Package: ants Version: 1.9.2+svn680.dfsg-1~nd60+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~nd60+1_amd64.deb Size: 11489456 SHA256: 39efeee21fd772a3ee5fe415c901a1d99f6a3211a2614b756989d1b90c22e67d SHA1: 993f2c23c2a994857ad0235b14628ba087156fa0 MD5sum: e0522aa5d4ee9bcf88764a1cdd022e31 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). Package: arno-iptables-firewall Version: 1.9.2.k-3~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~squeeze.nd1_all.deb Size: 132476 SHA256: b002efbc460e228ef300147169187793cc9cc8b36e7acf807567d35aa8d56099 SHA1: 7945add5a3b0968d8deeac27bb6d5bdf667ff03a MD5sum: ebcb9a6d4f275258f76616360ff739d0 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: autotools-dev Version: 20100122.1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 216 Depends: neurodebian-popularity-contest Enhances: cdbs, debhelper Homepage: http://savannah.gnu.org/projects/config/ Priority: optional Section: devel Filename: pool/main/a/autotools-dev/autotools-dev_20100122.1~nd60+1_all.deb Size: 72966 SHA256: dee3f923f4e6856aac8efa5aa8c890af4466679721b9a2dd03977c7bddf0d857 SHA1: 2c2a0419c7324111348c91772971ffef898ef835 MD5sum: eab0255d3b1d7620acccb2f6e01b667e Description: Update infrastructure for config.{guess,sub} files This package installs an up-to-date version of config.guess and config.sub, used by the automake and libtool packages. It provides the canonical copy of those files for other packages as well. . It also documents in /usr/share/doc/autotools-dev/README.Debian.gz best practices and guidelines for using autoconf, automake and friends on Debian packages. This is a must-read for any developers packaging software that uses the GNU autotools, or GNU gettext. . Additionally this package provides seamless integration into Debhelper or CDBS, allowing maintainers to easily update config.{guess,sub} files in their packages. Package: biosig-tools Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd60+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~nd60+1_amd64.deb Size: 253018 SHA256: 701eb19d5db76d60007d0929a132718bb2641a700ce8a0edbcd15c9972adad9a SHA1: 0c1ac2c0c07282fe032ee225484a9d813f6c49fc MD5sum: 99e8c00c062e2dd143cfc606519d9ec0 Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as * save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. TODO... Extend? ship client/server? Package: caret Version: 5.6.1.3~dfsg.1-4~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18628 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libminc2-1, libqt4-assistant (>= 4:4.5.3), libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvtk5.4, zlib1g (>= 1:1.2.3.3.dfsg) Suggests: caret-data (>= 5.6~dfsg.1) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.1.3~dfsg.1-4~nd60+1_amd64.deb Size: 7152804 SHA256: 36531ec0b51e710ff91e8eff1e281ea230fd67279c4210315cef53c39b621f9d SHA1: 1eac293c8a1e955c6c64f6df77579c0d1cb52ea7 MD5sum: a8583a1a33e3a53866eab6755c9e0717 Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Reference: . Van Essen, D.C., Dickson, J., Harwell, J., Hanlon, D., Anderson, C.H. and Drury, H.A. 2001. An Integrated Software System for Surface-based Analyses of Cerebral Cortex. Journal of American Medical Informatics Association, 8(5), 443-459. 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 SHA256: 329a14cfd5547064496d4f6909db62578412857ad7d5f73e129335481f550b47 SHA1: 7d6cbdd77b04f258327d2bc9fcc4b0494fcf71bc 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libclassad0 (= 1.0.9-2~nd60+1), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: misc Filename: pool/main/c/classads/classads_1.0.9-2~nd60+1_amd64.deb Size: 36536 SHA256: d2330cab6752b6721c0efca9b60570733d28c6f9abbf25a1e5e5ed3d69acfcd3 SHA1: d2fe0196d00656599f8f6244eea3570fff48504a MD5sum: 23ced7a4a5a134d5005583dce5d2b19b 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~nd60+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 (>= 8.4~0cvs20090328), 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~nd60+1_amd64.deb Size: 4399116 SHA256: d61ee73df51bab5bb1868a880408b174c1181c0de4213a30babfed143326553b SHA1: 431d9984f35bf8fec8e985367e07d9cf4183c892 MD5sum: 1b82530740f33e3e96960595592e11ef 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 35156 Depends: neurodebian-popularity-contest, condor (= 7.5.4+git567-gb10f6b4-2~nd60+1) Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.5.4+git567-gb10f6b4-2~nd60+1_amd64.deb Size: 12337974 SHA256: fedb590226496a09dd061627a359cd7a404d59f5c06eda0fa9bc774a956947a5 SHA1: 9416eddf5a6aee698cfb414e17097db3732263d5 MD5sum: ce464d408f66fd5599b5b58ab3a8a878 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12160 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.5.4+git567-gb10f6b4-2~nd60+1_all.deb Size: 6189058 SHA256: 343d05155abafc44257cd6f8cde4c7dc940317b6bb1b407c7d2f78f33800e2e8 SHA1: 88ee54dd4ba7ac9c5dfd051d508306489ae05c75 MD5sum: 20780293fe636eba3ad8915392199031 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~nd60+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~nd60+1_amd64.deb Size: 3486 SHA256: 121633f1c9ef0721e43011afbc0e0ab1df15e56b4f7093339b66e38cbc4ce36a SHA1: 0a73e4213d838462bbcba29feb50a7fbcebefcd5 MD5sum: 62837c213788d4e352fb8bf6ced0e79d 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~nd60+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~nd60+1_amd64.deb Size: 1331862 SHA256: 22f7506f5a19bb2bf75e29dbd27ca63e75fcc34c32630c21ff33fdc74f1c096a SHA1: ef4f6d6c619233f61ba975cfa9ff0589bf44855f MD5sum: added61380c2e8e7e3dad8d6cf5f9d5d Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd60+1 Architecture: 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~nd60+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd60+1_amd64.deb Size: 3422986 SHA256: 654ce21ca53f650629c50f607beb15915f72df8c5af595ec985cff34956d231e SHA1: 92739a417384b350ff63d57e9767d96f3c4ec648 MD5sum: d45deeb7aaf79ecefce8f55af58b4740 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: dicomnifti Version: 2.28.14-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 512 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.4.0) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-2~squeeze.nd1_amd64.deb Size: 157006 SHA256: e1dc380ba89272d7463c706eff98cf52d05f7e65c4277a4452ba700d506f0429 SHA1: 0a1c1c490f682b722786b09ff7aab3b34bbdabf7 MD5sum: d13b123fb4c03fe1dbd20d4ee9e562a0 Description: converts DICOM files into the NIfTI format The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer. . dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files. Package: freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+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~nd60+1_amd64.deb Size: 3112 SHA256: 9e737bd53d670e1c5fdcc0780173ceab1d980d759c313d62fd723f905f238361 SHA1: dc584087c95ac1f6f5d8fcdaea421caa91dcfc03 MD5sum: a7b794d358ca8848052a15a21dbd1750 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4164 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8b), libqwt4c2, libstdc++6 (>= 4.4.0), libvtk5.4, libvtk5.4-qt3 Recommends: fslview-doc Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_3.1.8+4.1.6-2~squeeze.nd1_amd64.deb Size: 1523802 SHA256: df84b94155e89d357e6b50bb78c24ad74020a8ff579f1ea6f236558c7cf6b04f SHA1: 5e83e84fae04918145d955ea4bab317ccaeae570 MD5sum: 2dc26463b7c2ef428443b27ca963b098 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3216 Depends: qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.6-2~squeeze.nd1_all.deb Size: 2378936 SHA256: a8fbd782cbb61ed77104e5e28da08040c63de551af6dda1e6ee41a098b40dcc7 SHA1: 565f0f4026969f9fa84091efdec611106608ebf8 MD5sum: f3f752fb3534ec465e7f6c98503ec376 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gdf-tools Source: libgdf Version: 0.1.1~svn62-1~nd60+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~nd60+1_amd64.deb Size: 39404 SHA256: 2f0ae8c7bf64d72f3c79bb53ab180ef0ebb4615ca082641a8205d92e52683597 SHA1: eba254a1e28eb7f5c8cd43ca7c5b21a7d3a2c9e1 MD5sum: 6a180517d80bfb1faadd42cda9007aed Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: gifti-bin Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 124 Depends: libc6 (>= 2.2.5), libexpat1 (>= 1.95.8), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-1~squeeze.nd1_amd64.deb Size: 29324 SHA256: e2556c47eccb3a6a5016e1f1ad69c37faab71d5df40ff05ca3922b3c34a2d339 SHA1: 8c0404cc4418f02b2fedc4d753f3793855952ee6 MD5sum: 9c226f7c644ff53a56e3e4150769f7b7 Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: itksnap Version: 2.1.4-1~nd60+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~nd60+1_amd64.deb Size: 3707204 SHA256: 65da6fe4cb19e80a1cfcf4a8422b4f0949867e477e132a4077390919d2895d25 SHA1: a7433bb717323702150ff1f4ff3228aa22025cf4 MD5sum: 7bb09718b431d17917c235ae0d8a014d Description: semi-automatic segmentation of structures in 3D images SNAP provides semi-automatic segmentation of structures in medical images (e.g. magnetic resonance images of the brain) using active contour methods, as well as manual delineation and image navigation. Noteworthy features are: . * Linked cursor for seamless 3D navigation * Manual segmentation in three orthogonal planes at once * Support for many different 3D image formats, including NIfTI * Support for concurrent, linked viewing and segmentation of multiple images * Limited support for color images (e.g., diffusion tensor maps) * 3D cut-plane tool for fast post-processing of segmentation results Package: kbibtex Version: 0.2.3-1~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 2860 Depends: kdelibs4c2a (>= 4:3.5.9), libc6 (>= 2.2.5), libqt3-mt (>= 3:3.3.8b), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), libxslt1.1 (>= 1.1.18) Recommends: texlive-bibtex-extra Suggests: texlive-latex-base | tetex-extra, bibtex2html, latex2rtf Homepage: http://www.unix-ag.uni-kl.de/~fischer/kbibtex Priority: optional Section: kde Filename: pool/main/k/kbibtex/kbibtex_0.2.3-1~squeeze.nd1_amd64.deb Size: 816752 SHA256: 11107abe9f2082c8db25fcafeadbde31c3894bbf7bd0e480b73f2d0c8cb14064 SHA1: 865cb1a2891a1902e9f30d51a898d2971561a602 MD5sum: 41b38f4770b6e2ebeb96e77f047c1eca Description: BibTeX editor for KDE An application to manage bibliography databases in the BibTeX format. KBibTeX can be used as a standalone program, but can also be embedded into other KDE applications (e.g. as bibliography editor into Kile). . KBibTeX can query online ressources (e.g. Google scholar) via customizable search URLs. It is also able to import complete datasets from NCBI Pubmed. It also supports tagging references with keywords and manages references to local files. . BibTeX files can be exported into HTML, XML, PDF, PS and RTF format using a number of citation styles. Package: libbiosig-dev Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1612 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd60+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.2+svn2552-1~pre1~nd60+1_amd64.deb Size: 379266 SHA256: 0f7e866a8efcaf4f56bb8612adf743db0289debd89b5c9cc6173399494703b2e SHA1: 9c219bdb42b41a7ce64e5d8b88fd5d2e43b0dca2 MD5sum: 6f78331ea29511fa68b2c43831cc50f3 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~nd60+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~nd60+1_amd64.deb Size: 302808 SHA256: 09d30c08c0d36ee25d7b3ace5342a3ba215eb2cda64be89c30b315f43dda625f SHA1: ed853af624b12a6267b12e4980dbca4bb28811b5 MD5sum: 44d1eb06bc8ba0d71dc3f540177f1696 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 712 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd60+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.94.2+svn2552-1~pre1~nd60+1_amd64.deb Size: 171870 SHA256: d34c361719ac05a949368e72762b57e798de97c01e4d6de59edf0d2f846a131e SHA1: 9b7b43b7e0a851d373f684a768832df6febc90f1 MD5sum: a21d063bca0a900216e5255a0baf4dff 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2220 Depends: neurodebian-popularity-contest, libclassad0 (= 1.0.9-2~nd60+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://www.cs.wisc.edu/condor/classad Priority: extra Section: libdevel Filename: pool/main/c/classads/libclassad-dev_1.0.9-2~nd60+1_amd64.deb Size: 573026 SHA256: ecc75ec320619344024c01a60d74ab281819b162a1a58916fd6adf41ac871fef SHA1: 5d454de0341c4cc04c70321de89eb13fb24de9d7 MD5sum: 2dd3fc23bad948559eb770f1a5612dbd Description: library for Condor's classads expression language (development) A classad (classified ad) is a mapping from attribute names to expressions. In the simplest cases, the expressions are simple constants (integer, floating point, or string), thus a form of property list. Attribute expressions can also be more complicated. There is a protocol for evaluating an attribute expression of a classad vis a vis another ad. Two classads match if each ad has attribute requirements that evaluate to true in the context of the other ad. Classad matching is used by the Condor central manager to determine the compatibility of jobs and workstations where they may be run. . This package provides the static library and header files. Package: libclassad0 Source: classads Version: 1.0.9-2~nd60+1 Architecture: 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~nd60+1_amd64.deb Size: 428738 SHA256: 67bbb461be88e142837d81b95542868f99b8309c05fa81b346a6f6d47a1c17ee SHA1: 189b2cf5600add30e8eaed266ef6001cdf6f7466 MD5sum: fb6097532b6c292e30012718f64ce43d 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~nd60+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~nd60+1_amd64.deb Size: 25970 SHA256: cd48f693c70093426d484d7c81d4af1ae49b5c8a10e4049bc9af3742bf248ac0 SHA1: 8463f6d81453f6f472e7a243c0a4a0f4a8063a6d MD5sum: 74b8545a2dd0f8c2641773947161cdda Description: library for accessing Kinect USB camera -- demonstrations libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package includes some example programs for kinect. All programs start with a freenec- prefix. Package: libfreenect-dev Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+1 Architecture: 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~nd60+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+1-2~nd60+1_amd64.deb Size: 25258 SHA256: e24f681c776f89f0b2923a27c921592d158bfef409b408e362d8f50372e6024f SHA1: 9f4ef43dd914445b734ac9f24fa7e879eb9ddf13 MD5sum: d63e2f93e25aa5894af26d403c183ca7 Description: library for accessing Kinect USB camera -- development files libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect0.0 Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+1 Architecture: 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~nd60+1_amd64.deb Size: 26110 SHA256: f8c63145824b4869b0bdb45b05773a8072a753fe398d0bd8a73fef607f1f31d7 SHA1: 82abefb92ebc0ee225700efe61aa313ddb7025eb MD5sum: ad525e18f8086413b2c7a3c207d089b5 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd60+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1~svn62-1~nd60+1_amd64.deb Size: 18008 SHA256: 9f26e88f3f65f0011c1f7de712a2a3196169272cd09c513e796c0c9d405bc409 SHA1: 0d242ec7b75b845a70182291738430a10f86d0c5 MD5sum: f741f280285ce1cd794807e279c1a76d 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~nd60+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~nd60+1_amd64.deb Size: 104586 SHA256: a7edd8850e45990392ba961f8b65b928a531f504a3a7f0b2189eee0f09df9bd7 SHA1: c0835f00a2f2c27b9234e3afa79f10a0a3275562 MD5sum: 0e7a04b3a638c0a721369dbb2459ad60 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4156 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1~svn62-1~nd60+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1~svn62-1~nd60+1_amd64.deb Size: 1106322 SHA256: f43c66ffa190def3c5fb8a9d01f82e0ee4accf996cf01759dc416fbc7fb67a8b SHA1: f5a0088af62f5f260cc550877ab1dc01aa9a7345 MD5sum: 2f340be18369dd9bc96523aa2449e245 Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 256 Depends: libgiftiio0 (= 1.0.9-1~squeeze.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~squeeze.nd1_amd64.deb Size: 65262 SHA256: a76723f3ffd3d00117217c6296ac9212cb34d597b9feafb51a48b6f481fb2a83 SHA1: 67ac21a682e867a0fa2e87b2017d8223af1df075 MD5sum: 5483d94d7b3cceb80b5e86d3133b580b Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 176 Depends: libc6 (>= 2.3), libexpat1 (>= 1.95.8), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-1~squeeze.nd1_amd64.deb Size: 57476 SHA256: 9177c604d183cfcca0c12cc172a865791417f4732a5503b2cc3833216524b897 SHA1: 68edb77db9badcca0b34dd203367d6ffa0c58c99 MD5sum: 3af42d32e40221ff48f8f7f5a55c4ad8 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libnifti-dev Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 620 Depends: libnifti2 (= 2.0.0-1~squeeze.nd1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-1~squeeze.nd1_amd64.deb Size: 171078 SHA256: 606c5b60cea6a9d184501cea87b55e9276b8c018fd81ce151ab891ecdeee1ab5 SHA1: 756547a678e5e0d744325529bbd3f41085728547 MD5sum: b324df0f6b88a8eb53a2354f92aeb3a9 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1896 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-1~squeeze.nd1_all.deb Size: 245414 SHA256: c421052431a49808544394d7242ddbd0437c09c001e9936fa302d29b653603d6 SHA1: 16d20e3475e20aaf39aa4df9231cb5117421d33d MD5sum: 1de8bde7f67f9fd2b7f2571ba0212457 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 332 Depends: libc6 (>= 2.7), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-1~squeeze.nd1_amd64.deb Size: 122310 SHA256: 64c18d6b2d42039e97c6b2c6157941c416bc3d49c9a71505b8009fdce45c0689 SHA1: 13dff3f1be4bc415cb6a34b73912629e30010344 MD5sum: 1c318229155fea0a86b5302d571456a0 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libodin-dev Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 21016 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~squeeze.nd1_amd64.deb Size: 4196634 SHA256: 2f2b4f24bd5d56c425d1a8d4cfcc7ece0afd575349423891c8bc1f921473ba73 SHA1: dda48dc2ecc2dc76f0cd12b9dc6a751c03fb1967 MD5sum: 51291b7c5d674095d84de8c1833ef7e8 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 276 Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-2~squeeze.nd1_amd64.deb Size: 43848 SHA256: c113f4e2260e469c9d5c31b5dfad482410bd731f254ece10ed056e3e64cb1e3c SHA1: 062bbbaf74194eec6f79554a2257a4a2b9e34e72 MD5sum: 1355332d7b7d3cc9ed6cfc243acb1631 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 964 Depends: libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-2~squeeze.nd1_amd64.deb Size: 253140 SHA256: 9552f235f659a25149cac15a7ff36dcea3ffd09096392cd1a140f7477ab71a75 SHA1: 332f87d24581812ff375ddea6a7aff42b732e946 MD5sum: 892f378826bc8efb0774b99837e9e020 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. Package: libslicer3 Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: amd64 Maintainer: Debian Science Team Installed-Size: 125536 Depends: libc6 (>= 2.2.5), libcurl3 (>= 7.16.2-1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libinsighttoolkit3.16, libkwwidgets1.0.0908, libstdc++6 (>= 4.1.1), libteem1 (>= 1.10.0), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, zlib1g (>= 1:1.1.4) Homepage: http://www.slicer.org/ Priority: optional Section: libs Filename: pool/main/s/slicer/libslicer3_3.4.0~svn10438-3~squeeze.nd1_amd64.deb Size: 26921078 SHA256: 34cac2737d4af7fb3318b0e69e524ef4bcdb9f39af3f7b6678299d0ec7f0e0af SHA1: 3589b3561719cd8b878adbf7e9edbf1ac5cb7651 MD5sum: 06ca061fd0a529d0d8b53c33d0d35d68 Description: software package for visualization and image analysis - runtime Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer libraries. Package: libslicer3-dev Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: amd64 Maintainer: Debian Science Team Installed-Size: 3088 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1) Conflicts: libmrml1-dev Homepage: http://www.slicer.org/ Priority: optional Section: libdevel Filename: pool/main/s/slicer/libslicer3-dev_3.4.0~svn10438-3~squeeze.nd1_amd64.deb Size: 446184 SHA256: 1972a9931ea8c384f1f1e1d1edcb235ad985e2300321be9f73bee14cbe66dec0 SHA1: 925bbc86c9261b5b25e7fe2bbe5345a284b4bffb MD5sum: 551206a99536696d0fd59f94b85efa73 Description: software package for visualization and image analysis - development Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer development files. Package: libvia-dev Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 916 Depends: libvia0 (= 1.6.0-2~squeeze.nd1) Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_1.6.0-2~squeeze.nd1_amd64.deb Size: 242248 SHA256: 6f7775049ae209a52d8468bce2d4d37822a99e740b77a9557b3804b950bc984e SHA1: d9f210e22c30e087eac0ca02544803fd2a771a3a MD5sum: 0908d88d076f9197702c60f9157de461 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 936 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_1.6.0-2~squeeze.nd1_all.deb Size: 110492 SHA256: 4e8b7ff2508c5a1611f3b8c0a7187d504559a7afc6333b3cd00fa4f20fc4cc88 SHA1: 6153d1287d5042551385c28bd9e46c9b5258c390 MD5sum: 1e42168726e0b36b1b9c1aefec7a276f Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia0 Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 476 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia0_1.6.0-2~squeeze.nd1_amd64.deb Size: 189924 SHA256: 2c95226e0a9b661583bb7ea104a37a21f38c974bb5c5a24876b2f360348be659 SHA1: 06bf55af063d29cb4b1b448b3421770c28e9dc99 MD5sum: 721ea2b500a2736110651947afae7125 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 3804 Depends: libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti2, libqt3-mt (>= 3:3.3.8b), libsm6, libstdc++6 (>= 4.4.0), libvia0, libx11-6, libxext6, zlib1g (>= 1:1.1.4), via-bin Recommends: dcmtk, lipsia-doc Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/l/lipsia/lipsia_1.6.0-4~squeeze.nd1_amd64.deb Size: 1347266 SHA256: 979d00009ee4b4d9313cc049a902879ff81f753e0f8bbadf32ba64a8d40a5362 SHA1: 07aab2dbaf06e65c5e284364b0bfd865be0a3561 MD5sum: 05210b5b08e55aa400f3a5fe14e6cdd3 Description: analysis suite for MRI and fMRI data Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an efficient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development of LIPSIA was the efficiency of the software implementation. . LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported. Package: lipsia-doc Source: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 7004 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/l/lipsia/lipsia-doc_1.6.0-4~squeeze.nd1_all.deb Size: 5539242 SHA256: 698077dd0ec212ab7db8d81fb1ea253fde3176d0817184edf9cc35f1b634be0b SHA1: 9370ec74bf24fddf9143bc0556f7f3535560b929 MD5sum: 5d38c0c06db5d46971b92e261ab545db Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: matlab-support-dev Source: matlab-support Version: 0.0.14~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.14~nd60+1_all.deb Size: 5470 SHA256: c08905c7ea85e0cca79a7d7ad975e801e5fb210c7f42b3a109f7ee8c81a3066c SHA1: e818c9eb90a39a197fad15e3f906cdb57933fd38 MD5sum: 5ae0952ee0a3ba92f156de5a9b26732b Description: helpers for packages building Matlab toolboxes Analogous to Octave a Makefile snippet is provided that configures the locations for architecture independent M-files, binary MEX-extensions, and there corresponding sources. This package can be used as a build-dependency by other packages shipping Matlab toolboxes. Package: mitools Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: 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), libnifti2, liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-3~squeeze.nd1_amd64.deb Size: 2438536 SHA256: 1c1bf6931b9db09d20118043b6670520352d76690bcba2bd9e626a7c14977f66 SHA1: 83a45f396f36edfcef79c2461bc01f038d61082a MD5sum: 18612ad31c664fb9fa1580a7e577657d 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~nd60+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~nd60+1_amd64.deb Size: 4864916 SHA256: 174afd49bd0ad33beb450162061b5e9eb7710ccd7698d28926c67a6945d75f5a SHA1: ca3bb6034041a9485e156405364fa481623502c7 MD5sum: ac0f72bc96bb9df0b9191d8dfb8198f7 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~nd60+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~nd60+1_all.deb Size: 1665752 SHA256: 7ba90f5148361b9ca37c6e08c91d99b6ecfb31b62d07cee52524d89b894b3b0c SHA1: 5697ee9a40badfc9ad66718480ceb18ff806ce16 MD5sum: b808906b5cd684f88b0e2ec7a113aa3c 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~nd60+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~nd60+1_all.deb Size: 737370 SHA256: 62f5cc8fe0124f2715d8c833f56abb845731c9ca9b3de4a585983c9c195a4bb6 SHA1: 8351ebd6143da6e2bc5f599cc5b94f0444c30f35 MD5sum: 8742cab4a32fd17d190e88ae27106eba Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.8-1~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 7260 Depends: libatk1.0-0 (>= 1.29.3), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.24.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.20.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.26.0), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.3), libx11-6, libxmu6, libxt6 Suggests: mrtrix-doc Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.8-1~squeeze.nd1_amd64.deb Size: 2259318 SHA256: ba24fafe774ad04731c7d1512f7c59a56d19460841c156fd6e1ba63c7b0eb165 SHA1: 936d88a06375fc0a08fe8a0f4700b99a9647a754 MD5sum: 419722ec323decf6fd6dd6f4cbc2a0dc Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magenetic resonance images in DICOM or ANALYZE format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.8-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 3416 Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.8-1~squeeze.nd1_all.deb Size: 2949200 SHA256: d09abc3e306bb2c180870e91d45439b7a3c4e7b63e0991af6a1a6df4b1e55274 SHA1: aaf46c988af9be0c7145312f44a0db291fc1fe07 MD5sum: 3185125d78f719d3942d277b91c59c5c Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magenetic resonance images in DICOM or ANALYZE format are supported. . This package provides the documentation in HTML format. Package: neurodebian-desktop Source: neurodebian Version: 0.22~nd60+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~nd60+1_all.deb Size: 111958 SHA256: bce9c5bb4b079354ebae9cbba0161d2e36483aa312e195362024f017814bcaf8 SHA1: dd8d516921f8fef2488675549c525fe83a3db499 MD5sum: c9d57a7ef97024a19d8f8160941cf17b 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~nd60+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~nd60+1_all.deb Size: 3788356 SHA256: dfecac1e4aeff00d707661a159a10c33c62579a9ddf330accfc2ae43d86b125e SHA1: e792ea3377073c40d3b2d69e20de4a121aed8f4a MD5sum: e62655be8295b8b75669e792dff587c5 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~nd60+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~nd60+1_all.deb Size: 10918 SHA256: c9dd0b0faf30e765550186d63fce21a0971643b1e91756d0df8e9313e2910d76 SHA1: fb0d5c6c6911109c1fa78c5baeee8b3a264dd74c MD5sum: fcbf0d3d368e6e3e1175ad872b1b577f 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~nd60+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~nd60+1_all.deb Size: 4702 SHA256: 25f288a78c944c7341a9814f89954ab4782c6189bb802fbea56ea4d9a8d9abbd SHA1: 0f13929e310826151d19818f5e03c0b6c4626e2a MD5sum: 1b95f186a6ecfc676eec175ebdd3254c 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~nd60+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~nd60+1_all.deb Size: 3850 SHA256: 718fde6a8b8b60bfee57a8da6fb9c0ea67a83757b0496e88f3ecdb39edd0e501 SHA1: bfb9d78e162fccf1ec36161d6b63f4cc521a0749 MD5sum: 6f3161ee0f989296d4d4c0f5fac71ae4 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti-bin Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 192 Depends: libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-1~squeeze.nd1_amd64.deb Size: 62198 SHA256: 1256f60544b62afd9dc439b9d9140f9f9d45d2cf4acd39acdcb91c4c2912e213 SHA1: 663320bd769210e86f738fd69145b663129280cd MD5sum: 7e62348a771f5851cc7438eb5b2bfb54 Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: octave-biosig Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd60+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~nd60+1_amd64.deb Size: 591802 SHA256: bc4c1dd82ae4dcfbc064e269000a510edb4f0d4b73bab68bc24f36efb8b19df8 SHA1: 9fac0c4f0b24155727a7ecc78a0af3f632263632 MD5sum: 7fe1cf68ec287349ea9170157700b1d2 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~nd60+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~nd60+1_amd64.deb Size: 131368 SHA256: 06c228f0c858a1dbbb8f2c51e9e773fb09262172ae4459144f60495c812915d6 SHA1: 3c8bc7b4ae0e9b95f8e8b83a14af990e8b2a9c63 MD5sum: d7a5bb745acccb39f00cb12486e1bfa2 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~nd60+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~nd60+1), psychtoolbox-3-lib (= 3.0.8+svn1934.dfsg1-1~pre2~nd60+1) Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.8+svn1934.dfsg1-1~pre2~nd60+1_amd64.deb Size: 748074 SHA256: d21724d6311311764a38a5dbabe54bd39b9a6994910870c37bbdaa50ef0cf4e7 SHA1: 052e81861965dbdbd0b71548c1f9e8f3465d030c MD5sum: ecf082299225b0040287febe5c2bb71e Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains bindings for Octave. . =========================== BIG FAT WARNING ============================ . This packaged version of Psychtoolbox-3 for Debian has been neither extensively tested nor officially released. It is known not to be fully compatible with 64-bit systems (yet). Please do not use it for conducting real experiments, and please report any detected problems to team@neuro.debian.net so we could assure future stable performance of PTB-3 on your systems. . ======================================================================== Package: odin Version: 1.8.1-3~squeeze.nd1 Architecture: 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 (= 1.8.1-3~squeeze.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.1-3~squeeze.nd1_amd64.deb Size: 1572226 SHA256: 5288e874586283f8d6aaec5cef7bdaae4d52fc332a02a17f073a3bb29d510fef SHA1: f004635ce76504339443399b17161a8f66e44a7d MD5sum: 2c6a128c6f8a99ac4638dde70657fe69 Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~squeeze.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~squeeze.nd1_all.deb Size: 34368 SHA256: d3c29b416792bf1d8ca68eb2af7da3b0d60a8f0d836fa9d1d3b83cdd9329b878 SHA1: 1f8d2aca09d37c8e5efb01093a0e10909a862e38 MD5sum: 78bfb172b4686b3985ab9ee42929d028 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 548 Depends: libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-2~squeeze.nd1_amd64.deb Size: 166870 SHA256: 182aa2adac63a2cdfbbb3a098056ec5574c76d2725d8dcdc499e53f3322e8a16 SHA1: 016f08d5dbb4cb9c1171502291c013b6ed352442 MD5sum: eb26062f1929486b6ceb886670b040e7 Description: tools for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides command line tools. Package: psychopy Version: 1.63.01.dfsg-1~nd60+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~nd60+1_all.deb Size: 2361354 SHA256: 5e482dd1bd552bf03b813a06bf5fefaa36e211cc843508449691deaedb04d68f SHA1: b38bac2a306e25d79ec35cca810c3b6391b0821f MD5sum: 3c9a7fac6bc6318f788a7fad78ba3bd5 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31368 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~nd60+1_all.deb Size: 13337660 SHA256: aa16477a015f17a267c6a2c42551a1b1c0491fe8ad054afb0af2aa86ddef40b5 SHA1: e1e2b2e148475bbb7425767310df3f89493294bf MD5sum: 52256552ca2e1ac11b7af0cf627993eb 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~nd60+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2648 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.8+svn1934.dfsg1-1~pre2~nd60+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~nd60+1_amd64.deb Size: 775764 SHA256: e8386742930a002ad2cec8ca8782ce7ca78c38e463c13cbfcef5859e151b3f7e SHA1: 698c8bce6ee42c5716a22ff3a1b3ca1f27663344 MD5sum: 88dd70ca681ecd6ded3ebe3cc1ca33a6 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~nd60+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~nd60+1_amd64.deb Size: 61642 SHA256: 6ca63d1261b44e7113ac2889740803bec0f6250e8764f37526de960328119ff2 SHA1: 164904bb4b3d7e2b2587a5243f1af91d9507c199 MD5sum: 206289e72cdb11e1ba369704e5a4b84c 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~nd60+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~nd60+1_amd64.deb Size: 336494 SHA256: 5f36d1355bdc030067f169109d52fd133ba75d5263c1e5966669699c3455f782 SHA1: 1287ed4422431eaefc0228d101791652b2dae1b7 MD5sum: cb9b92f61a00ea6f0cb2a37351d6ad0c 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~nd60+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~nd60+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~nd60+1_all.deb Size: 296648 SHA256: 14f5977d922a9294638660a4e65de2b019ea1b35ce20f156cc82691c8a15cb63 SHA1: 0ee996fd6665d59a42e62ecf5a21773b1cf4eaed MD5sum: 922ffe67841aeae5189a5d9b5563d217 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~nd60+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~nd60+1_all.deb Size: 860512 SHA256: 4f52d278350b0798e094d6fd6b828774d2f7fd846c3be6dfa9aa277b31bbfc43 SHA1: c421281c045075c5b20f40b0b60f8f9d5551e119 MD5sum: 59be3631bb4e066218f2af169fab0af8 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~nd60+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~nd60+1_amd64.deb Size: 53968 SHA256: 2d26eb40a4cfb2804d11396294186dbf4d599286f818a1f45cf5dc839f9cb292 SHA1: 1d25f7e7cdc5d7838092d8914e9e634a0bc97263 MD5sum: 97bbc02a7895e0aa61c0401e006fec9c 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~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1864 Depends: python (>= 2.5), python-support (>= 0.90.0) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.5~rc1-1~squeeze.nd1_all.deb Size: 372934 SHA256: 86c7cf926457b1ee202649b15563e1cc5f38003f0b12acd47b0f912fe7ba3349 SHA1: 69ded2a0cb005e606fdb53ae5c7d2812a9e08955 MD5sum: 18025a434efb994467d69e223bd17d6d Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+1-2~nd60+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~nd60+1_amd64.deb Size: 33938 SHA256: a0812d1687360e65661e2e86f7b0d098ae59ce60d28e32bb04ad6897f78d58dc SHA1: e68ce706c24559a256a50ca05f9a81e9c2a789c4 MD5sum: 5c18963a3118e43a6661779dd03b2e9b Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.4.6-1~nd60+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~nd60+1_all.deb Size: 38664 SHA256: 3d547cb745bc6ff58ada5f33d788ec5dfff82fef03aafcd976ec397b2ae1e6da SHA1: af3882c95c62855a860d685827577cc53a0f48e8 MD5sum: bbfae468703071fede9441d5a0b080c5 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: 2.6-1~squeeze.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 1556 Depends: python (>= 2.4), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-shogun-modular, python-libsvm Suggests: python-pp Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_2.6-1~squeeze.nd1_all.deb Size: 294380 SHA256: 1d403d11e45a5d05547ac32e8439992606ef2abc1d9550ead40f002d6dba14ff SHA1: 7ab2a574969ba070fe840595ae9ba6331e89e15e MD5sum: d29feeab68e19fed325a6b2d25338677 Description: Modular toolkit for Data Processing Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. Package: python-mlpy Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 428 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mlpy-lib (>= 2.2.0~dfsg1-1~squeeze.nd1) Suggests: python-mvpa Provides: python2.5-mlpy, python2.6-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 58266 SHA256: 77f4b8e2129db61e00feaad3c1460a923975820c91e625dc4fff605039f14c7a SHA1: 878fa1b9c71726e276b82d462006a5a90c127ea6 MD5sum: 69d292f9dfb2f666d6a3542ddbe60dd3 Description: high-performance Python package for predictive modeling mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . mlpy includes: SVM (Support Vector Machine), KNN (K Nearest Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression, Penalized, Diagonal Linear Discriminant Analysis) for classification and feature weighting, I-RELIEF, DWT and FSSun for feature weighting, *RFE (Recursive Feature Elimination) and RFS (Recursive Forward Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated, Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time Warping), Hierarchical Clustering, k-medoids, Resampling Methods, Metric Functions, Canberra indicators. Python-Version: 2.5, 2.6 Package: python-mlpy-doc Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1136 Depends: libjs-jquery Suggests: python-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: doc Filename: pool/main/m/mlpy/python-mlpy-doc_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 480866 SHA256: a1a158d0318129c2b6ac767cf0385b266a45aeaa6a06a45fc5bf61d6a77ff9b5 SHA1: 0de7a2884bfd8de60215558a742d138d0d35f167 MD5sum: 676b76390bb77f41f7a1ee949b11e212 Description: documention and examples for mlpy mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . This package provides user documentation for mlpy in various formats (HTML, PDF). Package: python-mlpy-lib Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 560 Depends: libc6 (>= 2.2.5), libgsl0ldbl (>= 1.9), python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mlpy-lib, python2.6-mlpy-lib Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy-lib_2.2.0~dfsg1-1~squeeze.nd1_amd64.deb Size: 139514 SHA256: 3647b82f5ebd3a2640f78d378d85e0be59934c5cf10d3e4e0a3c50a16af3ac57 SHA1: d44f8dec0b76d874cbdd5961b229f1789348796c MD5sum: 408f7cae4996611b999d4606d1d91e2f Description: low-level implementations and bindings for mlpy This is an add-on package for the mlpy providing compiled core functionality. Python-Version: 2.5, 2.6 Package: python-mvpa Source: pymvpa Version: 0.4.5-1~nd60+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~nd60+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.5-1~nd60+1_all.deb Size: 2167528 SHA256: 1a5846d7192053a4044629d90f741bff0d8097d295d2b4ac6a1ee50776e2be77 SHA1: 4e62d6202110deef7202355c0a002a31b3e0bc9c MD5sum: fe1f077da5c87b78233630490ada0912 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41020 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~nd60+1_all.deb Size: 9040710 SHA256: 2091efc201fb90c99fc09229ef6792cff9a2a9631a7102303625926573a5ca4c SHA1: 21c979e1aa0113e09c3576ddb89cf33ad715e22e MD5sum: 71cbbf55cb8baa1d956ad6a21a6206b3 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~nd60+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~nd60+1_amd64.deb Size: 70014 SHA256: 886dbc3eeb65d716d7e2ded52d213f0f02cb06045c3317b49a9d1370f35d0974 SHA1: 269a1ae2c745a824f971d78807a0a3b81eaffe3c MD5sum: 84ea8d4f5c5a86c9c45beb4f98de18b9 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~nd60+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~nd60+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~nd60+1_all.deb Size: 2284176 SHA256: 3cb4c9508927a5bf1035af9514777b681f7054e4e76d6752c15b6333722c1bdc SHA1: a464b3ee095bd0b8fb246aa63fcf4654dee7fa97 MD5sum: 8f99826107e3c6e29f67010aba894d8d 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~nd60+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), libsvm2, 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~nd60+1_amd64.deb Size: 60320 SHA256: 455f14b94e60d06c3bc9ce812987a8892f6eed9d8dd74e3109e1400356f676b5 SHA1: 5fed91f9f72eb424012e646ed1976932761a3736 MD5sum: 33d2b066e5365387e9608bc6c69e47b6 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-networkx Version: 1.0.1-0.1~squeeze.nd1 Architecture: all Maintainer: Cyril Brulebois Installed-Size: 1980 Depends: python (>= 2.4), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: https://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.0.1-0.1~squeeze.nd1_all.deb Size: 537842 SHA256: 0bed24d1ae233d484992277c1fe58619219db67e87bac47de4fc473273176410 SHA1: 980c0931aeac54c6e394c703d1df2ea1e707c551 MD5sum: cf2df0438a30f01ce5280ba618df0c82 Description: tool to manipulate and study more than complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph we mean a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network we usually mean a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-nibabel Source: nibabel Version: 1.0.0-1~nd60+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~nd60+1_all.deb Size: 1061220 SHA256: a09c40cf98009fc60a10ef173895241402566d4acc7aa10d5a071955ab990c38 SHA1: 26611832b51d3faa0cd450fd0f0f828d2bcce188 MD5sum: e96ca394ef8d5b61d9eb5d8658f27379 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~nd60+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~nd60+1_all.deb Size: 404004 SHA256: a73a38a18037c63da57c2e20c65ebd25a9a672e0164c327d4e2009bb688443ed SHA1: 20d3a9b5ccac7d710afd34fd8f318d9feb351333 MD5sum: 0723ce739df2a8a2a78ffe3875bdfb0e Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~squeeze.nd1_all.deb Size: 469788 SHA256: 88f8f2603bab6606985a137433460486b70e5765b08eba1ca81b8dccd3cfe96f SHA1: 12bd934e7cec2d24b9aec58fd66b592b9b4be485 MD5sum: feea254498444cc7f9827456091e83dc Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nifti Source: pynifti Version: 0.20100607.1-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1516 Depends: libc6 (>= 2.2.5), libnifti2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, libjs-jquery Provides: python2.5-nifti, python2.6-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-2~squeeze.nd1_amd64.deb Size: 366564 SHA256: fbf3f349e062fb5234040c95b198e3a4bd7bd2562a5242c0ab976a566b5e3a86 SHA1: 7f7c5ea466c51319f9e90cbc1bfc3ebd1a8daaee MD5sum: 59187c491607343e9b00615f3382b1cd Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.5, 2.6 Package: python-nipy Source: nipy Version: 0.1.2+20110114-1~nd60+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~nd60+1) Recommends: python-matplotlib, mayavi2 Suggests: python-mvpa Provides: python2.5-nipy, python2.6-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.1.2+20110114-1~nd60+1_all.deb Size: 1165306 SHA256: 8f463c681472d3799d8eea21f6e3c368c5cd6b433d26cc8613167cafcf645e42 SHA1: 31d61e80aae514db18c1758df17d27edb6c86631 MD5sum: e423f5320094336d7f16bc1f43cf70ac 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11344 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~nd60+1_all.deb Size: 2837856 SHA256: 80daf0d75c71dd7a4183c32edaf674d991ad339d802d60cef5142577448700bd SHA1: 0586468c0b616e667f307be936b19323369b5689 MD5sum: e38e6b678771d4539d7c3eda8952d4a8 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~nd60+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~nd60+1_amd64.deb Size: 1230152 SHA256: 27692f77fa54564e1fffb5a8e3fcb5a6f4fd508a56fa3c5ddebb9fea2df5d919 SHA1: 685191e65318ecd1804ca7223e341399a1fe04f1 MD5sum: 00a1443a85b324292158ddd9e5f78c79 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~nd60+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~nd60+1) Provides: python2.5-nipy-lib-dbg, python2.6-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.1.2+20110114-1~nd60+1_amd64.deb Size: 1352092 SHA256: 9ea248b3c8eb22bf6e2a5cd0790ed86f57509817b762966371d756e313e2d153 SHA1: ff0fab59528c52ab08d39870539cd185608c1704 MD5sum: b841cfa9b320ab7a0bdabfde2918926e 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~squeeze.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~squeeze.nd1_all.deb Size: 277528 SHA256: c9f658b7045c47f30bcd1c4c1003dc84d177e5cc973e08e8ad828dec772369b0 SHA1: 62aebb706464818ddca13f1edf064820fc0f4088 MD5sum: 14644333145064a6db9f43cd16b3c14a 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~squeeze.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~squeeze.nd1_all.deb Size: 840654 SHA256: 3c415531033955e31045f2db2f1edfd51dc65ccb1ce51dae7ced1899625d79a6 SHA1: 1262afc30d40e8b74698fbdffa6e0b6d1f8a0537 MD5sum: 8a1e7f0cc079faf07940c344e85d63e0 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~nd60+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~nd60+1_all.deb Size: 312908 SHA256: d79eee41d0925a32d7c503257d11aa6029bbc7e429e2c8e107a4f209a33f01d9 SHA1: f0e85ee73bc481212c1f11e6ba28ae1afb680d6e MD5sum: eb0b1caba41f6f1411a4b52e3203f87a 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4008 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~nd60+1_all.deb Size: 2570546 SHA256: 6caa0aeec593316f8a2a01f1e6d15772123199dfef02bff74679ef1458edacc1 SHA1: e83d2e8a93433fdd7eb58dea9b67538aecb551c1 MD5sum: e9ed5bf1cae29a21cb7cc6ff1c3eeff7 Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 600 Depends: libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-2~squeeze.nd1_amd64.deb Size: 162886 SHA256: 527803c4a9f4f871ae020d5a0c350d27b8aa36be9c9e31c7fc9ec57c43054e5a SHA1: 33de86df948aafe2fb11be5802a7d18d0691cfe1 MD5sum: 8f366487f4712de474cc664c4c0fd522 Description: Python bindings for openmeeg library OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides Python bindings for OpenMEEG library. Python-Version: 2.6 Package: python-openpyxl Source: openpyxl Version: 1.1.0-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 448 Depends: python, python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.1.0-1~squeeze.nd1_all.deb Size: 49184 SHA256: 7edf6c44f034197891e558f2dbe31136fbc4aa7f81257afea99d286d14729d88 SHA1: 913e4bee3b1f7bbfa4836583ceeba683da382cf0 MD5sum: c2217c8d63f12b262b1af9e1424d8fe2 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pyepl Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 2404 Depends: python (<< 2.7), python (>= 2.5), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~squeeze.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.18), libc6 (>= 2.3.2), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0, libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.5-pyepl, python2.6-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0-3~squeeze.nd1_amd64.deb Size: 602514 SHA256: b48eba7dd53f1093633ed4408c7a7ac86c65184f387d470dd631de3b4e6c8cea SHA1: 8e96378a486a819a29d5de22ff50c654a210eb8c MD5sum: d4932c3c0a0259905e0ce9e6eacfd0e0 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Python-Version: 2.5, 2.6 Package: python-pyepl-common Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 852 Depends: python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0-3~squeeze.nd1_all.deb Size: 817820 SHA256: 575a264fe983d8b7d0ad9eaac6baae7c46308bfea1a454dd466636f7cd9b60da SHA1: 219e559bf4ac39efbc3f0e375cf3ea8849d1d224 MD5sum: b3492c37881b41822afe7760f1b3cc5a Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4356 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.5-pyglet, python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd60+1_all.deb Size: 972196 SHA256: 91b6b5b43bba43c419bc93e875ebba6ac09733899d7d34e944a5df43c3a33a6c SHA1: d9cb126e2761a5bd4b56f73542eac4dadea3f185 MD5sum: e3b5a0fd56d17deacf83460ebcea6737 Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-pyoptical Source: pyoptical Version: 0.2-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~squeeze.nd1_all.deb Size: 6956 SHA256: 66717fa53f6d283a3a697f969f32bc1c15f1467bbc26bb09ffceba7beb871644 SHA1: 3201dafeb370ade84db53fbe0ce85c1a0e57455c MD5sum: cf68976930753cdd2fde4b74529ba1b6 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~squeeze.nd1_all.deb Size: 119516 SHA256: 1adaffa1132d6581ae599f8781f656a482fb586ecdaa789ab235068043a7f85f SHA1: bd3b2114258a93dbd1108eaea341f8541ff74a47 MD5sum: 1f942f44319f70c9cc3afcaac2e70796 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-scikits-learn Source: scikit-learn Version: 0.6.0.dfsg-1~nd60+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~nd60+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.5-scikits-learn, python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.6.0.dfsg-1~nd60+1_all.deb Size: 254824 SHA256: 51c4f9e531f9a092c8642daf951c9e6409ffdc34ef1c24ac7e932a13d7dd6ff3 SHA1: cc47a480fdb597a4561f35ab2c6438fd70f0fde1 MD5sum: 3da6e9cc2b5fd98561934a4b7b926246 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~nd60+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~nd60+1_all.deb Size: 4457280 SHA256: 25fa76b8d9e26683f50ca3bddca4beed31ed8c0225c9cea6dff2932360b0ec02 SHA1: c033f933ef759bfcb46c95be1de195a6d881b57f MD5sum: 156a3cbfcb877302d173a2715412bfaf 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~nd60+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~nd60+1_amd64.deb Size: 912610 SHA256: 5de9d8ef992d28f5098ec3fe2c14bbe0d4314063e93612e2559f5f5c3eb5519d SHA1: 8992d2b38039e51f3df18d18d02f5fed0a306df1 MD5sum: edd7ffc7125d6cecc4cce04f37eda08b Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-sphinx Source: sphinx Version: 1.0.1-1~nd60+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~nd60+1_all.deb Size: 1233510 SHA256: 0edc593f216f6b662d2a853e0f9b0bdc112ad1924ef2bc71ff44b284e3198e6b SHA1: 2727e77c2cdbbf4a4bdf57adcc5712669c0c7a2e MD5sum: 7d408c4e28ec1fbdda2ab2b75a789a92 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~nd60+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9268 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-imaging, python-ctypes, ipython Homepage: http://code.google.com/p/sympy/ Priority: optional Section: python Filename: pool/main/s/sympy/python-sympy_0.6.7-1.1~nd60+1_all.deb Size: 1696348 SHA256: 90437808b931d5eb683327ab48a3ca8e81092be6f14d7f9cdf3f1fd8c8e6381d SHA1: 8ff9042d8752320997021155b1d7ee3620d11545 MD5sum: 38368c397ca1f942608ee78c4d6f1a8f Description: Computer Algebra System (CAS) in Python SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. Package: qlandkarte Source: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 32 Depends: qlandkartegt Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkarte_0.16.0-1~squeeze.nd1_all.deb Size: 2600 SHA256: 971cfe8965e2ac770ab91d1ff374cd8a75c9c59d21a4a3a6c2fec65f0aa36f27 SHA1: 94b85cfadc8414252933de2d0bab789f82ea1161 MD5sum: 461d6da351ea7fcd3dbffa8c5a5bfcf3 Description: Transitional package for QLandkarteGT This is a transitional package for the QLandkarte to QLandkarteGT upgrade, and can be safely removed after the installation is complete. Package: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 4936 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdal1-1.6.0, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libproj0, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libx11-6 Recommends: gdal-bin, qlandkartegt-garmin Replaces: qlandkarte Provides: qlandkarte Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkartegt_0.16.0-1~squeeze.nd1_amd64.deb Size: 2725310 SHA256: 66584656de7506b2ab1ce6ea74e8521aa5b7161477409e903939f8cb60c5c939 SHA1: 0eb2186d67c5db133ff959044148d3e30468856b MD5sum: 5adb9290b742bb724bc79cca7b665a2a Description: GPS mapping (GeoTiff and vector) and GPSr management This package provides a versatile tool for GPS maps in GeoTiff format as well as Garmin's img vector map format. QLandkarteGT is the successor of QLandkarte. Among various improvements (e.g. 2D/3D map rendering and reduced resource demands) the major difference is its device-independent architecture, which is not limited to Garmin devices anymore. Therefore, the package also does not include device drivers. Drivers for a number of Garmin devices are available from the qlandkartegt-garmin package. . Additionally, QLandkarteGT serves as a frontend to the GDAL tools, to make georeferencing of scanned maps feasible for users. In contrast to similar tools (e.g. QGis) its straightforward interface is especially suited for non-scientific users. Package: qlandkartegt-garmin Source: garmindev Version: 0.3.0-1~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 532 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libusb-0.1-4 (>= 2:0.1.12) Homepage: http://www.qlandkarte.org Priority: optional Section: utils Filename: pool/main/g/garmindev/qlandkartegt-garmin_0.3.0-1~squeeze.nd1_amd64.deb Size: 176124 SHA256: 0e7889268a8b9d610d85045c31806e813f7474c7dbfa59f095d95b5c742d3587 SHA1: b24b383073c7824c5823bb8b21d687cdb94e955b MD5sum: 9dbf981042c5f4af1be1e5adad880cf1 Description: QLandkarteGT plugins to access Garmin devices A collection of plugins for QLandkarteGT to talk to various Garmin GPS devices, including GPSMap60CSx, GPSMap76, eTrexH, eTrexLegend and similar GPSr. Package: sigviewer Version: 0.5.0-1~nd60+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~nd60+1_amd64.deb Size: 450796 SHA256: b6b113255e51336ba0e27e29a23c197318391fb470bd0149bfd32c6af322d56f SHA1: 203cd9e33608552370ff1edb74328049c020ed3b MD5sum: 34787052b28da544c27abaa94c0c85ef 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: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: amd64 Maintainer: Debian Science Team Installed-Size: 122560 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1), libc6 (>= 2.3), libcurl3 (>= 7.16.2-1), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libgl1-mesa-glx | libgl1, libinsighttoolkit3.16, libkwwidgets1.0.0908, libopenigtlink1, libstdc++6 (>= 4.1.1), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, slicer-data, itcl3, iwidgets4, tcllib, tcl8.5-kwwidgets Homepage: http://www.slicer.org/ Priority: optional Section: graphics Filename: pool/main/s/slicer/slicer_3.4.0~svn10438-3~squeeze.nd1_amd64.deb Size: 25430684 SHA256: 7c47578ed0936d7bd34dd0a01f93390d083e60886cbc32cf44bbc562d6347851 SHA1: 8cf5a31b640435e6776918f7884ffa2820d983c8 MD5sum: 1c8867846dab10523045eb035b8d70eb Description: software package for visualization and image analysis - main application Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer main application. Package: slicer-data Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: all Maintainer: Debian Science Team Installed-Size: 75656 Depends: tk8.5 | wish Homepage: http://www.slicer.org/ Priority: optional Section: doc Filename: pool/main/s/slicer/slicer-data_3.4.0~svn10438-3~squeeze.nd1_all.deb Size: 45850452 SHA256: c5a750d8b5ae619e7676d13bc9f8975e081771cfe9b6d534b000b54968903d3f SHA1: 34f83bdb09471100da1c6ea84b67a6064bf20708 MD5sum: 7470a7eb5cb992fb85799cd88960ff69 Description: software package for visualization and image analysis - share Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer data files. Package: spm8-common Source: spm8 Version: 8.4010~dfsg.1-4~nd60+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~nd60+1_all.deb Size: 10087122 SHA256: 91d4717f99fb2ade32c94d961922a58dad4631a38fc086d746b94eb072eeaf11 SHA1: f2da0fbfa6c0536a699089e7f22ee6554e8c4696 MD5sum: 6b2ee2b58abcafc5e2a4b56523c956bb 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~nd60+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~nd60+1_all.deb Size: 52168452 SHA256: 998be0e0a03cab691fabf0c1edf9fe5da1de2260f5d55381863779187faf566a SHA1: b31b4b995286ea7f28ba8d39c6b51403edbd255f MD5sum: 9dde1a7ab736fcafb6054d6480f29ae0 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~nd60+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~nd60+1_all.deb Size: 10423798 SHA256: 61f4b7c87d78d668c04fcdd8c175533b68d7873240b33ce274c9945a03b69f10 SHA1: 92edc359d3e39d886830f50e0776dfc9118d1f97 MD5sum: 8f3f2f55256977deb4e606b8da2edd6a 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: via-bin Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 908 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia0, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/via-bin_1.6.0-2~squeeze.nd1_amd64.deb Size: 189026 SHA256: 694ff7ad7867e4b405ddb913418efae3ef785aa57cb8fc942cd435a14cc5777b SHA1: 618f19b1209f68a4d68293902e2e5b8863459a08 MD5sum: 4a5e635a865ae3d6a80fa0d59963e070 Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: voxbo Version: 1.8.5~svn1241-1~nd60+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~nd60+1_amd64.deb Size: 3697904 SHA256: ec81eb8d7d7284509468f9a2917b512d229d32771abdaa3d4f4a060435f809a2 SHA1: 799853126d4be0c65e858cd8fe0a5c3a3ea23a9b MD5sum: 385b07b2fd21a864e5b7718cc92ec47b 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.