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-data Version: 5.6~dfsg.1-1 Architecture: all Maintainer: Michael Hanke Installed-Size: 236780 Homepage: http://brainmap.wustl.edu/caret Priority: optional Section: science Filename: pool/main/c/caret-data/caret-data_5.6~dfsg.1-1_all.deb Size: 175205418 MD5sum: e5f41497554088124975dfc27ba6378b Description: common data files for Caret This package provides online help, tutorials and atlas datasets for Caret. Package: classads Version: 1.0.9-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libclassad0 (= 1.0.9-2~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_1.0.9-2~nd+1_amd64.deb Size: 36538 SHA256: 5b5b77fe40453b70a96baf35ac0148b02c68e19bb2790b0a8b5eed2b4f275d95 SHA1: dbc637018753ab177b7770dd182eabfc8773ef7f MD5sum: 1e3abd90ef58392a32feef94f8f2bbd9 Description: Condor's classad utilities A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides command line tools to manipulate, test and evaluate classads. Package: condor Version: 7.5.4+git567-gb10f6b4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11984 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.4), libclassad0, libcomerr2 (>= 1.01), libexpat1 (>= 1.95.8), libgcc1 (>= 1:4.1.1), libglobus-callout0, libglobus-common0, libglobus-ftp-client2, libglobus-ftp-control1, libglobus-gass-transfer2, libglobus-gram-client3, libglobus-gram-protocol3, libglobus-gsi-callback0, libglobus-gsi-cert-utils0, libglobus-gsi-credential1, libglobus-gsi-openssl-error0, libglobus-gsi-proxy-core0, libglobus-gsi-proxy-ssl1, libglobus-gsi-sysconfig1, libglobus-gss-assist3, libglobus-gssapi-error2, libglobus-gssapi-gsi4, libglobus-io3, libglobus-openssl-module0, libglobus-rsl2, libglobus-xio0, libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.7dfsg), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libltdl7 (>= 2.2.6b), libpcre3 (>= 7.7), libpq5 (>= 8.4~), libssl0.9.8 (>= 0.9.8m-1), libstdc++6 (>= 4.4.0), libvirt0 (>= 0.5.0), libxml2 (>= 2.6.27), zlib1g (>= 1:1.1.4), adduser Priority: extra Section: science Filename: pool/main/c/condor/condor_7.5.4+git567-gb10f6b4-2~nd+1_amd64.deb Size: 4399054 SHA256: a5ff0d0952636577e3370e446233e213b5d6b1f084b9198774e11dfe713f2476 SHA1: b250eea695c8e2e835dc72c39f3709a659d78461 MD5sum: 42d8c85a6f204e56f5e5f1ae511d99bf Description: workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . The Debian package uses Debconf to determine an appropriate initial configuration for a machine that shall join an existing Condor pool, and moreover, allows creating a "Personal" (single machine) Condor pool automatically. Package: condor-dbg Source: condor Version: 7.5.4+git567-gb10f6b4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 35156 Depends: neurodebian-popularity-contest, condor (= 7.5.4+git567-gb10f6b4-2~nd+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.5.4+git567-gb10f6b4-2~nd+1_amd64.deb Size: 12338022 SHA256: 840182f233e9db356086819c6207dde1c3eeffebbde8680ea256636c84b52695 SHA1: 5054798fa037a3e8e367d999db99cccb58422920 MD5sum: 1b73179b3c314fcbf76e253d9d18c16b Description: debugging symbols for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This packages provides the debugging symbols for Condor. Package: condor-doc Source: condor Version: 7.5.4+git567-gb10f6b4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12164 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.5.4+git567-gb10f6b4-2~nd+1_all.deb Size: 6191764 SHA256: ab1b5c4d41e2d7271abad0e9aea0b5ce10a6520f76c6d96246bed22ee771896e SHA1: 86bbf2b34b6d085445ad833afda5f6adcd470a9e MD5sum: 816f364837da87eb308963bab14a66d3 Description: documentation for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This packages provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: condor-tests Source: condor Version: 7.5.4+git567-gb10f6b4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/c/condor/condor-tests_7.5.4+git567-gb10f6b4-2~nd+1_amd64.deb Size: 3480 SHA256: e9644f6c3bcf7db31f11d7bec336353166dd6ddc60f6def76587395592599a0f SHA1: dbfb42211f90061fed1e37443c5526b6d8115c09 MD5sum: b3b9a5d290eac485d7ac5bb8e6a63e59 Description: test suite for Condor Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor, Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing system, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This packages provides Condor's test-suite that can be used to verify proper functioning of a Condor installation. 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: 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: 1.0.9-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2220 Depends: neurodebian-popularity-contest, libclassad0 (= 1.0.9-2~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_1.0.9-2~nd+1_amd64.deb Size: 573050 SHA256: e7ff578efb34e0537bf0806e8b87939673c6526e5776261bc9a1c635b143f153 SHA1: 3836db74477366fbec77ce1e2f2e1ca93cc3153d MD5sum: bd19dd46a65226901bc9668eb8db8cd2 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: 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: 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: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15624 Depends: libatk1.0-0 (>= 1.29.3), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.8.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20101102.1~dfsg.1-1~nd+1_amd64.deb Size: 4864922 SHA256: 86e21d89b5d4409c373b90ac5ae7e7c67685802b3bb67aa4d23c748e7e48b75a SHA1: d5bd8b1089f94769542728669c67ae50cf5b9ab1 MD5sum: d1e5a2cbcab35b38dd90da96379f07ed Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1852 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20101102.1~dfsg.1-1~nd+1_all.deb Size: 1665748 SHA256: fbbd06044b00a09b0797feda9bb4f3dbe8efa305380d3dfd974b7df11920599d SHA1: fdecd28e935671338aa2c5104d2819475b1a0f4f MD5sum: 5c5053032ec6aa65ac35d4a5d7086a96 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1220 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20101102.1~dfsg.1-1~nd+1_all.deb Size: 737360 SHA256: ebae0128cc36c8060fccb24609eb960d946a9de4ef3157f0e65d1eaf96aeef35 SHA1: 6d8c0a2054f62c790f8cbaa7c48ac1d70e74a888 MD5sum: d53ff217364a20faf63f6456a1b27751 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: 0.22~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.22~nd+1_all.deb Size: 111952 SHA256: c29704ff4fbe212b677532d670dbebb7a0d48d08e6c642dadad6a0cd40b2c75d SHA1: d2c15c230e7d75fe979f525ab737e087c1de8ced MD5sum: 82cc654ef5db25fc7b2e400090e00ecf 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: 0.22~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4372 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.22~nd+1_all.deb Size: 3788356 SHA256: e492985c4092cdbca0d7f86c9a9eba24fbd1209feb3b646fc1b99b89803cd917 SHA1: 4ddd28e8f2da0473a65e2b2736ce3d6c61080127 MD5sum: 5bebf9c32de2182a6eabb41c220d0f1e 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: 0.22~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 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_0.22~nd+1_all.deb Size: 10910 SHA256: 77b39331445d67043c35cf2755ec85bb822ecfa9c8f0536ba54157e0e79a24d7 SHA1: e33348f41bb0d2359b20c93c237e5fb4e126f3ad MD5sum: 8d63b21229f4a8ddf44817e76506d745 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: 0.22~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.22~nd+1_all.deb Size: 4698 SHA256: ec3ca953d0fd94f82af39b8f40e9e784fc8af49ca291e0e41903f4e3d45de687 SHA1: 8aff5ba99210ed2cc0964ee275e8131834a67875 MD5sum: e1675e39cacc06ef824f2a271812d088 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: 0.22~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.22~nd+1_all.deb Size: 3854 SHA256: 9f460cfd0ae38029baa05d97dbc9345527328bc45be64966ee0768a95c893ea8 SHA1: 5c8797e8bccb309f0424ba8767cc1e91fdf8cff3 MD5sum: bb5bb0e58da743c2fbc646382533a18a 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: 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: psychopy Version: 1.63.01.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4404 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 Suggests: python-iolabs, python-pyepl Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.63.01.dfsg-1~nd+1_all.deb Size: 2361346 SHA256: 700efda46d05a8c981e309dad6d849dfc91045a7bda03ce29babc4222787a225 SHA1: cca40585366f1cc49d6a062d2287d387d10aab46 MD5sum: 33695878ac9eb4979520f3fe41c84ccd 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 - High-level powerful scripting language (Python) - Simple syntax - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.5, 2.6 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.8+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: 1.2.2~svn2229-1~pre1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1736 Depends: python (>= 2.6), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-brian-lib (>= 1.2.2~svn2229-1~pre1~nd+1), python-matplotlib (>= 0.90.1), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.2.2~svn2229-1~pre1~nd+1_all.deb Size: 296628 SHA256: e608814a47785d3b62f5deac63a911f52423ddf1c6f392eba2f965e9d7592827 SHA1: ad5b21cdb83c99d9738585146522337f108ae7df MD5sum: 0bdc6a766e3a092468149a7faad25a72 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: 1.2.2~svn2229-1~pre1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4004 Depends: libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.2.2~svn2229-1~pre1~nd+1_all.deb Size: 860504 SHA256: 87886ed8fa1c0979869d7acbddf87e2838ad681c01b04acd0caec1f1b4e177be SHA1: 04d54f281eea05cba252a9c2be29c0991beb34f1 MD5sum: 7ff0300a28d9b66e3c95f6e3ef4777d9 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 and PDF formats), examples and demos. Package: python-brian-lib Source: brian Version: 1.2.2~svn2229-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 216 Depends: 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_1.2.2~svn2229-1~pre1~nd+1_amd64.deb Size: 53956 SHA256: daed9e56acb00a15bd6221e39e30a5f83894d6ccb698ec03d9672aa9ec0b6cd8 SHA1: e0963b116537eeac55a57354f7683f1542816d4f MD5sum: 4349f57462127dc3ebfcf22ed31cba0b 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-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: 0.4.6-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: 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_0.4.6-1~nd+1_all.deb Size: 38672 SHA256: c5bb30de24d7ae7b7ad6dec8c9f2fffbe7a327ba3e42164cdc903041e230c711 SHA1: 86a83704d8e03bbe6e60bd5138f957438bdba4ff MD5sum: 855225f4071e1fe4697007ef8214de54 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-mdp Source: mdp Version: 3.0+git8-g921253a-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1872 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, shogun-python-modular, python-libsvm, python-scikits-learn, python-joblib Suggests: python-pp, python-py Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.0+git8-g921253a-1~nd+1_all.deb Size: 450842 SHA256: c8a8df9061794e10bccfa7368ad2c0896885a62ab4386db10592b2e3fa2653bd SHA1: 945a2348374b55abaec9f9ce483c5eba3754dad9 MD5sum: 85f10aa762a3267e791581fba510e851 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-mvpa Source: pymvpa Version: 0.4.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.5-1~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_0.4.5-1~nd+1_all.deb Size: 2167538 SHA256: ef59abd523cb2a25602db157335858c76be23a860ce1cbc69acccae734da943e SHA1: da884e0fa1249e3f8d9f248b4bf9af485cc2533c MD5sum: 066f06deebccb91dc35dafa463d1400b 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: 0.4.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41052 Depends: libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.5-1~nd+1_all.deb Size: 9067604 SHA256: cf0b284af9f9414dc02204ac31625343d80f2b96644fbd718863bc506a8f60f6 SHA1: 7ad38563e0ceedd361e1c42c2b4ecc569d56a9d7 MD5sum: c2e96d3144191dfd8a181b7192052d74 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: 0.4.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, 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_0.4.5-1~nd+1_amd64.deb Size: 70014 SHA256: 6a33bff70c2b3266a205fc2a08fe9f319eca15cfbe625f1af19dae74e3f8b8e1 SHA1: 59cd49331b103a9317ed87a01dee9b271c81e204 MD5sum: 4682edfb8db73ea7a9ca2dc1b5b2fb30 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~dev-69-g7afe4f7-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4624 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-numpy, python-mvpa-snapshot-lib (>= 0.6.0~dev-69-g7afe4f7-1~nd+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab, python-h5py Suggests: fslview, fsl, python-nose, python-lxml, python-scikits-openopt, python-rpy, python-mvpa-doc Conflicts: python-mvpa Provides: python2.5-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~dev-69-g7afe4f7-1~nd+1_all.deb Size: 2284198 SHA256: e9420a28264b702ce8b824640868e5afbd2878d927898eae51bd7f126412a172 SHA1: 917c39adcb8510586906435700fb669e16dc6368 MD5sum: 500333770d321fd342fd27f740053dba Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.6.0~dev-69-g7afe4f7-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 284 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~dev-69-g7afe4f7-1~nd+1_amd64.deb Size: 60516 SHA256: b56a625f0a7c733e90d802bad89bab86d4dda80b8e6fbcc78f6058a99a5375d2 SHA1: 4428ac5c68ec3ba896b513cce7844d973a6e737b MD5sum: 4a2bf955e026af03b7ce6e4f8f57b243 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-nibabel Source: nibabel Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2784 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.5-nibabel, python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.0.0-1~nd+1_all.deb Size: 1061210 SHA256: 0505371d82e6a344e73ce30b5d1b7200f8a104bc3ebf561ddb5dbc4544f210f2 SHA1: 3bb315251ab12b46a378e1df67107d032fd81ced MD5sum: 7924017354df1fa9c4963e13ac694244 Description: Python bindings to various neuroimaging data formats This package provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nibabel-doc Source: nibabel Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2724 Depends: libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.0.0-1~nd+1_all.deb Size: 404008 SHA256: bda2ded9fa849d866db78959a43e71862b9a66cb02b663d7612112aac2ac4da1 SHA1: 1462cfbd7f63745042f8522b354cf186c51b9b1b MD5sum: c403118f483919e980093dbedbcb8e0c 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+20110114-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4588 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-nifti (>> 0.20090302), python-nipy-lib (>= 0.1.2+20110114-1~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+20110114-1~nd+1_all.deb Size: 1165334 SHA256: 23b0b75fb374a4f4e04382ce1b473c027d4fffc7801318153a248ca9ef2a89a3 SHA1: eab493bac1a890a7441ff11380e98975f26cd4ca MD5sum: 4d968f65251930513586c346015c2eda 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+20110114-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11348 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+20110114-1~nd+1_all.deb Size: 2842136 SHA256: 1cacca1937b3aa3d4cf26fb6c2647648facce9b7001a0d6a5a9abec00555a69c SHA1: d5f28e2db86c0db4cde73f6154c9dd7795f4b4a6 MD5sum: 874deb2ce596b9bf738e164e3d739c51 Description: documention 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+20110114-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3328 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+20110114-1~nd+1_amd64.deb Size: 1230232 SHA256: 99243d99abc8feba33434ea64171b418ffff791023549f77f4ab207f30c7bc49 SHA1: afd8ecb6d8d73ad24265f828fce0ceb1bb3bcd2a MD5sum: 515423ff7d5af87c67de894a9e710466 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+20110114-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3560 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+20110114-1~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+20110114-1~nd+1_amd64.deb Size: 1352156 SHA256: b6db40710c7f822ce7df7ba89443c022323bb7ded733063b0c264dae67ecff4b SHA1: cb9a88e8749fb3be7b6374cc9a947ecfac26d516 MD5sum: 5ed9b6cb67426781899d510824fc48c6 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: 0.3.3-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1752 Depends: python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits Recommends: python-nifti, ipython, python-nose, python-networkx Suggests: fsl, afni, lipsia, python-nipy Provides: python2.5-nipype, python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.3-1~sid.nd1_all.deb Size: 277514 SHA256: 368910b5558d3586e86bb6d919354e15c980d15156e87379ed5b6d92e9944637 SHA1: e8079a3aef6b6ea8822867bb23ea127d228e82c7 MD5sum: fb3c525781e1a4416582704f8041bd71 Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.3.3-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3640 Depends: libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.3-1~sid.nd1_all.deb Size: 840650 SHA256: a2adc848d29e0eac4f7f7d1e323d06441cc7a2a947d1f608364e3a2a14c4bd8d SHA1: fd337addc385ad76b1a6f1e19b9eafea534a8a62 MD5sum: 2cbce98a7cd66dac74d132b310f68328 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-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-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: 0.6.0.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1308 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-scikits-learn-lib (>= 0.6.0.dfsg-1~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_0.6.0.dfsg-1~nd+1_all.deb Size: 254802 SHA256: aafc63ac91bed2aa35cece84898482923702a2d23d98d04dd263b4df49344873 SHA1: b36e9ccfbe0fc36d6f831a2ae0dff698bfe56dc5 MD5sum: 620cd214688bcaba7e01f752661ece42 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: 0.6.0.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8844 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_0.6.0.dfsg-1~nd+1_all.deb Size: 4456714 SHA256: 2b839c18deaadf00e5ffae2b1941bde6dae7389d735b86d91967b32401317913 SHA1: 35b2ec1fcce3c2782ba65b5bbff79668183d7e15 MD5sum: ff818f6d34877d5a4f706e9131aa03e6 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: 0.6.0.dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2556 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 (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Provides: python2.5-scikits-learn-lib, python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.6.0.dfsg-1~nd+1_amd64.deb Size: 912608 SHA256: 1a09ff410d4d59c9dafdcbbbd50aef132d1ea6a65b1deba156bf982a6bc1825e SHA1: 07b903c0594c9bf40ced43396ad256363c0ce3ee MD5sum: db89756d768b37eec13e420e1ba2faf2 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: 1.0.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4580 Depends: 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_1.0.1-1~nd+1_all.deb Size: 1233522 SHA256: 9d2412a330c57af8bd8adff6703a5e3c70346a1b892e02a8bb18d751b374ccba SHA1: 5f994974763ed9fa89766248c7ff86510b9fe1b2 MD5sum: a7aa0438348ec0b070a3b32c8f566511 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-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: 8.4010~dfsg.1-4~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21124 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4010~dfsg.1-4~nd+1_all.deb Size: 10087172 SHA256: adf7dd05ad33fa85c8f4fa3321a4ef87e9dc87e5ef52e8ae5c22ed5528923093 SHA1: 1fa4d631a4ad3bff09bc738956a2db38421bd5c0 MD5sum: d2d24b5e6188b06a78275aaefb1654c6 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4010~dfsg.1-4~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73316 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4010~dfsg.1-4~nd+1_all.deb Size: 52168442 SHA256: 491c07c46ba0d67154d7aa9aa52b9b9a40ee79e40a2474fd3196597191032155 SHA1: 10266c0c8bcf02b921f5dbade24c19650f2b2013 MD5sum: f19e8088d81dd21091ac7af81c713926 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4010~dfsg.1-4~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11288 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4010~dfsg.1-4~nd+1_all.deb Size: 10423792 SHA256: b5194321d5b58755ac0216f9977fc8408ac43dc3123f45354454644606ee59a0 SHA1: 296675b0d70be451ece77f3de2faa3ff5109d006 MD5sum: 12ce47b9c6ee812db84bd9e2466006de 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: 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.