Package: arno-iptables-firewall Version: 1.9.2.k-3~jaunty.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~jaunty.nd1_all.deb Size: 132484 SHA256: 51eba5d1e08a7426efc4a4ca1f3a3afa792baa92eaea989414b53b42d1e57c1d SHA1: ef28a1aa6bb4747cca6c59fd8752b0cedf1c2666 MD5sum: 0782d32f4519d5ceb9d18f7e4d8c8419 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: biosig-tools Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 672 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsuitesparse-3.2.0 (>= 1:3.2.0), 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~nd09.04+1_amd64.deb Size: 255696 SHA256: 8de19a19a03a528044a5592cbf75291dc73dcccb92acd4ad7ff2a608abdd7d81 SHA1: 13a5463f66fb4b8fee489eee0922d540d09582ef MD5sum: 856d73d58b7e9612da28b507ca2b6162 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.1-1~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 18900 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libminc2-1, libqt4-assistant (>= 4.5.0~+rc1), libqt4-network (>= 4.5.0~+rc1), libqt4-opengl (>= 4.5.0~+rc1), libqt4-xml (>= 4.5.0~+rc1), libqtcore4 (>= 4.5.0~+rc1), libqtgui4 (>= 4.5.0~+rc1), libqwt5-qt4, libstdc++6 (>= 4.2.1), libvtk5, zlib1g (>= 1:1.1.4) 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.1-1~jaunty.nd1_amd64.deb Size: 7163464 SHA256: c656d55db12106c3cb0ef16261167fb9ec868aea374adc635a37cb5cb51f640b SHA1: a31939d0b1041cbbb30a6da4f41048a68386f98e MD5sum: 6df45db5a3b7204e529505b38b7955fe 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: cython Version: 0.13-1~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4924 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), libc6 (>= 2.4) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd09.04+1_amd64.deb Size: 1299290 SHA256: 21f363a3ab5ac162ac64870a0502aa73dd3c22550deff8f7291283672e161b2e SHA1: 566cca9fc7a4b0575cac4faa18fb35326a8b8ba5 MD5sum: 09ad8372e5919e7dde61ccca0bdf863c 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11800 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), libc6 (>= 2.4), cython (= 0.13-1~nd09.04+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd09.04+1_amd64.deb Size: 3730870 SHA256: 27215f2100ed0c035c267d255cd6bf118589348a5fa2257961c2963613ea3d77 SHA1: 5819c1ef46b258329903864652219c984b83b7d1 MD5sum: 9bfdc45bae45c243317daf5a1e4f4e2e 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: debhelper Version: 7.4.11~bpo50+1~jaunty.nd1 Architecture: all Maintainer: Joey Hess Installed-Size: 1360 Depends: perl, perl-base (>= 5.10), file (>= 3.23), dpkg-dev (>= 1.14.19), html2text, binutils, po-debconf, man-db (>= 2.5.1-1) Suggests: dh-make Conflicts: dpkg-cross (<< 1.18), python-central (<< 0.5.6), python-support (<< 0.5.3) Homepage: http://kitenet.net/~joey/code/debhelper/ Priority: optional Section: devel Filename: pool/main/d/debhelper/debhelper_7.4.11~bpo50+1~jaunty.nd1_all.deb Size: 463476 SHA256: ca82359d2a6dc0da2832bbffd787949f3fd245912133da8a2f59a4b43c45fb70 SHA1: 9f35edfdaac8b2ee5105e491aec838482e043825 MD5sum: 240c436a7891473f963cebe0c45f1728 Description: helper programs for debian/rules A collection of programs that can be used in a debian/rules file to automate common tasks related to building debian packages. Programs are included to install various files into your package, compress files, fix file permissions, integrate your package with the debian menu system, debconf, doc-base, etc. Most debian packages use debhelper as part of their build process. Package: dicomnifti Version: 2.28.14-2~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 528 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.2.1) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-2~jaunty.nd1_amd64.deb Size: 159522 SHA256: 397c66041bae98d6ea6ea773b2657499703a165d205904199c4d8f9c2337f6ff SHA1: f44d15a69ffd72d37b5ca6da6141bec2f4867e46 MD5sum: 78acb92395b1759d449a12b3789bb7c4 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: epydoc-doc Source: epydoc Version: 3.0.1-4~jaunty.nd1 Architecture: all Maintainer: Kenneth J. Pronovici Installed-Size: 15008 Recommends: iceweasel | www-browser Priority: optional Section: doc Filename: pool/main/e/epydoc/epydoc-doc_3.0.1-4~jaunty.nd1_all.deb Size: 1544776 SHA256: 51ee31a039129212fcdc7b80213e2566ccc3749cd849c00b07a5e8242ec0aa1e SHA1: 3ce8bb7727b5c9c52f90b40d9421f4c7034d6e79 MD5sum: c514e5964b7f5c7bc2190ce74c2391f6 Description: official documentation for the Epydoc package Epydoc is a tool for generating API documentation for Python modules based on their docstrings. A lightweight markup language called epytext can be used to format docstrings and to add information about specific fields, such as parameters and instance variables. Epydoc also understands docstrings written in ReStructuredText, Javadoc, and plaintext. . This package contains the API reference and usage information for Epydoc, all available through the Debian documentation system (dhelp, dwww, doc-central, etc.) in the Devel section. Package: fslview Version: 3.1.8+4.1.6-2~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4200 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8-b), libqwt4c2, libstdc++6 (>= 4.2.1), libvtk5, libvtk5-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~jaunty.nd1_amd64.deb Size: 1526106 SHA256: cef32d39d19604c949a28bceed477b69c69e83f14083fc324be573bd2b5b551b SHA1: 29c90ee2eaaff715a4fa50db2054b98ecb5b4a20 MD5sum: cc3e92caf6fb0a5b73ff6a3399298de4 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~jaunty.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~jaunty.nd1_all.deb Size: 2378978 SHA256: cea54623e73f095616697b6d2d005886f133fa76f9f7e68bead01bbe26cdbff7 SHA1: 403d46ade71b45711387b3f31f73bd17691c06ed MD5sum: 02d465e653537e608f059ad3dca2abcf Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gifti-bin Source: gifticlib Version: 1.0.9-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 128 Depends: libc6 (>= 2.3.4), libexpat1 (>= 1.95.8), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-1~jaunty.nd1_amd64.deb Size: 29288 SHA256: 5f762d467cdc820419bcdad588621a34f58ccb84c3b0db73b6711c6a3c739546 SHA1: 38a200ad9847eefb6bc7a29f169b18757f68452b MD5sum: 3d8c8ed830ff362e94062e51c362306b 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: hdf5-tools Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 1268 Depends: libc6 (>= 2.7), libhdf5-serial-1.8.3 | libhdf5-1.8.3, zlib1g (>= 1:1.1.4) Homepage: http://hdfgroup.org/HDF5/ Priority: optional Section: science Filename: pool/main/h/hdf5/hdf5-tools_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 408434 SHA256: f89fcebf7e9673f5a2a5c77a1c79809d4dd150d9c86239344f1b3a59ef6584b0 SHA1: b5c6b732b910251dec18b1c44a88f5f216e468ef MD5sum: 566e438b780c52d87df0539f35792511 Description: Hierarchical Data Format 5 (HDF5) - Runtime tools HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains runtime tools for HDF5. Package: kbibtex Version: 0.2.3-1~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 2796 Depends: kdelibs4c2a (>= 4:3.5.9), libc6 (>= 2.4), libqt3-mt (>= 3:3.3.8-b), 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~jaunty.nd1_amd64.deb Size: 796778 SHA256: a256627897df94f908ec979d8f045fa33e459d344487c5e4ec725170011994a7 SHA1: 94af1d24e7d1daedcfbb54d8f525b7667ede203c MD5sum: f34c885296e2939189871d339a62713b 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1636 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd09.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.2+svn2552-1~pre1~nd09.04+1_amd64.deb Size: 383478 SHA256: a8f2700c847a103cdd27040e198f9bc5d1ab72ea71acc3ba819c481d283f15fe SHA1: c375db35ccff4bdab824f801b493d40676864fec MD5sum: 8338dea620afd80a7a3b95267e889d77 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 908 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsuitesparse-3.2.0 (>= 1:3.2.0), 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~nd09.04+1_amd64.deb Size: 306010 SHA256: 4573938444ed0dede2261d57aaea10182b3663cee9110fbda688cff2031f0c51 SHA1: f746213609d54fd23272b7c02bb9416634126982 MD5sum: 79c61c7fa216957f2aae1dae1cc3d0e0 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 752 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd09.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.94.2+svn2552-1~pre1~nd09.04+1_amd64.deb Size: 176686 SHA256: 0e9c69e899d0fb4bf412b938d65d9f1e161052603597a237bf8cd6833c482e1e SHA1: e67a5d873cb2be6a44cd276bb3dcd81efed888cd MD5sum: 33192cb4607472b8ae4ea840a9add6a0 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: libgiftiio-dev Source: gifticlib Version: 1.0.9-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 260 Depends: libgiftiio0 (= 1.0.9-1~jaunty.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~jaunty.nd1_amd64.deb Size: 65498 SHA256: 28d4662cf03652daa1be3af7e27b8709df015453eb7e57b8c36c6c89a1553774 SHA1: 1c63b66b71325871714c9e5074a7160103c006cc MD5sum: 13ffce78e35f94c98038dc026c483e34 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~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 180 Depends: libc6 (>= 2.4), libexpat1 (>= 1.95.8), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-1~jaunty.nd1_amd64.deb Size: 58244 SHA256: f90f71efae7014dd15fe4e6da2f80a56878426392fd8b6bf8b0f6c32c76afdc2 SHA1: 526f16878de8f8a18661f7865d5ebac1d46ff9a8 MD5sum: bf5c0692eabdadedb983cce61a7bc1dc 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: libhdf5-doc Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: all Maintainer: Debian GIS Project Installed-Size: 188 Suggests: libhdf5-dev, www-browser, pdf-viewer, doc-base Homepage: http://hdfgroup.org/HDF5/ Priority: optional Section: doc Filename: pool/main/h/hdf5/libhdf5-doc_1.8.3-2.1~jaunty.nd1_all.deb Size: 77880 SHA256: ac8ac5ce85aff9fc91c006a35014c19f56518a2e729532e92e8fd69df8110753 SHA1: 4604cf2c032867c95d22089abb81414a56bb07ea MD5sum: 7580e5c4d6df96baa8c1706198ddc3ed Description: Hierarchical Data Format 5 (HDF5) - Documentation HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains documentation for HDF5. Package: libhdf5-lam-1.8.3 Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 4976 Depends: libc6 (>= 2.7), liblam4, zlib1g (>= 1:1.1.4) Conflicts: libhdf5-1.8.3 Provides: libhdf5-1.8.3 Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libs Filename: pool/main/h/hdf5/libhdf5-lam-1.8.3_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 1561702 SHA256: 7fb27e25250e11dcf4d3ee20453ff1ff5e6bbaaee2b8677fe34b71edc83b0af1 SHA1: 70a201e1284c02064fad901b22e52a1e464a6561 MD5sum: ba421d07c663b290c711b2e401f82da0 Description: Hierarchical Data Format 5 (HDF5) - runtime files - LAM version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains runtime files for use with LAM. Package: libhdf5-lam-dev Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 9904 Depends: libhdf5-lam-1.8.3 (= 1.8.3-2.1~jaunty.nd1), zlib1g-dev, libjpeg62-dev, lam4-dev Suggests: libhdf5-doc Conflicts: libhdf5-dev Provides: libhdf5-dev Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libdevel Filename: pool/main/h/hdf5/libhdf5-lam-dev_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 1830308 SHA256: 5f2ce07c7e1a398218b369d809cf9c0f3287549a64ee1807fba1f3ab341e64c2 SHA1: 8c8ad22ba54e8f7acce61243482df3967c004585 MD5sum: 4638d31db1f55ff18915664934ba8d80 Description: Hierarchical Data Format 5 (HDF5) - development files - LAM version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains development files for use with LAM. Package: libhdf5-mpich-1.8.3 Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 6204 Depends: libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), zlib1g (>= 1:1.1.4) Conflicts: libhdf5-1.8.3 Provides: libhdf5-1.8.3 Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libs Filename: pool/main/h/hdf5/libhdf5-mpich-1.8.3_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 2034994 SHA256: 4c517c4e37cd764efdb76c632fc4d1b503fe8b6b3cea9e554a71bbeb2d55ad59 SHA1: ce0e57fd1091bb053aafea2e3266ae0d1a02d173 MD5sum: 6f4685e16eb18ca285719497e60fad83 Description: Hierarchical Data Format 5 (HDF5) - runtime files - MPICH version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains runtime files for use with MPICH. Warning: the C++ interface is not provided for this version. Package: libhdf5-mpich-dev Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 18080 Depends: libhdf5-mpich-1.8.3 (= 1.8.3-2.1~jaunty.nd1), zlib1g-dev, libjpeg62-dev, libmpich1.0-dev Suggests: libhdf5-doc Conflicts: libhdf5-dev Provides: libhdf5-dev Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libdevel Filename: pool/main/h/hdf5/libhdf5-mpich-dev_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 2524936 SHA256: a03ec7e44115396cafa29f8d20b6e73ff445eacf336c0fcf63b790bb3ac48c3a SHA1: b6ca13a28975ce30b9adb4536de201e495d3377e MD5sum: 93c41fdcf37dda8d5ead96be94e05b07 Description: Hierarchical Data Format 5 (HDF5) - development files - MPICH version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains development files for use with MPICH. Warning: the C++ interface is not provided for this version. Package: libhdf5-openmpi-1.8.3 Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 5292 Depends: libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libopenmpi1, zlib1g (>= 1:1.1.4) Conflicts: libhdf5-1.8.3 Provides: libhdf5-1.8.3 Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libs Filename: pool/main/h/hdf5/libhdf5-openmpi-1.8.3_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 1644414 SHA256: cc7945a016b274435751dddec68c55caec6f08d527f47660e8805e99dfe6e22d SHA1: 1c1bb9376f161cec3a6d4a41177d83438ae8fb23 MD5sum: cdc21f735a28ebf57ecc9f83f8a98437 Description: Hierarchical Data Format 5 (HDF5) - runtime files - OpenMPI version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains runtime files for use with OpenMPI. Package: libhdf5-openmpi-dev Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 18080 Depends: libhdf5-openmpi-1.8.3 (= 1.8.3-2.1~jaunty.nd1), zlib1g-dev, libjpeg62-dev, libopenmpi-dev Suggests: libhdf5-doc Conflicts: libhdf5-dev Provides: libhdf5-dev Homepage: http://hdfgroup.org/HDF5/ Priority: extra Section: libdevel Filename: pool/main/h/hdf5/libhdf5-openmpi-dev_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 2525886 SHA256: ffef9438912095b4f6afc3c5e7ffd3428638ca1ef5f9b7de512cfa8a71593751 SHA1: 3aabbb13a1d26c7d0754fd906de9f982b0152ada MD5sum: 60cfc4a17cbb5b9ff7673293739f9362 Description: Hierarchical Data Format 5 (HDF5) - development files - OpenMPI version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains development files for use with OpenMPI. Package: libhdf5-serial-1.8.3 Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 5596 Depends: libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Conflicts: libhdf5-1.8.3 Provides: libhdf5-1.8.3 Homepage: http://hdfgroup.org/HDF5/ Priority: optional Section: libs Filename: pool/main/h/hdf5/libhdf5-serial-1.8.3_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 1741112 SHA256: 76116ab8291215b90f96bd06bc2bad9e345c4a21c1db3bc983ea200ebed70859 SHA1: cf0d84d81b9dccc5468e4094bac874ecac6641fb MD5sum: 2031318d3ce7a6140a53328caae86c67 Description: Hierarchical Data Format 5 (HDF5) - runtime files - serial version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains runtime files for serial platforms. Package: libhdf5-serial-dev Source: hdf5 Version: 1.8.3-2.1~jaunty.nd1 Architecture: amd64 Maintainer: Debian GIS Project Installed-Size: 18600 Depends: libhdf5-serial-1.8.3 (= 1.8.3-2.1~jaunty.nd1), zlib1g-dev, libjpeg-dev Suggests: libhdf5-doc Conflicts: libhdf5-dev Provides: libhdf5-dev Homepage: http://hdfgroup.org/HDF5/ Priority: optional Section: libdevel Filename: pool/main/h/hdf5/libhdf5-serial-dev_1.8.3-2.1~jaunty.nd1_amd64.deb Size: 2643168 SHA256: b1553d5ef4ffbfb27c985f5d06a0315ca0dad10b135a27c082eb9a9c23d545bc SHA1: eef1fd720c2c345e7abbd3411942c4a37f5f32f1 MD5sum: a6575eb76bffc917a0df23fa0e608772 Description: Hierarchical Data Format 5 (HDF5) - development files - serial version HDF5 is a file format and library for storing scientific data. HDF5 was designed and implemented to address the deficiencies of HDF4.x. It has a more powerful and flexible data model, supports files larger than 2 GB, and supports parallel I/O. . This package contains development files for serial platforms. Package: libnifti-dev Source: nifticlib Version: 2.0.0-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 624 Depends: libnifti2 (= 2.0.0-1~jaunty.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~jaunty.nd1_amd64.deb Size: 170488 SHA256: 22ab7934d1b65c1a186c60d78e91b921782b2b6f350bcd8988b0066d2106b343 SHA1: 38a5d6bf308031edfc98f6b0ad0583a937590f4e MD5sum: bc29d9392596d5a12b0f7b5718d010d3 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~jaunty.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1156 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-1~jaunty.nd1_all.deb Size: 176648 SHA256: ab05334c4b95d80ec88aa0b729643814e7aeb0e239e8fc7128cd077ba40c5d21 SHA1: 5a1325cb3e826ca2382ece57bbcb388764ea6b78 MD5sum: 7e89de56cbb748949311eb8337678fb0 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: libnifti1 Source: nifticlib Version: 1.1.0-3~jaunty.apsy1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 324 Depends: libc6 (>= 2.4), zlib1g (>= 1:1.1.4) Conflicts: libniftiio1 Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti1_1.1.0-3~jaunty.apsy1_amd64.deb Size: 119906 SHA256: 318d7206547202c0fee87e8877362c315a88b483a134a3b6bd08c75b407df471 SHA1: 6df7bda48f415f1cfdf4c169f9e1d0c201f0f027 MD5sum: 77f39d763b5cdc0d3c21ce5c736502b0 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: libnifti1-dev Source: nifticlib Version: 1.1.0-3~jaunty.apsy1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 616 Depends: libnifti1 (= 1.1.0-3~jaunty.apsy1) Conflicts: libfslio-dev, libnifti-dev, libnifti0-dev, libniftiio-dev Provides: libnifti-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti1-dev_1.1.0-3~jaunty.apsy1_amd64.deb Size: 167942 SHA256: 765da5977337f1ebf0025fdf8c11a66037ed52f81efa3abb0efbc6c51b940475 SHA1: 60b65f29b34fd7993f1af4669edc3f0e7366e0da MD5sum: a1fe2fd52298818c63aacd8d13a79996 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: libnifti2 Source: nifticlib Version: 2.0.0-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 336 Depends: libc6 (>= 2.4), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-1~jaunty.nd1_amd64.deb Size: 122368 SHA256: aa4cdb23b1efe4f83b5cabb7fbab32fb6d822acd95cae5abda73ab41db92457b SHA1: d9ad0ec967433245ae283264669e79b116c88a1a MD5sum: 47fa19eba7fe841f09df3763446750b6 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~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 21380 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~jaunty.nd1_amd64.deb Size: 4217142 SHA256: db2e87ee52e4f030f9cecad456bfdc4bcac8ac97dc8c10466e1385a15edfe23b SHA1: 7c993c7fe60e9463c1bcfba98abb3591a49840d3 MD5sum: 5fba8ffeede6996c8967b64094a9bace 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: libvia-dev Source: via Version: 1.6.0-2~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 916 Depends: libvia0 (= 1.6.0-2~jaunty.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~jaunty.nd1_amd64.deb Size: 243472 SHA256: 34ad6d83fdac10cd65be3773c072c6b6016a09b47c3aeac996c59cc91984a441 SHA1: 1648884f89d7192270ae571352e7594e73a44350 MD5sum: 0543bb7d4d4e1e98cd353430c633eaf8 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~jaunty.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~jaunty.nd1_all.deb Size: 111240 SHA256: 1a26a18a184e7a085b8f37dd5ec5c47fff8f251f6b5b7b7fe37109789f1b2280 SHA1: 33693f4df637dd981def768d134723ba3a1bc12b MD5sum: 14ab35fe3da5def6c071a5f8302a1af8 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~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 492 Depends: lesstif2, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.7), 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~jaunty.nd1_amd64.deb Size: 190764 SHA256: 7151211ec25f781d1f2de02dffab3a4c5931c54684d1fd3f1166b563f6dede5e SHA1: 8f9a1d96ae079a53e88de8c5d144d358982e8684 MD5sum: 7678e76b4780c17502a00f40978383ad 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~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 3960 Depends: libc6 (>= 2.4), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti2, libqt3-mt (>= 3:3.3.8-b), libsm6, libstdc++6 (>= 4.2.1), 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~jaunty.nd1_amd64.deb Size: 1342052 SHA256: 8f134e0814772ece58654ed799334cd3489a7a29bd00d38d50542dc4109d44e8 SHA1: d1f988763a0dafe3b22832f265ed3f2b15f7c185 MD5sum: 333c833297e4bf59a79630842a4c54e7 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~jaunty.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~jaunty.nd1_all.deb Size: 5539254 SHA256: 0700be9122fe2ce154fffdd522eb5fcf4bf6a0b6e780b0bf933b4bafeae18446 SHA1: 62b121f6603ea0f9ee6756e20d5afa357b5bda49 MD5sum: c910313c177a65666dda4adc5a252116 Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: mitools Source: odin Version: 1.8.1-3~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 6976 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.7), 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 (>= 4.5.0~+rc1), libqtgui4 (>= 4.5.0~+rc1), libqwt5-qt4, libstdc++6 (>= 4.2.1), libvia0, libvtk5, 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~jaunty.nd1_amd64.deb Size: 2399866 SHA256: 086f51d89e3eb0a0c6ec333e0eaaa8ce1d5fdd9df2d8c6ffb60d5d923e07d175 SHA1: cd7ef73d2746b21f68b1c494a3393b0ec5ca04ad MD5sum: fd5321be149086b2e396326720b806e2 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: mrtrix Version: 0.2.8-1~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 7288 Depends: libatk1.0-0 (>= 1.20.0), libc6 (>= 2.4), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.4.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.19.3), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.16.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.16.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.24.0), 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~jaunty.nd1_amd64.deb Size: 2238000 SHA256: d4c4f676b8134a2ff823775df6c1cf07a3204d3933ebbaed6dd02979e755a72f SHA1: 13c1f7d029f2bbd3234a4d140dff2890e7c129fa MD5sum: 8dd727f2623982eea30d782d48038aa5 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~jaunty.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~jaunty.nd1_all.deb Size: 2949214 SHA256: 14cb3fc3bdc986700c963385459552a3b806163a91aa8717cfa303e9ca1ef1ea SHA1: 0c0d6390dcbc8e33bc9c862a44872f7ed07a9b1c MD5sum: babace880fc632b6595ae684ba46c953 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: nifti-bin Source: nifticlib Version: 2.0.0-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 200 Depends: libc6 (>= 2.4), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-1~jaunty.nd1_amd64.deb Size: 62564 SHA256: a7c90ff3dc146b6bd5cd168970c53372ee2ab74acf1b532672664aec6b8ebf8c SHA1: 6e873754d7e074dfbe25895e7f673007dfae53e5 MD5sum: 72b183318e19ac3fc59f198364d18cf8 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1644 Depends: libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.3 | libhdf5-1.8.3, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.6+20071006-3), libreadline5 (>= 5.2), libstdc++6 (>= 4.2.1), libsuitesparse-3.2.0 (>= 1:3.2.0), 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~nd09.04+1_amd64.deb Size: 594268 SHA256: 4d801eb2f318835de998de9ec0611b4ea457980802ca2a8bcc252a492b94afb8 SHA1: 32154a1123f69be8dac20c9e3fd604213332782b MD5sum: 21521632615a53eb8e461bc83c69bc44 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: odin Version: 1.8.1-3~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4140 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4.5.0~+rc1), libqtgui4 (>= 4.5.0~+rc1), libstdc++6 (>= 4.2.1), libvtk5, mitools (= 1.8.1-3~jaunty.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~jaunty.nd1_amd64.deb Size: 1548276 SHA256: a5c3c931496f38ece3a474d4760ed36cb4f7bc2b49b98e4efe38c33f2fe6faba SHA1: ffc4cf0b1825796ad6a5a1763bd40834d364dc11 MD5sum: ad1f04aa6b959147588781ac08bdc5b2 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~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~jaunty.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~jaunty.nd1_all.deb Size: 34362 SHA256: f139639a48e4b3869e0a4cce7c9702e72add20868feb5c8e55e820a8dc5579f2 SHA1: e1ae17907b8c588294e4e14006b933394d450a1f MD5sum: aa68fd3a84a824750de61a1d2054ab63 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: psychopy Version: 1.62.02.dfsg-1~nd09.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3100 Depends: python (>= 2.4), python-support (>= 0.7.1), 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_1.62.02.dfsg-1~nd09.04+1_all.deb Size: 1396892 SHA256: 943f826c7a99c7e733e2c54e3e06ccb9b5263bb477b9a212342ccb16ceda6177 SHA1: b2370946e5c2ead805829e7a52e07250b0963b21 MD5sum: 0fe45f3c5011c3ed97b90e32c3f533bf 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: python-biosig Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1036 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsuitesparse-3.2.0 (>= 1:3.2.0), 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~nd09.04+1_amd64.deb Size: 338240 SHA256: ffd75627816cf986eeee16b9b43ab75737e46271c5c9c02760ccb24610435dae SHA1: acc51ebd0f040f33fdad42dbdbbc92dbebd5d775 MD5sum: 0d5bd912cd154f91ff7ee28385a75cb6 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-epydoc Source: epydoc Version: 3.0.1-4~jaunty.nd1 Architecture: all Maintainer: Kenneth J. Pronovici Installed-Size: 1216 Depends: python (>= 2.1), python-support (>= 0.7.1) Recommends: gs-common, python-tk, python-docutils, texlive-latex-base, texlive-latex-extra, texlive-latex-recommended, texlive-fonts-recommended, graphviz Suggests: epydoc-doc, python-profiler Conflicts: python2.1-epydoc (<< 2.0-2), python2.2-epydoc (<< 2.0-2), python2.3-epydoc (<< 2.0-2) Replaces: python2.1-epydoc (<< 2.0-2), python2.2-epydoc (<< 2.0-2), python2.3-epydoc (<< 2.0-2) Priority: optional Section: python Filename: pool/main/e/epydoc/python-epydoc_3.0.1-4~jaunty.nd1_all.deb Size: 267040 SHA256: 312c145664c8ea0b5eafa44d4aaf36d5021e42364a964f7e7dfa20c1f2db6e24 SHA1: 4fb3cb310f396da52a093b5bf7a073e3d7739e6d MD5sum: dc764475a92057f38ff67326bc3edbb7 Description: tool for generating Python API documentation Epydoc is a tool for generating API documentation for Python modules based on their docstrings. A lightweight markup language called epytext can be used to format docstrings and to add information about specific fields, such as parameters and instance variables. Epydoc also understands docstrings written in ReStructuredText, Javadoc, and plaintext. . This package contains the epydoc and epydocgui commands, their manpages, and their associated Python modules. Package: python-mdp Source: mdp Version: 2.6-1~jaunty.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 1552 Depends: python (>= 2.4), python-support (>= 0.7.1), 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~jaunty.nd1_all.deb Size: 293698 SHA256: 4253276e7511b10a169bac8eced5986bc384ddcc66c83f53aa67597dc0ea4254 SHA1: 1ad76a08974ef499122c0a6df035f5bf87e7474b MD5sum: 1a4be6a51ffc50abfd67f5abb91da80c Description: Modular toolkit for Data Processing Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. Package: python-mvpa Source: pymvpa Version: 0.4.5-1~nd09.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4132 Depends: python (>= 2.5), python-support (>= 0.7.1), python-numpy, python-mvpa-lib (>= 0.4.5-1~nd09.04+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.5-1~nd09.04+1_all.deb Size: 2155218 SHA256: e45fe6c1c238b943906455965fbe2a190930e72139c2f70de240fae299a6ed27 SHA1: 85a9eb8dba726f5dafb469a33a2b9ffe5e1f1694 MD5sum: 2cc3f827caf2d5d4d58f82eb9baa74c2 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~nd09.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40984 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~nd09.04+1_all.deb Size: 9058390 SHA256: b3cdaf67859d3ed75c61686f5b426cbc4f63376c3b3ffb5486f15772ea0d619a SHA1: 20b73a76d761be7fb89daa86984d19f505a102a8 MD5sum: 3e52b8fecf85a71911120367b8876c64 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~nd09.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 308 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), 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~nd09.04+1_amd64.deb Size: 62092 SHA256: 5fa4d0ab62ecb4282bfbefa6af9016d4c0f89b02926cd737871cc87591daf03c SHA1: 269da25b3398dfdc47d979351e03da7495c4f65b MD5sum: 87a27b44494b18a096ba4fa897ed31bd 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: 0.5.0.dev+783+gde39-1~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4412 Depends: python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-mvpa-snapshot-lib (>= 0.5.0.dev+783+gde39-1~jaunty.nd1) 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-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_0.5.0.dev+783+gde39-1~jaunty.nd1_all.deb Size: 2213864 SHA256: ab572a75c8ba28690085ed3d5e3dc8026dfe8614bff6388b8a48c1e989db7fe1 SHA1: bed3e65433ed3d22b3f5971e882cc1de8629ebd1 MD5sum: 5977bd7637be1fff8256f47170b98663 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: 0.5.0.dev+783+gde39-1~jaunty.nd1 Architecture: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 304 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), 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_0.5.0.dev+783+gde39-1~jaunty.nd1_amd64.deb Size: 60420 SHA256: 0e6a177f3d648e42016eae341ec97539f45498aa1c3cd1c0e2faebbfd975fd94 SHA1: efd2bd443f3aa4e6ae04b5748d71d83dc7dbb02d MD5sum: e6d550587bf446eee05e92b99212b80e Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~jaunty.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.7.1), 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~jaunty.nd1_all.deb Size: 469574 SHA256: 91b53f7f46a11ee9f9da44a1b89d71902a53641460942446e59daa91ac31b600 SHA1: 5b6bd58796032e49d147acccfc8e9eff505ee5ae MD5sum: 4d1ac72049f79c9939e37fc8016de5a0 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~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1500 Depends: libc6 (>= 2.4), libnifti2, python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), 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~jaunty.nd1_amd64.deb Size: 360538 SHA256: b5eb5fdb37070dbe135c92f8f906a61c1f72886a0d989418c380ca32667196a1 SHA1: fb9631b10fba356dc835c6dedb99b7ae306a101c MD5sum: 486da432032a8e8768b44e21254b08ba 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-openopt Source: openopt Version: 0.25+svn291-1~jaunty.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 1188 Depends: python (>= 2.5), python-central (>= 0.6.11), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib, python-glpk Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.5-openopt, python2.6-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.25+svn291-1~jaunty.nd1_all.deb Size: 152194 SHA256: f747888452b3627cf90795de4180fd0dd610d272033b061c7f0e67417485b1e4 SHA1: b27e83509b884400fdae35d648e28885cab4cb90 MD5sum: ccd9b7ed8a4a39e6a0fdd3ab7f009d35 Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: >= 2.5 Package: python-openpyxl Source: openpyxl Version: 1.1.0-1~jaunty.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 444 Depends: python-support (>= 0.7.1) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.1.0-1~jaunty.nd1_all.deb Size: 48916 SHA256: 3778c0dac0cbea2305e9432a0921900454176a140e76cc204119f7986a157407 SHA1: f3ca356f11f055391389d22ecf51c70b52eb7ae4 MD5sum: f89b9ea2138dd7878f225bc78525649b 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~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 2448 Depends: python (<< 2.7), python (>= 2.5), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~jaunty.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.18), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode0debian1 (>= 1:0.8.dfsg-3), libsamplerate0, libsndfile1, libstdc++6 (>= 4.2.1) 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~jaunty.nd1_amd64.deb Size: 604158 SHA256: c948eb1fe1109e42151aa4b5c6a848a7e2f314ce3e4ddd0921f250e5093001f5 SHA1: 2c0272bee3208924398ab91bcba0ccefc9a85f22 MD5sum: 893d4addcacca50e317a699a3b92d037 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~jaunty.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~jaunty.nd1_all.deb Size: 817822 SHA256: 132b135adc1a1e1d8abd118f7a5d9f2b59c703f3fe56c544d664236aebe8bc81 SHA1: f518107230bc900c570e683bc03179fca267f2aa MD5sum: b92c01800be9d13a93810e6460192b44 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-pyoptical Source: pyoptical Version: 0.2-1~jaunty.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 68 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~jaunty.nd1_all.deb Size: 6868 SHA256: 6637f87f248bf59d0a4694972e6e3e8cec579032399996f73214775582dfa107 SHA1: 3fdc9de81dc3565a96e4967227584dc073af1d50 MD5sum: 02252899ecb2028dfa71657a2d8cc3cb 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~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 784 Depends: python-support (>= 0.7.1), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.5-pyssdh, python2.6-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~jaunty.nd1_all.deb Size: 119340 SHA256: eab3eb4322879f87e42e9e8c456003c3d96bcf98e481f4529dd1c9ca0f3972c6 SHA1: 5f0c5bd7a8fd3dcd4cb4c30d5cfa084476c14d68 MD5sum: fc7e29565fca1ccbe82bdfa54ef25c78 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: 2.5, 2.6 Package: python-scikits-learn Source: scikit-learn Version: 0.3-1~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 1736 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), python-numpy, python-scipy, python-scikits-learn-lib (>= 0.3-1~jaunty.nd1) Recommends: python-nose, python-psyco, python-matplotlib 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_0.3-1~jaunty.nd1_all.deb Size: 454998 SHA256: 8302fedfc307cf29f8dac7642680d3617cc33f148a9f4c894eb8efc2880bfc3a SHA1: 4c123811c6a749b91f795701178f89a7dc8f43c0 MD5sum: 56e7acd006a11aec24f89cae226ea619 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: 0.3-1~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 1608 Depends: 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_0.3-1~jaunty.nd1_all.deb Size: 599906 SHA256: b05410c464b7d83765fc87f2b3f9409d934307740d909c83d46310922dc53487 SHA1: b14ba19766b3a96bc9e19cee47f37552eab65c7f MD5sum: 4ae7c9e58cd4d396b482e8b7b516cbd0 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikit-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.3-1~jaunty.nd1 Architecture: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 1344 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), python-numpy 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_0.3-1~jaunty.nd1_amd64.deb Size: 430936 SHA256: 6e72ca855682f51e1b1350c9babf3482218291cc957028e33dc35ac35e5608fd SHA1: 6cb0b9c04925e19d18cb2c18b50d7f980362c9ec MD5sum: 9dd8ecb4a74b50adabca3ecf602e334c Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-scikit-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-scikits-statsmodels Source: statsmodels Version: 0.2.0+bzr1990-1~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 9648 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.7.1), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Provides: python2.5-scikits-statsmodels, python2.6-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: python Filename: pool/main/s/statsmodels/python-scikits-statsmodels_0.2.0+bzr1990-1~jaunty.nd1_all.deb Size: 1877782 SHA256: 74b94cab15b557a60f6b9aed6d194d258f3280207dfe35bd02caa8555d222478 SHA1: 8addbcda5caa6033c7ec389985d32950b5b417c4 MD5sum: 20dccf17cebeb5ffdb909a86e77b4d68 Description: classes and functions for the estimation of statistical models scikits.statsmodels is a pure Python package that provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are avalable for each estimation problem. Python-Version: 2.5, 2.6 Package: python-scikits-statsmodels-doc Source: statsmodels Version: 0.2.0+bzr1990-1~jaunty.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 668 Depends: libjs-jquery Suggests: python-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: doc Filename: pool/main/s/statsmodels/python-scikits-statsmodels-doc_0.2.0+bzr1990-1~jaunty.nd1_all.deb Size: 217468 SHA256: 4e5a56cb0359b474a405da219b53aef035c437a39c6051eaf43cdfb2a6588aa8 SHA1: c7b4b571b4f72dbc598a608a508f2299214c3095 MD5sum: 0369b9c3108d6005361e616a070943dd Description: documentation and examples for python-scikits-statsmodels This package contains HTML documentation and example scripts for python-scikits-statsmodels. Package: python-sphinx Source: sphinx Version: 1.0.1-1~nd09.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4576 Depends: python (>= 2.4), python-support (>= 0.7.1), 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~nd09.04+1_all.deb Size: 1233066 SHA256: 1bab07bfeb1dbace004870b27a0ea246687b55306b01c074ac2d7e32833b9c53 SHA1: f9f527ab108b516b3a07ee55e9e57c073655a066 MD5sum: 5c148a723f0f56b83ea3c946e52b1ee9 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: qlandkarte Source: qlandkartegt Version: 0.16.0-1~jaunty.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~jaunty.nd1_all.deb Size: 2598 SHA256: 7cecc24e7b0125b73a2b7f72f75deb8f8a14e53813ccda96ac83728bba21d384 SHA1: 6cdb92ebbc58e5bfd079f4e447c7c4d44d5e0887 MD5sum: 937e6563564ae2d2f5a916ac1e0dfa47 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~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 4984 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdal1-1.5.0, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libqt4-network (>= 4.5.0~+rc1), libqt4-opengl (>= 4.5.0~+rc1), libqt4-sql (>= 4.5.0~+rc1), libqt4-xml (>= 4.5.0~+rc1), libqtcore4 (>= 4.5.0~+rc1), libqtgui4 (>= 4.5.0~+rc1), libsm6, libstdc++6 (>= 4.1.1), libx11-6, libxext6, proj 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~jaunty.nd1_amd64.deb Size: 2735096 SHA256: b0682183e883c01385db73fa1f98761daef04cdce9fef44fecb338b74c8d496c SHA1: 3986495d98fd2e0875e7823bd5f7f221d5683e68 MD5sum: a5d5224c6a56e91f86e85854f55aebe6 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~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 528 Depends: libc6 (>= 2.7), 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~jaunty.nd1_amd64.deb Size: 177954 SHA256: ba8b91888a8fc6f708f293c8aaa609a956bd39e9f4d21c8187f5407b02ddc1f8 SHA1: f5967bfc4388512400435aac4b96630f4612f493 MD5sum: 75f6fe8b538ca28b3d581820050f5bb2 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: svgtune Version: 0.1.0-1~jaunty.nd1 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_0.1.0-1~jaunty.nd1_all.deb Size: 6754 SHA256: b57d1e7ff1cec86f0e751903bb020a0d027ec037ae5e98f615e0622d713ad69e SHA1: bc9d0fef094cad94e2d5c0fbfdbd5b440ea46a78 MD5sum: 5f654a6ee6bbf068ba9f1d03f2eadf3f 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~jaunty.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 1072 Depends: lesstif2, libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.4), 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~jaunty.nd1_amd64.deb Size: 190264 SHA256: 8eaa26c2648dec30354023581a4989818b5e50acbace46fe9dfef68f633b6340 SHA1: 06785a8f5eac2934dba1d2e37071206f939aff2e MD5sum: d2eb4ea0096574951789b83497c5c1c7 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~svn1172-1~jaunty.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 9040 Depends: libc6 (>= 2.7), libfontconfig1 (>= 2.4.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4.5.0~+rc1), libqt4-qt3support (>= 4.5.0~+rc1), libqtcore4 (>= 4.5.0~+rc1), libqtgui4 (>= 4.5.0~+rc1), libstdc++6 (>= 4.2.1), libx11-6, libxext6, libxi6 (>= 2:1.2.0), libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1172-1~jaunty.nd1_amd64.deb Size: 3408310 SHA256: 019a2a7b5e1049d11b0c5344a44ac6ae4610f9548cfe5500bf2aa79190543471 SHA1: 7b8e3f3c391f706a80297474e9ce1de7978630bc MD5sum: b2b71312683ce9123af37fc3e1aac982 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.