Package: biosig-tools Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 13820 SHA256: 0ff2c17b42a59193774b5a476563ba374fdc2a8ed50d95414e2bf0fa91b6fe72 SHA1: f3a7dc754a6923831a971bc8808171c6f40b736a MD5sum: 7be85a6a2c3b4133c5ea28792023987b Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: freenect Source: libfreenect Version: 1:0.0.1+20101211+2-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 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+2-1~nd11.04+1_amd64.deb Size: 2542 SHA256: 84f7b44858e7bed740e40bbe1aea08b52d18baae2b529b6a8c98dd2ac97722e2 SHA1: 4b884dff4a26dd01bb44f090e9cb6fc8ed876519 MD5sum: 328ee0b20ef6eeff20761161f021b879 Description: library for accessing Kinect USB camera -- meta package libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This is the meta package to install all components of the project. Package: gdf-tools Source: libgdf Version: 0.1.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.1-1~nd11.04+1_amd64.deb Size: 41594 SHA256: 867e6deb6e588548668115d6e3be811e52526968f16f03808e91323b0b94782c SHA1: 98737092d002998651d4600e8e64cf20ac06c3f3 MD5sum: 134f9656178d832de7bf27289fd0e74d 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: klustakwik Version: 2.0.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd11.04+1_amd64.deb Size: 22946 SHA256: 7b1c678e143a7244aedff53ca5064d8b6113ad4bd6c2c71232272474c96204c7 SHA1: b20487c1e162725ee846d1d9ebf2ebb2e8727e06 MD5sum: 83b91d26ee9a956103127078090401a0 Description: automatic sorting of the samples (spikes) into clusters KlustaKwik is a program for automatic clustering of continuous data into a mixture of Gaussians. The program was originally developed for sorting of neuronal action potentials, but can be applied to any sort of data. Package: libbiosig-dev Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1604 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd11.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 391474 SHA256: 3f19f1e667cec394dd7fe337e2d6de002cfad2f53f03590331e4622db053efe7 SHA1: 55b75908cb9c9c1b34209e0ae1b736b6c0a8428f MD5sum: 632f8674cd89d2738dd9e3307230b40f Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig0 Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 880 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 309408 SHA256: 7ebbf2a0fea0cd938702538d19d65f8c84abdf9a6cdfc89c6e66b8fdb6967118 SHA1: 1d9c94a1e5d42de635a12d80a0775e5a5e858a2d MD5sum: 3fde135092a7e5fa19b057df7dee58a2 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig0-dbg Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 240 Depends: neurodebian-popularity-contest, libbiosig0 (= 0.96.3+svn2677-1~nd11.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 69618 SHA256: e538ba7febcb07a03d109549682295e03eeb6e634bbfc4899e53ccfc61d01b87 SHA1: 98d10c152bebd870d24d8bad25ad79373e7b6a96 MD5sum: 3240d0746ac767de4642587801edebc3 Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libfreenect-demos Source: libfreenect Version: 1:0.0.1+20101211+2-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 92 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.3.4), 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+2-1~nd11.04+1_amd64.deb Size: 25080 SHA256: c8f18833fa2f86940ebaabdd1532ce4c88d89654bf4ee9ac5b003c16fdef2e44 SHA1: 605d8b9b5b1fe9abce14f1ee0a19ee673f3b08a2 MD5sum: 258696c4dfdebc9efd3694e30ae0a564 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+2-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libusb-1.0-0-dev, libfreenect0.0 (= 1:0.0.1+20101211+2-1~nd11.04+1) Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.0.1+20101211+2-1~nd11.04+1_amd64.deb Size: 18582 SHA256: a0c560d8e7dbfca860afdf2e81a7887d05b9f739e992603b9671a0a5a9f90d24 SHA1: f53c655ac47939b89babe7e1f13f043a2324488a MD5sum: d984b2fd002fd2c39ec5d0e90ffbf2d4 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+2-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 96 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+2-1~nd11.04+1_amd64.deb Size: 27874 SHA256: 090513dbcda4fb282463f7a9f2b8c0c358991e5c4af5d8413437a288a1966838 SHA1: 4c9806ecee5be39dbd18ae6fba46bb59de86e634 MD5sum: 6067e3772aa5dc3c811b4095467ac6da Description: library for accessing Kinect USB camera libfreenect is the core library for accessing the Microsoft Kinect USB camera. Currently, the library supports access to: - RGB and Depth Images - Motors - Accelerometer - LED Package: libgdf-dev Source: libgdf Version: 0.1.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd11.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.1-1~nd11.04+1_amd64.deb Size: 18538 SHA256: c23e932e513adeac57badc00d8a1313467c4d9396b948655bd673e38d9aa4a0e SHA1: 41252235face22f096eb5d94a9fd3835b53cbc62 MD5sum: 73a53868b3cb67298dc105d41832bfaa Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.5) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.1-1~nd11.04+1_amd64.deb Size: 103624 SHA256: b28cdc12327f9f5a04fef6ba973cbd4e1eac44d89ff34f62b724b538a4332738 SHA1: 3c806d811ef44dcb071d445a699b20d8a3afbb27 MD5sum: 75dcc4b4afbc3d4c56e5d93d5c8155df Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5428 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.1-1~nd11.04+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.1-1~nd11.04+1_amd64.deb Size: 1380036 SHA256: 54c41ae587b88ed81ed90f1d327b8605727cf262eed5bcaa48f20b27dc68f07b SHA1: a6dbdab5963b4236b4e65cb64745120d078cdcd0 MD5sum: 98161f98b7c726c5df76e37c1fa74521 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: matlab-support-dev Source: matlab-support Version: 0.0.14~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.14~nd11.04+1_all.deb Size: 5526 SHA256: 0a5ec0e12050643a178bcc67f1600ab95f9152334d8be9d108f1595dec9c6ea6 SHA1: 0783bda9456ea8e9d39e8a9a7e7ff01739325767 MD5sum: f8a2f0790b01d312f21be0c60cb75c54 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: neurodebian-desktop Source: neurodebian Version: 0.25~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 268 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.25~nd11.04+1_all.deb Size: 113490 SHA256: 609f84f5dc2a84de0076f450ec2c6bda54fcf218806d1fdd004c3050d2336015 SHA1: 50dc0a47979ba27e7f7fb9f0c3b949db644ebc0d MD5sum: bfdbd6af4eb8ce27748b1ee0f433a36c Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.25~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4408 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree, moreutils Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.25~nd11.04+1_all.deb Size: 3845794 SHA256: b583641c2059cc1389dc2362f68708cfabf5983bd6dbce00b1a0eb89495585b5 SHA1: aae1004c90da8edcbc5fe44ca3f4bd712abf5948 MD5sum: d4a447fbe20620f4e2ce34410345f41d Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.25~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.25~nd11.04+1_all.deb Size: 12814 SHA256: 024a912ba0aca83868b78876e24b127402518011a055a9959db5e6beef6670d3 SHA1: 01a21fbd086d8e8bc7b5791c47cc2f9437d08fed MD5sum: 649a3940d7fa97c7e26ec5380ceb3da7 Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.25~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.25~nd11.04+1_all.deb Size: 5866 SHA256: 0ddb751895ba9cdf611ca39fc1d78af9b6f423e38e7e0a082da2d69ec8f26008 SHA1: a698da617644d3097b690f1f550fc0cfe82a7d39 MD5sum: dddda8b231155a3aa2e9d2e784d840eb Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.25~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.25~nd11.04+1_all.deb Size: 5020 SHA256: e3283c840c520b6c11c41519f2bba0bf1e062bf2c9417c2c1efef9a102432356 SHA1: f1357adf59c11ea3181842b7cb1064d5d68e5379 MD5sum: 803d47fb1de800be22a9efa634b6b92a Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: octave-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Depends: neurodebian-popularity-contest, libbiosig0, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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 (>= 5.5-5~), libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 17918 SHA256: 34ef3971d43361b3f8b2ffb863a216537243b1cd13cec4fb3dfebf4686c32c5f SHA1: 5d4c8b2b221f1859dbb156519ba396cfbc2a2470 MD5sum: c954df00099a1c7371b77d6b2a3b8b93 Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.1-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 288 Depends: neurodebian-popularity-contest, octave3.2 (>= 3.2.4), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.1-1~nd11.04+1_amd64.deb Size: 116976 SHA256: 6da7a993a5f9de01ac477ae81d0cba1addaa365a562cc164b88d326eba933a1c SHA1: 3185a8012ce6c636521ed918662a3f53af963878 MD5sum: 0f45a86114fded6f2840b941f5439919 Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. Package: python-biosig Source: biosig4c++ Version: 0.96.3+svn2677-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 224 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libbiosig0, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.96.3+svn2677-1~nd11.04+1_amd64.deb Size: 52818 SHA256: 32491caa8ddf652124b486d9403758b8e7f50e5c7533d5ceeb36a5c973d7f64c SHA1: a747a4e4a493cdc9939171ccd023eecb227077da MD5sum: 814be39bc6ba592d07481e3c98ab00f0 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-cfflib Source: cfflib Version: 2.0.5-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 768 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-numpy, python-networkx (>= 1.4), python-nibabel (>= 1.1.0) Recommends: python-nose, python-sphinx, python-tables, python-h5py Provides: python2.6-cfflib, python2.7-cfflib Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd11.04+1_all.deb Size: 217710 SHA256: f43ce8ebf52ffc74d10c86f356c53d6bdbf60d8ac8afdc330c789831b212b8d2 SHA1: c8b78aac188af4bb0a489bd6af44e00aad07af59 MD5sum: 6c16047dfeecab6c850d99dd75191b8b Description: Multi-modal connectome and metadata management and integration The Connectome File Format Library (cfflib) is a Python module for multi-modal neuroimaging connectome data and metadata management and integration. . It enables single subject and multi-subject data integration for a variety of modalities, such as networks, surfaces, volumes, fiber tracks, timeseries, scripts, arbitrary data objects such as homogeneous arrays or CSV/JSON files. It relies on existing Python modules and the standard library for basic data I/O, and adds a layer of metadata annotation as tags or with structured properties to individual data objects. Package: python-freenect Source: libfreenect Version: 1:0.0.1+20101211+2-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), 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+2-1~nd11.04+1_amd64.deb Size: 33238 SHA256: 8f05f3127f7fad3c654902d449582bd2b7d0d7dd3a991283f4e48d9609bc9f73 SHA1: e54f4f3aadea632f4b39bf70b5bbb5230df3b94f MD5sum: 00ba9829c64d687ef238bbc442bac9d9 Description: library for accessing Kinect USB camera -- Python bindings libfreenect is the core library for accessing the Microsoft Kinect USB camera. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-joblib Source: joblib Version: 0.5.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.5.1-1~nd11.04+1_all.deb Size: 44188 SHA256: 31f84c7be667044d3a46c72f13042efcd75fedaea4652fa07da268c1abd806e1 SHA1: 0ee0100b6ba7355c21b4043e2182047eda7a69cf MD5sum: 668c3aa1b87b0fd0f257dbd5f3a74bbb 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-networkx Version: 1.4-2~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: http://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.4-2~nd11.04+1_all.deb Size: 647290 SHA256: 46af0162d46d69b38d76984d10577b337ec8cbeb61b064ebca55500dd92ffd1c SHA1: eb58edd4c3c571c35d6a796e0d6c547be617d113 MD5sum: 721176531d2dc53a9eeb81d80861ffcc Description: tool to create, manipulate and study complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-networkx-doc Source: python-networkx Version: 1.4-2~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15812 Depends: neurodebian-popularity-contest Homepage: http://networkx.lanl.gov/ Priority: optional Section: doc Filename: pool/main/p/python-networkx/python-networkx-doc_1.4-2~nd11.04+1_all.deb Size: 6229030 SHA256: 3f9a60dbe16c43365090f53f01ecabb8de486a1c785e8d57e547e606111a4636 SHA1: 5f4e62733f3342daf0a873ea56dac67bbdd5b121 MD5sum: d721409534a58309f5f63c1bedeb1371 Description: tool to create, manipulate and study complex networks - documentation NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains documentation for NetworkX. Package: python-nibabel Source: nibabel Version: 1.1.0-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3608 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.6-nibabel, python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.1.0-1~nd11.04+1_all.deb Size: 1665814 SHA256: 634a9433263713d05172cc51911e48e6618840b4d39d1825e12330b4c93fab33 SHA1: 613177876f214ce3472783355072cca467927204 MD5sum: fc7082234d76848b6d934ea3a61b32d2 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.6, 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.1.0-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2736 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.1.0-1~nd11.04+1_all.deb Size: 404626 SHA256: 6312bef49e81bfa61b3e87a7e31f54c26039f705216667f2b4e506fabbe755f6 SHA1: ef837b8232c7835b69c1ae7401dbb13b9abab005 MD5sum: 40f31d2eaaeb0440bceb41627a05f96d 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-scikits-learn Source: scikit-learn Version: 0.8.0.dfsg-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1424 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-scikits-learn-lib (>= 0.8.0.dfsg-1~nd11.04+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.6-scikits-learn, python2.7-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.8.0.dfsg-1~nd11.04+1_all.deb Size: 310654 SHA256: 2ef6428fa0df4a2214cd420825916873ce9e92a6be15195f9b27c8e9f2e60336 SHA1: d03c7363a71a7ed94d8718b0026068aa343b4e16 MD5sum: 9f01f128df100309eea3e0bd5283c246 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.6, 2.7 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.8.0.dfsg-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14596 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-scikits-learn-doc_0.8.0.dfsg-1~nd11.04+1_all.deb Size: 9035582 SHA256: 70807213412dfd306fe177b7361bb8db200f795ceb4de212d557a3a4d3b0c81e SHA1: c3d47eb8beca1b0a15b4c37039c206faf18df676 MD5sum: e81600f40199af79a9e3c48426c556e0 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikits-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.8.0.dfsg-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2720 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), python (<< 2.8), python (>= 2.6), python-numpy (<< 1:1.6), python-numpy (>= 1:1.5.1), python-support (>= 0.90.0) Provides: python2.6-scikits-learn-lib, python2.7-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.8.0.dfsg-1~nd11.04+1_amd64.deb Size: 1030384 SHA256: f83d6eda800ac595f92bed3db1d0aeeabf693462e6a0fe5208abcd9f9dbb215c SHA1: a559c3753be35520db7f05a32ec5490f5b1765c9 MD5sum: e44cf17e498f1fdadfc29ba3f1de118a Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.6, 2.7 Package: sigviewer Version: 0.5.1+svn556-1~nd11.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 992 Depends: neurodebian-popularity-contest, libbiosig0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.5) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-1~nd11.04+1_amd64.deb Size: 422992 SHA256: 504147e2c6535a690bc9325c990db0590f39098009da63d7065043e125810318 SHA1: 0f5e2da422edbbe0ad83186e77699eaa551355eb MD5sum: 064ff4751aa19d285d8e251e249cc3e1 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: spm8-common Source: spm8 Version: 8.4290~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22192 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4290~dfsg.1-1~nd11.04+1_all.deb Size: 10547232 SHA256: 311aef085f7e4020abe98273e633d85d054b79eeec6b20638906c766424d10f1 SHA1: 94df1ab77472264814457881c5af62927f308821 MD5sum: 197fd2735629c7274ea3783181fc9bdc Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4290~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73084 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4290~dfsg.1-1~nd11.04+1_all.deb Size: 52167568 SHA256: de99254176288f13c810031edd9076d7144137fcf2a47188bb847a35a7d70158 SHA1: 8e92a60804c5cc98514fae95e12f45c7dd6f688a MD5sum: 2b5e078263f961028a278528d21aa864 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4290~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9380 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4290~dfsg.1-1~nd11.04+1_all.deb Size: 8648816 SHA256: 1246975b745587320cfa229ea7b4475a5133e9ecbbb472d6fa6b08468d7e0554 SHA1: 7ed14c87012cef9a2d7371c45ee738e6590940b3 MD5sum: a6b73e1f5d718a59ef15d3604e3af435 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).