dcc30a640e4e0e Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.25~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.25~nd+1_all.deb Size: 5860 SHA256: c2dbdc58e0e8aabd2cf5a7b52a7cffd3486af67258957a9460fa96988e42674f SHA1: 1d87a1b03ab2c6b5473be18632d0b40455db4e30 MD5sum: 5ad52cb1aead24865c5da8de020c7dd9 Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.25~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.25~nd+1_all.deb Size: 5016 SHA256: c0487e1ef4c8eca912573975adc2f119ac0becdec47b3fc501d1e80ce9bb55fe SHA1: 76be7f7965e409a28ceb31180e725fcc8587fa1e MD5sum: 74b6ea510b9f71f27ca2cec77617aed8 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nipy-suite Version: 0.1.0-2 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1612 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 (>= 5.7+20100313), 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~nd+1_amd64.deb Size: 591786 SHA256: a08849d3235b48df56398e08469139cb2d3918f2b3644375f962b017cd09de85 SHA1: 25e750cd72227396e0cdde8689986b67b9c07051 MD5sum: 2b5a943b2af6af706742a56f42be29aa 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 388 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 131350 SHA256: b6927eb0e62417f1b3e0714729097a1af5ab06361932d544d3b85c048ca51829 SHA1: 69236a02b95f535fadbea582d3744e01c31a49f2 MD5sum: a9ee83cd2798006cad0a1335812502a4 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2544 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), freeglut3, libasound2 (>> 1.0.18), libc6 (>= 2.7), libdc1394-22, libfreenect0.0, libgl1-mesa-glx | libgl1, libglew1.5 (>= 1.5.4), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), libpciaccess0 (>= 0.8.0+git20071002), libraw1394-11, libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.8), libx11-6, libxext6, libxml2 (>= 2.6.27), libxxf86vm1, psychtoolbox-3-common (= 3.0.8+svn1934.dfsg1-1~pre2~nd+1), psychtoolbox-3-lib (= 3.0.8+svn1934.dfsg1-1~pre2~nd+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~nd+1_amd64.deb Size: 748044 SHA256: b264811dfbb05647fce37c9f6af653a7398a0076a0447d0002ce898cde277e06 SHA1: 612bc8dc7c15f386ab81f92ff8645e81b66b41b9 MD5sum: 37f53d8dbef89fb018807d099f28e515 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: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4124 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.4, mitools (= 1.8.1-2~sid.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_1.8.1-2~sid.nd1_amd64.deb Size: 1571906 SHA256: 4a0dc4cef73caf8d308df2f65815560bd1a922c3878915f65cd634893dc648ee SHA1: 56adeb26583834f6034cf12e028ea58d4f491796 MD5sum: dbee20ccd8b613879ac610cc048e7a9d Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~sid.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~sid.nd1_all.deb Size: 34360 SHA256: 15e2e7aefc8b1af85c120f648897950db56fb71fe5999c5a3ca51b1c70bc0fb4 SHA1: 84e8c88b4d56f44c987808ba5c54b1799a0403ee MD5sum: 0eaf72ffeedd568782315315e95b4dfe Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: opensesame Version: 0.23+git1-g0212357-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5104 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-tk Recommends: python-serial (>= 2.3~) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.23+git1-g0212357-1~nd+1_all.deb Size: 3336634 SHA256: 02a4b3f73e1dadb9b384011b6881f2bff5159c4a00b76f355f30fc94939a74cc SHA1: 443cf9de4918c17239cb823734686284d42fbbb8 MD5sum: ac2c54af98f27d1e5a811524c2690745 Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Python-Version: 2.6 Package: psychopy Version: 1.64.00.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4748 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-scipy, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.64.00.dfsg-1~nd+1_all.deb Size: 2611644 SHA256: 76958c141b97a603c8f1d14d7d68beaa91a69ae880bc8fb3a9051fc26e203595 SHA1: efb71fb3236b077211d3aab208856f290f44ade9 MD5sum: e507b97843b27a33cacdecf6ad22c872 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.6, 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.8+svn1934.dfsg1-1~pre2~nd+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~nd+1_all.deb Size: 13337568 SHA256: 60ad757975d7613da79ea748e0777ce4800bc0ff516b63ea17af35aa8b07e396 SHA1: 63f027a8a51bb3bb90fcf271c34112b5fc023590 MD5sum: 58e24bca8fa991fc634eb6df9a6eca9e 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2648 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.8+svn1934.dfsg1-1~pre2~nd+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~nd+1_amd64.deb Size: 775764 SHA256: 35f3854829bb809376b545f7a8d8a973defe1c165b241bc4f1720b5d6989dfe4 SHA1: 99177beee7848b0b346f3f90857c743b0a707e1f MD5sum: b4c7341553875f6b0034af3cd5827d15 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 272 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 61628 SHA256: b2fe678362b11d0593238bd899df247c886f7d3ed45ac0845ccf570b405d63a6 SHA1: 1c893b28ec95d732167f3fcaaf9d46540cc1fb0a MD5sum: 775494d0cd6c66fe4570022544489b51 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1036 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~nd+1_amd64.deb Size: 336484 SHA256: d16e46d429d49a85ea7d657a4800b9288e837bec4028cee3f89be63f3a0f838a SHA1: e4fdb1c6369ea5d55952069bd441fcf685549b96 MD5sum: 533e6d46ba4d62668ff1a35da7236396 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.3.0-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1692 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.3.0-2~nd+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.3.0-2~nd+1_all.deb Size: 314058 SHA256: ad683843b4d3807e13d15bb9df28e3297fff8a4763f1d6e6e01cd4022990c8d5 SHA1: 107dff141ba27e8fb1b8dc94530553034e8dd928 MD5sum: 45397f0c1b02af6ab00ab67a1b356429 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.3.0-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5320 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.3.0-2~nd+1_all.deb Size: 1652826 SHA256: 8f2309fd5d4b4195463550730774a4938f6cc0be6972db705d924ecc8ab173e3 SHA1: 47e1bf8e5048edd45d9825f538930c3bc675c6cc MD5sum: ad406678e9c972bdd7eb41720d6d334f Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.3.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 168 Depends: neurodebian-popularity-contest, python (<< 2.7), python (>= 2.6), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.3.0-2~nd+1_amd64.deb Size: 59004 SHA256: 16906383b781d87eddac85e6cb8c26b9e9e6b703dfbd02b80cdd27106b3b5513 SHA1: 4bfd6100dbd9a04eeebc2f31e68e282fea7006ca MD5sum: c0aca0db38dda2d040c7726a77f4a863 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~sid.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~sid.nd1_all.deb Size: 372936 SHA256: e3abd85463e1a311df3588f4ac4b582da1e712e6d0b14cf6a5f87a5d92247862 SHA1: af591e04e34defa29892d5c1398a11de56d08191 MD5sum: 5546527ef55fde4ae81bc8bd50cb1ee0 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2204 Depends: neurodebian-popularity-contest, python-numpy, python-scipy, python-dipy-lib (>= 0.5.0-1~nd+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.5-dipy, python2.6-dipy Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.5.0-1~nd+1_all.deb Size: 1459142 SHA256: 5abc834f1372f48392abb299023e23888cc448fbc72e846127c1a5fa5e02d72b SHA1: dc5758d3d23ccd4a9b5662d3c290636a0fa7f6df MD5sum: f26be33db49377e14819439f4c7493f5 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.5, 2.6 Package: python-dipy-doc Source: dipy Version: 0.5.0-1~nd+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~nd+1_all.deb Size: 1950786 SHA256: 3c65fe6de290adf5f5fbef7d5b0569a075a88b57a78e2630b5a7a03a3d1748c0 SHA1: 156407c8ab8bd6f22b6d12eb3ab607584640f232 MD5sum: 8fe95ae81007890f7ad9d1cd1ccc6057 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1248 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5) Provides: python2.5-dipy-lib, python2.6-dipy-lib Homepage: http://nipy.org/dipy Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.5.0-1~nd+1_amd64.deb Size: 441672 SHA256: 506d528574ce04efbcb0b15c4d3efa22f5beaf99fb1a720149fffbea3b7251db SHA1: 2204ebf4a3725d3ee2edd5c06e2cf919522fb5f2 MD5sum: 88c078e1d6ff197fd1064276f3d5169b Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.5, 2.6 Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 160 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfreenect0.0, libusb-1.0-0 (>= 2:1.0.8) Suggests: python-numpy, python-matplotlib, python-opencv Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.0.1+20101211+1-2~nd+1_amd64.deb Size: 33938 SHA256: a89663c5f8200b3c256a445c153c7b7b108ca48b8ecb6e6e7dbe6889b48deb36 SHA1: 1a96e428065b18318b14c5a9239862749011bd05 MD5sum: deef019eb34607b93c2a52f1bef02218 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-griddata Source: griddata Version: 0.1.2-1~sid.apsy1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 264 Depends: libc6 (>= 2.7-1), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext Recommends: python-matplotlib Provides: python2.4-griddata, python2.5-griddata Homepage: http://code.google.com/p/griddata-python/ Priority: optional Section: python Filename: pool/main/g/griddata/python-griddata_0.1.2-1~sid.apsy1_amd64.deb Size: 72084 SHA256: 17869327b4ac23591a2f5c0c64b6b5e3d774204b64e55c5c328d620b1792dbef SHA1: 53e5eb8db403feb625fa80c5ad05de6ecc49bc4b MD5sum: f165543d0b0f631f3243e5f9969a8f11 Description: Python function to interpolate irregularly spaced data to a grid This module provides a single function, 'griddata', that fits a surface to nonuniformly spaced data points. It behaves basically like its equivalent in Matlab. Python-Version: 2.4, 2.5 Package: python-joblib Source: joblib Version: 0.5.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.5.1-1~nd+1_all.deb Size: 44180 SHA256: cb18a858c1b58f80b3cbb44a73f2dff4a6094a9ca6e2a7fb94b66726ede6b657 SHA1: 3175b95992189a2e6cde06324792fd6f91dbdc6a MD5sum: 9e39534ae68535fa778819f7f57d0709 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1), python, python-support (>= 0.90.0) Provides: python2.5-libsvm, python2.6-libsvm Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: python Filename: pool/main/libs/libsvm/python-libsvm_3.0-1~nd+1_amd64.deb Size: 14310 SHA256: fd999ffd87492f02d03cc112367d112f9a9f40f29b7281a27fb1e6d82184e706 SHA1: 85c8da86fcc992c1e7f2c347b2c26562024e4e1b MD5sum: fbe7317e20d2a6f8cf761596d683732f Description: Python interface for support vector machine library Python interface for the LIBSVM library using ctypes. This new python interface is provided since 2.91, and it is incompatible with the old one. Package: python-mdp Source: mdp Version: 3.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1812 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-scikits-learn, python-joblib Suggests: python-pp, python-py Enhances: python-mvpa Conflicts: python-libsvm (<< 3.0) Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.1-1~nd+1_all.deb Size: 455290 SHA256: 1aac8db7da9ce94b8ffecd49549348175fb67817f830664aef07bf05e2981dff SHA1: 6988574ece6fa57f6073c679001bae50c7be6c95 MD5sum: 652d4fec97f6e950df87cc02c9af1899 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-mpi4py Source: mpi4py Version: 1.2.2-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2204 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libopenmpi1.3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0) Recommends: openmpi-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.2.2-1~pre1~nd+1_amd64.deb Size: 742744 SHA256: 7563abf0c134a9b534bbb4cc23702e54ac1db958b66c1a9bf474d77bdde5f936 SHA1: e5b403da34d2f8e52f040adc707cd799fccb48a7 MD5sum: dba0f7012c6e5d378c2b6e912be9f83b 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5828 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.2.2-1~pre1~nd+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~nd+1_amd64.deb Size: 1398448 SHA256: 7a72d2fd353af19e42b79a82fb7e591f6ea4b8ebeeca2900dd3aa3e9667d48b2 SHA1: 1fc2c5830eeec41c5cbce3b74cb36316e05375f8 MD5sum: eb39108fc8204c441e1b73e8251fad20 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~nd+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~nd+1_all.deb Size: 54800 SHA256: 460ff10609587804fee11ca68c72611942677a0c4a52db6535f3dfbdc3880bb2 SHA1: 1f36ea0d57e0b6739f8e4402dab389ca6d8ca6f2 MD5sum: 0cce2dc50f0aadac8e7e3a2b8419a4da Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-mvpa Source: pymvpa Version: 0.4.7-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4076 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.7-2~nd+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.7-2~nd+1_all.deb Size: 2196832 SHA256: a379f925bfa7389d343f0600c32fb23202cf872f8834c183650d6cffeba5c413 SHA1: 578ffee5e361d0d8a1d12114b24feb61196fe08f MD5sum: 527bde7c26408cf02a004d51fa97c20a Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.7-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41220 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.7-2~nd+1_all.deb Size: 8775790 SHA256: c130b467c72ae91fc269802a637854d858dc8d15911af50c894650031d4b2924 SHA1: 45e56bc5af81e6f6b52581a0d12841ed44b42aa0 MD5sum: 9dae676ab99d39c1afc97a4aa5b1ac1e Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.7-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.7-2~nd+1_amd64.deb Size: 72858 SHA256: 74957a263a5a8df54995588af62f56ca249a8301ec090c43252fb3c77d71069b SHA1: 0c94d593782172c8d9d23d96022abf91d3867a8b MD5sum: 9d3ea1294f97eab5657f95d51312c9f2 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.6.0~rc3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4584 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa-snapshot-lib (>= 0.6.0~rc3-1~nd+1) Recommends: python-nibabel, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy2, python-mvpa-doc, python-scikits-learn Conflicts: python-mvpa Provides: python2.5-mvpa-snapshot, python2.6-mvpa-snapshot Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot_0.6.0~rc3-1~nd+1_all.deb Size: 2312826 SHA256: 590d2c50f53934ab81053b5060416fba3445076807d7581236240881c681dd4a SHA1: b41dcb0aecbbc6026544ed36de2413c742650828 MD5sum: 22d01dc3442ca7478071b786ee695661 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 snapshot. The latest released version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.6.0~rc3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 220 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib Provides: python2.5-mvpa-snapshot-lib, python2.6-mvpa-snapshot-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot-lib_0.6.0~rc3-1~nd+1_amd64.deb Size: 72670 SHA256: aa0773195f6208ff16b7bba82c0ddb9576c8d2550918c8290982bd6aec2fe8a1 SHA1: e0b8285d460e2539dbc998c6a690bf558da6e3ea MD5sum: 136ec00baad2d2b75d275342437c0587 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-nibabel Source: nibabel Version: 1.0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2724 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel, python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.0.2-1~nd+1_all.deb Size: 1070424 SHA256: 4d39fc47d07c6b1fdd514796a719e5d42f97852b9fccc3b92834866a1612e3ac SHA1: 950ae5e6c872e3236057da654d0e7160aaa6b570 MD5sum: 378d742db4add5808a398d94447e3c81 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.6, 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2704 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.0.2-1~nd+1_all.deb Size: 393458 SHA256: 94e50f7340474cc22cd9a020819cf435827bfde75f7f3a4351069671e38df432 SHA1: 9df1f039281279d4eddf504dbe924ba6c935ba95 MD5sum: bc5cf711010e637920519e4ff2ab1d76 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~sid.nd1_all.deb Size: 469776 SHA256: 674d6faa8c47cc5d2abded6bf10d56d3c7b2041b70390b254d6bed4fe0b89f92 SHA1: 1e06be036a09d6114c43bcccf080aa256f7c7a69 MD5sum: 26e58a8ca88e85dfba68eae891bdcdeb Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nipy Source: nipy Version: 0.1.2+20110404-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3380 Depends: neurodebian-popularity-contest, python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-scipy, python-nibabel, python-nipy-lib (>= 0.1.2+20110404-1~nd+1) Recommends: python-matplotlib, mayavi2 Suggests: python-mvpa Provides: python2.5-nipy, python2.6-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.2+20110404-1~nd+1_all.deb Size: 692218 SHA256: 189f610fe7952124e3a716091507789f635b991c03048579a4f60f376b8cf760 SHA1: 664f69f59f0f26e4b3948b6d6f86d0ba9646989e MD5sum: 7767920a41293e45f1ccc3e5f9efd1ed Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). Python-Version: 2.5, 2.6 Package: python-nipy-doc Source: nipy Version: 0.1.2+20110404-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9460 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.1.2+20110404-1~nd+1_all.deb Size: 2536298 SHA256: 7fe9e57248e121e8ce14b945f9f9e0c13fafb1066fa1422fcc761f36408099fc SHA1: 81b0954e2f3506eee391e891c3c9d2614092cb5d MD5sum: e1c639b39046ab3dfc32ccd5ec92649d Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.1.2+20110404-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3112 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Provides: python2.5-nipy-lib, python2.6-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.1.2+20110404-1~nd+1_amd64.deb Size: 1239304 SHA256: b12746c685d60fd3a28d7b4b8209fe48558bcb6f757d554a560f1eba7476bc8a SHA1: 02dc904b4627516a6afd279b523604cbc4dc86fc MD5sum: 1460673aaff6e622b5daf47d0d65cd20 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). . This package provides architecture-dependent builds of the libraries. Python-Version: 2.5, 2.6 Package: python-nipy-lib-dbg Source: nipy Version: 0.1.2+20110404-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3356 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), liblapack3gf | liblapack.so.3gf | libatlas3gf-base, python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-nipy-lib (= 0.1.2+20110404-1~nd+1) Provides: python2.5-nipy-lib-dbg, python2.6-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.1.2+20110404-1~nd+1_amd64.deb Size: 1369494 SHA256: 8ed01eb5970cbf982ec5f6d4733f71b38d649cfb24ac079de330162346e6f211 SHA1: 31371933eb329999ca7b2272fb49f7a26368b6ef MD5sum: 38e3320cf2383dfb6b106b86b44cd1ad Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI). . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.5, 2.6 Package: python-nipype Source: nipype Version: 0.3.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1820 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits, python-nibabel, python-networkx Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat Provides: python2.5-nipype, python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.4-1~nd+1_all.deb Size: 318222 SHA256: a39204803e6eb16517fba5e03c868f8423ffac2de520c66d66347c31a447f69d SHA1: 9d751cbd3dcdbe54a527fcff73297707ecb33003 MD5sum: 941841a81590be4c82f05e784f40bb6e Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.3.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3944 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.4-1~nd+1_all.deb Size: 883976 SHA256: a845e40404edb63af6258b524da92416d40ba4edbf567dba07b2ac475daf8ab2 SHA1: 1b5f6328b546e11f492aaf6a913a5553f7c0140e MD5sum: 1840e98a1809a4f528d742e58dd9292e 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~nd+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~nd+1_all.deb Size: 312880 SHA256: fff965f4b8993e9afa6c2d83a2b3c6c0f56bcb14fb4b48b07703b0585bf5c660 SHA1: 526e3c73cf4a538774961aa82beb07919e7a079e MD5sum: f4bac61309b120a633cbcaa82004c050 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4056 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~nd+1_all.deb Size: 2631540 SHA256: 174f9035e1239f9831f477855dc231deb64ad0e9409dc6732456213b46eb8ca3 SHA1: bb9668391763b17e6885f33f52f8ee9e23ce03a4 MD5sum: 820475354de9de093251285e46f4f0d4 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-openpyxl Source: openpyxl Version: 1.5.0-1~nd+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~nd+1_all.deb Size: 57448 SHA256: f5fdb9d794865fb84ade4d634ef57c24479210b1999f2023d8c914883f6eb096 SHA1: df9eeeaa1a9885b353d04f22fbffe752da414449 MD5sum: c81a9152dfd5e4241d08dea92c7d1098 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-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4356 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.5-pyglet, python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd+1_all.deb Size: 972190 SHA256: d192998b5a0ad23a8014afd611a21ad4300c71dbd5d14b3f64e3f0fd669b6210 SHA1: 5e072bcd364c59d478f4006386eb7487a8ba4dbd MD5sum: 920b7e086aa6042bef058e20b3c5b057 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~nd+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~nd+1_all.deb Size: 187286 SHA256: f05cfb775f0d8307d3e861dc2d61ab202f10605606a0c0c5c9d38ae670e55566 SHA1: b953d289b3c182e130169fb1f63a994d8019797e MD5sum: 9edb8e594953950fe21834adad1ecbca 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~sid.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~sid.nd1_all.deb Size: 6946 SHA256: 61b96afae4d2c43351ad598253b8b38fff6b0c2d99669f49f431b8d8678f89be SHA1: 8442b14c93a7d2c3718d78655dc85fef951bcfaf MD5sum: 1eaea3d3d51bcd440299d8aa65220111 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~sid.nd1_all.deb Size: 119482 SHA256: 047337422d8c671d1ca38e938384c985fc1fac566d178123b6cb5ee4d1fccc51 SHA1: 2fb56ca17ad07ee58955caf8de17a4cd24d3d85a MD5sum: 1790628c9012a2ae40aff02998bd9c41 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-scikits-learn Source: scikit-learn Version: 0.7.1.dfsg-3~nd+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-3~nd+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.5-scikits-learn, python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.7.1.dfsg-3~nd+1_all.deb Size: 270790 SHA256: 14a6f5ed5bcf79eb237c4b7fef0ea60e4c73e6a33847df1f947e69b30b7e0516 SHA1: 4d36f6ba421b81fb520deb6a0992c7a620a0abf5 MD5sum: 47b04e0afcf05c16d74b6db4d2647f4a Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.5, 2.6 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.7.1.dfsg-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9052 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-3~nd+1_all.deb Size: 4462062 SHA256: 7fd03278923807c84a57bbf785f99b530fc648bc4517c543035fe5cbb9711c8d SHA1: d9a1970edb2c79cd9d7a9d7326923efb5d94365d MD5sum: e84377bffb1c7ce3206a7dd17ebdd8b1 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-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2432 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Provides: python2.5-scikits-learn-lib, python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.7.1.dfsg-3~nd+1_amd64.deb Size: 930882 SHA256: 4a45a518102e1348861a1d098a8e72a4006f9117c1be32b9e6c377f3b67f2d07 SHA1: 6de9d709b9a19ffaaf6af8c9c21288332c27d391 MD5sum: 026d05af9a7391e00b4cfa269ae5d801 Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-scikits-statsmodels Source: statsmodels Version: 0.2.0+bzr1990-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 9644 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Provides: python2.5-scikits-statsmodels, 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~sid.nd1_all.deb Size: 1874480 SHA256: 1d5be1691f554290e8c195284ef8fbdffd1ef948df40cb4e42f23ed1ea454724 SHA1: 95f607c3b8e4ec04a0a3530abcc4d0f381decba7 MD5sum: 775433657571640365080d6f54bba54c 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: 2.5, 2.6 Package: python-scikits-statsmodels-doc Source: statsmodels Version: 0.2.0+bzr1990-1~sid.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~sid.nd1_all.deb Size: 307526 SHA256: e87b964cce23b84e481622b0dd5b20db420f9da592f62f56b48372e1f162a76b SHA1: a5b070d9b9ea9046491c3efc92582ae85ccd7c95 MD5sum: f52b8e834c2a71aaf9541efd3bd7326b 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~nd+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~nd+1_all.deb Size: 1260238 SHA256: 6b0bdebb3903a4eb0a75440f121dde7c531d0b7b060d33223f1185d9e0a27ce9 SHA1: 555f959d260ce486fb4395838b0918eaf71fab5e MD5sum: c52dab199b31675ed95d4298586b8ed2 Description: tool for producing documentation for Python projects Sphinx is a tool for producing documentation for Python projects, using reStructuredText as markup language. . Sphinx features: * HTML, CHM, LaTeX output, * Cross-referencing source code, * Automatic indices, * Code highlighting, using Pygments, * Extensibility. Existing extensions: - automatic testing of code snippets, - including doctrings from Python modules. Package: python-stfio Source: stimfit Version: 0.10.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 504 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python-numpy Recommends: python-matplotlib, python-scipy Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.10.13-1~nd+1_amd64.deb Size: 224750 SHA256: 3d35af5cd08128883681086617c6c3de12081a580d66abb24e7b069d8b4d1500 SHA1: ac2c571100c5ec5473e7d381bb939b170360bb76 MD5sum: a6854f8b08d91300ebdf6d1290c03935 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~nd+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~nd+1_all.deb Size: 1696300 SHA256: 65cc1db7a2ef35ab86aef147e04c6b2d8b7c2ca10e689a3e9767e3bce6291484 SHA1: b6182a46ed673beb7b3568356ac27cb73ca33585 MD5sum: 16047fa2cf0d90581ff5df51e1de35b1 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: r-noncran-psychofun Version: 0.5.0-1~sid.apsy0 Architecture: all Depends: r-base-core (>= 2.4.0) Installed-Size: 600 Maintainer: Experimental Psychology Maintainers Source: psychofun Priority: optional Section: math Filename: pool/main/p/psychofun/r-noncran-psychofun_0.5.0-1~sid.apsy0_all.deb Size: 70968 MD5sum: ad3d95b1a239fa17cae77a362e9f8639 Description: Bayesian Inference for Psychometric Functions The package provides routines for inference about the parameters of psychometric functions. It provides routines for maximum a posteriori estimation and Markov chain Monte Carlo sampling from the posterior over model parameters. . This package is in many ways the successor of the psignifit package. Package: sigviewer Version: 0.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1112 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.2.5), 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~nd+1_amd64.deb Size: 450788 SHA256: f7a5b1fb7f165cd432d62b846907278ae9441992c1014263e8f2d060532d41a9 SHA1: 22ebc3e380cd0975f5eb4f834ceca0ffcc56d0b6 MD5sum: 939c3d1d1c495df4b9065608095de6f3 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: 8.4290~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22192 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4290~dfsg.1-1~nd+1_all.deb Size: 10547186 SHA256: 8259c16103a8d5a4633fa4f1f009de963c46cf29ad56d031308c574aef12a5cf SHA1: db0c109459249d4e2dbe2714d518d4367d401c74 MD5sum: e1dd481790e9c155b33923f772707a1f Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4290~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73084 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4290~dfsg.1-1~nd+1_all.deb Size: 52167546 SHA256: 34f179cb6c5f07e2cca308b199821f44fbc0216dcc2b096af4c9e6225fa5b574 SHA1: cf3a4188d88d54dee74aa1d469cb50f8024cf20e MD5sum: cda8296526ed5bc2efb5e7b7da46bcb5 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4290~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9380 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4290~dfsg.1-1~nd+1_all.deb Size: 8648780 SHA256: 747ac1dcf327bcd7b3086d000b182eb5f4fc60b30269edf88c68651c6e7e5e82 SHA1: 87be5ffde06e2e3e08a2b9d4fac565784e3a2343 MD5sum: b9f8f78ad274703d783a63ee06c9f929 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: stimfit Version: 0.10.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2168 Depends: neurodebian-popularity-contest, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.2.5), 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_0.10.13-1~nd+1_amd64.deb Size: 774336 SHA256: 11e33688cde1417366a5305de1b07eee21dd9474ad251e26b4f62ad4cb85c6a5 SHA1: db843829b750e9bcb9ec20fbf7e5c668f41c639b MD5sum: 1bbe08a298f32be57a35a0704f54f802 Description: A program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.10.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27084 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.10.13-1~nd+1_amd64.deb Size: 6355014 SHA256: 72c69857ff4de30efa3da575be4220a2d02a88604e67821391ff2baf9145b4b5 SHA1: 613407cfb5b91d500d0ff581d02dcb598ef03850 MD5sum: 02b5c8db53ee75b3869756b17bd8565d 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~svn1241-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10100 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), 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~svn1241-1~nd+1_amd64.deb Size: 3697908 SHA256: a735afd3c8f426cd89fb51297cea9bda046d678c0af61dee46504217920561b7 SHA1: 9d8efb5cdcccd907e9bbd45590a188bf70556f03 MD5sum: 288ff5ad6ddc9be4f4e248a18b49821a 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.