Package: arno-iptables-firewall Version: 1.9.2.d-1~intrepid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 824 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0 Recommends: iproute, 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.d-1~intrepid.nd1_all.deb Size: 123620 SHA256: 7a951b6391796c386d7b53053dc549b54f2faa2c89e988e5bf38b2f38d15c82d SHA1: 241c798a8689da81c97510dd00f9467c4553d9e7 MD5sum: 9836f2e568d2e23c8b55b31547505409 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: dicomnifti Version: 2.28.14-1~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 496 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti1 (>> 1.1.0-2), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-1~intrepid.apsy1_i386.deb Size: 150830 SHA256: a9302ee36289bbdd9b16e357abb93b7641e247c82aa181e9bf4579e1851fcc41 SHA1: e2bb0c9d99d6b22a7e9527466ffdde86fb0df6f5 MD5sum: 81293ea910c9821dfbd6038b8d13bd41 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~intrepid.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~intrepid.nd1_all.deb Size: 1544776 SHA256: 561d90e7ab07a46ed84cffa9d57ac53f5976274424f75ac1c61cd87b970c1510 SHA1: ad5ce6d78bc14f9cf3d89a292b51c56e9858c896 MD5sum: 38cfb43524cf45e60188da8d29cc117a 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: 3.1.2+4.1.5.2-1~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3848 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti1 (>> 1.1.0-2), 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_3.1.2+4.1.5.2-1~intrepid.nd1_i386.deb Size: 1474956 SHA256: 6a83509aecd3a26f0739e709c14b9b75ce5006ab95a3ad3c03ca212df505efd8 SHA1: 9ecd4cd19afa26c951fc55bfdd6a80c7b2456843 MD5sum: 3b0489e2d8ae695c5b2482d25ea9c19b 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: 3.1.2+4.1.5.2-1~intrepid.nd1 Architecture: all Maintainer: Michael Hanke 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_3.1.2+4.1.5.2-1~intrepid.nd1_all.deb Size: 2378810 SHA256: a75f2d094f9946a20ed3d685ba9148df620c5cdadd76e7251b304bfdc03856d7 SHA1: c58639889fb8adb001a3980071915e79322839e5 MD5sum: 51f70297d91ed770fd239d2e8c6e7895 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: kbibtex Version: 0.2.3-1~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 2512 Depends: kdelibs4c2a (>= 4:3.5.9), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), 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~intrepid.nd1_i386.deb Size: 758458 SHA256: a8ee7cee34286522d4733350f2dab9c56541bd262dcd032492b0a5e53b28102d SHA1: 564ba4eb347533b537f54353d203b673cc2066fb MD5sum: b82ecde47ebe64ccb400a0bce294fa03 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: libjs-jquery Version: 1.2.6-1~apsy.0 Architecture: all Recommends: javascript-common Conflicts: jquery Replaces: jquery Installed-Size: 240 Maintainer: Debian Javascript Maintainers Source: jquery Priority: optional Section: web Filename: pool/main/j/jquery/libjs-jquery_1.2.6-1~apsy.0_all.deb Size: 65238 SHA256: fa858cf809b1885439cfb0d6e8ba64021a732b2e9b8493027f5d767973268d22 SHA1: 19177bbdd00962ac018ffa081149840aa7bbc469 MD5sum: 6dc346b0c5ffacbdf0e63f00d1f18485 Description: JavaScript library for dynamic web applications jQuery is a fast, concise, JavaScript Library that simplifies how you traverse HTML documents, handle events, perform animations, and add Ajax interactions to your web pages. jQuery is designed to change the way that you write JavaScript. Package: libnifti-doc Source: nifticlib Version: 1.1.0-3~intrepid.apsy1 Architecture: all Maintainer: Michael Hanke Installed-Size: 1140 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_1.1.0-3~intrepid.apsy1_all.deb Size: 171278 SHA256: b78c7adb796bbd90753b63d3924f23159c327301897059ff0ebc6ddee7949d91 SHA1: f12b0fb1e07f86181368d35745f9c3d356b14861 MD5sum: 7c6cbcff70e956b22e3bb2d0d8bd2290 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~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 300 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~intrepid.apsy1_i386.deb Size: 105816 SHA256: ed42d21bd49e6703a38fe0efd65b8c59614d277cfd958abbdad7c8914c21d556 SHA1: 3633557374f314305605c3460c074c38b97c4424 MD5sum: bae194ac45e66e9ebf7ce7a1ff37055b 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~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 452 Depends: libnifti1 (= 1.1.0-3~intrepid.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~intrepid.apsy1_i386.deb Size: 149190 SHA256: 72ee482d7965a3100703532b3b14dea8e19f4e8fdc85b54615c22114bd618bbf SHA1: 2e48e0bbd8bd056e54a01b5a3b4a77d0da885ba7 MD5sum: f96ea163307b631b4c00d9e60ec103e6 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: libodin-dev Source: odin Version: 1.8.0-1~intrepid.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 15568 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.0-1~intrepid.nd1_i386.deb Size: 3902394 SHA256: 58741c22221794c0842c5641998cc3d8aa73563add94cb23fd175cdeb4231432 SHA1: 759407dd30f7728473f0d56b33d3fb1568c4edca MD5sum: ad0e0005fb9c41a0f8131595618837a8 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~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 700 Depends: libvia0 (= 1.6.0-2~intrepid.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~intrepid.nd1_i386.deb Size: 214624 SHA256: 18d134ecbcda417da22aa3d89a5c4e27afdb2721ccfb8253513e799a662dfce6 SHA1: 33e6bef427ce540dcb622d7fbe12ebb4362d43ef MD5sum: f76d91ed55d3f823e1a0287e20c6bbd9 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~intrepid.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~intrepid.nd1_all.deb Size: 111168 SHA256: 5c1e3644ed0d203297cb3f3586fa1c371e4a1b1f1d097d5ff56e08e715da3892 SHA1: 39f6c30ca1bb73c3b770b12152a4f34b04cb51c2 MD5sum: 209632ad5513801d1d269ecd257fe78e 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~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 452 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~intrepid.nd1_i386.deb Size: 181454 SHA256: c6e6aa8016b2581faffb9b3bdb61fa711454c2f938fc9a19fec8adab43c5f88e SHA1: 23995f3ab6287c950826b758a036fd6f4136792e MD5sum: be94a687641a6eb8e756b54e87a5d172 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: 1.6.0-3~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3604 Depends: libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti1 (>> 1.1.0-2), 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_1.6.0-3~intrepid.nd1_i386.deb Size: 1264848 SHA256: f35b6c51eead220ce6c7c83ade6ee258f279dcda9d9a29284180feb95ee21ac0 SHA1: a2fe53796569fe8027d674e2c1acdcdbc33fecec MD5sum: cdd8e3f0915c56334263291fd4e588b5 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 effcient 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 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: 1.6.0-3~intrepid.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_1.6.0-3~intrepid.nd1_all.deb Size: 5533894 SHA256: 4126dd2fde3203dec5587a738826e1dd7c64635e6188f1a8432a0ae3d8a799dc SHA1: ef8d6a7cb9d48987eb3b8d8a470ccb65dbc57545 MD5sum: 4cb6097be67be81abfad03f65e0c2253 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: 1.8.0-1~intrepid.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 5980 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti1 (>> 1.1.0-2), liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4.4.3), libqtgui4 (>= 4.4.3), 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_1.8.0-1~intrepid.nd1_i386.deb Size: 2168092 SHA256: edb4db15d4a7c5aca33d75ab4f50031d9bd83e5242a7609a1059a626f91cfda2 SHA1: 09284ee43c90d3528b3c0199d0225832519d11b9 MD5sum: fd801db2a9b3d0b2cb1e2acf75261229 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: nifti-bin Source: nifticlib Version: 1.1.0-3~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 196 Depends: libc6 (>= 2.4), libnifti1 (>> 1.1.0-2) Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_1.1.0-3~intrepid.apsy1_i386.deb Size: 59620 SHA256: 2e4ac524bc73e4a70039d159ddd0ab28507151de28dacba8d3fcf32cf737bc96 SHA1: 55b1984be8d39ca08d642187c272ec0780b29aa0 MD5sum: 96e131671da577d749c0bbaf3470c493 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: 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: odin Version: 1.8.0-1~intrepid.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 3816 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4.4.3), libqtgui4 (>= 4.4.3), libstdc++6 (>= 4.2.1), libvtk5, mitools (= 1.8.0-1~intrepid.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, 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_1.8.0-1~intrepid.nd1_i386.deb Size: 1478722 SHA256: d459d3d6dc1cd5f698a9875151a1c77f1eb379060d200fb551abc912f6b5d890 SHA1: a49b23222e80eca2bf0051e621e4317a6416280d MD5sum: 0f6b17ea5e0eab64c8b27f2f344b7fe3 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~intrepid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~intrepid.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~intrepid.nd1_all.deb Size: 34360 SHA256: 693ec835ea374f46b79fc2035933a73511eefd08fb60caf47777a0f8041ea51a SHA1: 1d970e0f4ba75b684802cac0f7c7efa58adbb5ab MD5sum: 412554b3eb401ce7707836e003a22759 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: 1.51.00.dfsg-1~intrepid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 2412 Depends: python (>= 2.4), python-support (>= 0.7.1), python-pygame | python-pyglet, python-opengl, python-numpy, python-matplotlib, python-lxml Recommends: python-wxgtk2.8, python-imaging, python-serial, python-scipy, libavbin0 Suggests: python-pyepl Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.51.00.dfsg-1~intrepid.nd1_all.deb Size: 1003170 SHA256: cb8f87b4e538c93e29333d58343f30de85ff3863c4a24e895c35e7f03dc9a891 SHA1: ef0185baf7831760502c325255955daa67e9d777 MD5sum: bb72ed9ca4242e8098f0ac16d6ac73af 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: 2.4, 2.5 Package: python-epydoc Source: epydoc Version: 3.0.1-4~intrepid.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~intrepid.nd1_all.deb Size: 267060 SHA256: 28fbb77b6b6b6af37963b15a6cce4c41b31547db3310c10875a234893088fdde SHA1: 1fe020c9d672bbad6bd5a3580db8355180a08cf5 MD5sum: 4a25806ee04781f8a35181016a9daf8f 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-griddata Source: griddata Version: 0.1.2-1~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 244 Depends: libc6 (>= 2.4), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext Recommends: python-matplotlib Provides: python2.4-griddata, python2.5-griddata Homepage: http://code.google.com/p/griddata-python/ Priority: optional Section: python Filename: pool/main/g/griddata/python-griddata_0.1.2-1~intrepid.apsy1_i386.deb Size: 60476 SHA256: 917012c97ee135b66f2357d4995f1384e45917c75cb6bfb8a8f00cf537442c49 SHA1: baa1c94680217a5f091edaa63ea9b629d55433d1 MD5sum: 48229250e76b1a0ca747476fb6b959be Description: Python function to interpolate irregularly spaced data to a grid This module provides a single function, 'griddata', that fits a surface to nonuniformly spaced data points. It behaves basically like its equivalent in Matlab. Python-Version: 2.4, 2.5 Package: python-hcluster Source: hcluster Version: 0.2.0-1~intrepid.apsy1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 400 Depends: libc6 (>= 2.1.3), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext, python-ctypes Recommends: python-matplotlib Provides: python2.4-hcluster, python2.5-hcluster Homepage: http://code.google.com/p/scipy-cluster/ Priority: optional Section: python Filename: pool/main/h/hcluster/python-hcluster_0.2.0-1~intrepid.apsy1_i386.deb Size: 82396 SHA256: 08a42f086b4ed8c623c36fc765a8241d9447048fbe622a26a8f13f35c8c93f8c SHA1: c6fe217a8ce09fc23823d0832aca4e2d7b029813 MD5sum: 077287b18c7e2d86b380bca6492eca16 Description: Python functions for agglomerative clustering The module's features include: . * computing distance matrices from observation vectors * generating hierarchical clusters from distance matrices * computing statistics on clusters * cutting linkages to generate flat clusters * visualizing clusters with dendrograms . The interface is very similar to MATLAB's Statistics Toolbox API. The core implementation of this library is in C for efficiency. Python-Version: 2.4, 2.5 Package: python-jinja2 Source: jinja2 Version: 2.1.1-2~bpo50+1~intrepid.nd1 Architecture: i386 Maintainer: Piotr Ożarowski Installed-Size: 512 Depends: python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), libc6 (>= 2.1.3) Recommends: python-pkg-resources, python-pybabel Suggests: python-jinja2-doc Provides: python2.4-jinja2, python2.5-jinja2 Homepage: http://jinja.pocoo.org/2/ Priority: optional Section: python Filename: pool/main/j/jinja2/python-jinja2_2.1.1-2~bpo50+1~intrepid.nd1_i386.deb Size: 76014 SHA256: cc7ebfcc2b4ae475e8d4e19a248379bc4fdb5b788cff4b4b403465b8fe4151a5 SHA1: 4883b54d098c1eaa66d06020292c65df90c796eb MD5sum: 4ee4f4990a4ca9f886d69b8ccea32638 Description: small but fast and easy to use stand-alone template engine Jinja2 is a template engine written in pure Python. It provides a Django inspired non-XML syntax but supports inline expressions and an optional sandboxed environment. . The key-features are: * Configurable syntax. If you are generating LaTeX or other formats with Jinja2 you can change the delimiters to something that integrates better into the LaTeX markup. * Fast. While performance is not the primarily target of Jinja2 it’s surprisingly fast. The overhead compared to regular Python code was reduced to the very minimum. * Easy to debug. Jinja2 integrates directly into the Python traceback system which allows you to debug Jinja2 templates with regular Python debugging helpers. * Secure. It’s possible to evaluate untrusted template code if the optional sandbox is enabled. This allows Jinja2 to be used as templating language for applications where users may modify the template design. Python-Version: 2.4, 2.5 Package: python-jinja2-dbg Source: jinja2 Version: 2.1.1-2~bpo50+1~intrepid.nd1 Architecture: i386 Maintainer: Piotr Ożarowski Installed-Size: 180 Depends: python-jinja2 (= 2.1.1-2~bpo50+1~intrepid.nd1), python-dbg, libc6 (>= 2.1.3) Provides: python2.4-jinja2-dbg, python2.5-jinja2-dbg Homepage: http://jinja.pocoo.org/2/ Priority: extra Section: python Filename: pool/main/j/jinja2/python-jinja2-dbg_2.1.1-2~bpo50+1~intrepid.nd1_i386.deb Size: 22470 SHA256: 3d22bb68f5d9b4d1fdc1a912baf185609dad1912ec6231d6a9d1cf85aefa2b3f SHA1: 3922b190f7a3639295b128e3becc74eec8a6375e MD5sum: 99028acaf491414d3c64916f660397e8 Description: small but fast and easy to use stand-alone template engine Jinja2 is a template engine written in pure Python. It provides a Django inspired non-XML syntax but supports inline expressions and an optional sandboxed environment. . This package contains the extension built for the Python debug interpreter. Python-Version: 2.4, 2.5 Package: python-jinja2-doc Source: jinja2 Version: 2.1.1-2~bpo50+1~intrepid.nd1 Architecture: all Maintainer: Piotr Ożarowski Installed-Size: 968 Depends: libjs-jquery Recommends: python-jinja2 Homepage: http://jinja.pocoo.org/2/ Priority: extra Section: doc Filename: pool/main/j/jinja2/python-jinja2-doc_2.1.1-2~bpo50+1~intrepid.nd1_all.deb Size: 211302 SHA256: 2ccb2aa0f923ae8e649c43c40cad9971f97112375343c0940f95600ead1165f2 SHA1: dd627a39bb16153d76a2e46a1fe632c1a73c087a MD5sum: 5467fcff16e2282a880b86e9e1993523 Description: documentation for the Jinja2 Python library Jinja2 is a small but fast and easy to use stand-alone template engine . This package contains the documentation for Jinja2 in HTML and reStructuredText formats. Package: python-mdp Source: mdp Version: 2.5-1~intrepid.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 944 Depends: python (>= 2.4), python-support (>= 0.7.1), python-numpy Recommends: python-scipy Suggests: python-pp Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_2.5-1~intrepid.nd1_all.deb Size: 172326 SHA256: f6a33c38e176c1138228b177ef0e2fea7e6ad6ac151484f5c09ca2ac842610a7 SHA1: bed32c925b7c393e79a1caa515540f3f6d6c8ebb MD5sum: 771fae97c74c33078ccb2cf657902987 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: 0.4.3-1~intrepid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4068 Depends: python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-mvpa-lib (>= 0.4.3-1~intrepid.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 Provides: python2.4-mvpa, python2.5-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.3-1~intrepid.nd1_all.deb Size: 2140906 SHA256: 2c8c89a3dc7ef27d2247ef2cce8b32832c9c0b911b7c3e709dd6686229cf3a28 SHA1: 4bffeeb54603c248e3c29510d4b305868e6e1bbb MD5sum: bf93de8bc2c6e33b9a9f9169c2067b1d 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. Python-Version: 2.4, 2.5 Package: python-mvpa-doc Source: pymvpa Version: 0.4.3-1~intrepid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 44364 Depends: libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.3-1~intrepid.nd1_all.deb Size: 11556116 SHA256: 89b466a5c611e5b27df055bcec746e98a053589c3f55e44be82635f7a5f748b3 SHA1: 6a2541abe8eee78f72ab7d81a338fd555caedb39 MD5sum: 81703baf4e69819bfc5836e21afd5163 Description: documention and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT, PDF) including * User manual * Developer guidelines * API documentation . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.3-1~intrepid.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 284 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-ctypes (>= 1.0.1) | python (>= 2.5) Provides: python2.4-mvpa-lib, python2.5-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.3-1~intrepid.nd1_i386.deb Size: 56728 SHA256: e16609a29dd175e38fd95f1c9f11f44ac2bdc7894e39982f9c2661e035d99116 SHA1: 5baba5e83d9ff34fed82c2982b84e0ba52e962ef MD5sum: 8801278baaaeb6a271606f1426a9140b 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: 2.4, 2.5 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~intrepid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4416 Depends: python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-mvpa-snapshot-lib (>= 0.5.0.dev+783+gde39-1~intrepid.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: python2.4-mvpa-snapshot, python2.5-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~intrepid.nd1_all.deb Size: 2214468 SHA256: e642eb4f909fe69fc23a535684e6d08091cf29d9b96b6795024e543c01a01d5e SHA1: c6ddd6a72a636cc30b9f2bee335d939a00fcfe72 MD5sum: 308911cdeb5e12f16cdb97eba6dc1329 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: 2.4, 2.5 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~intrepid.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 284 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy Conflicts: python-mvpa-lib Provides: python2.4-mvpa-snapshot-lib, python2.5-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~intrepid.nd1_i386.deb Size: 57592 SHA256: f8b3968d983b532b43aebe7439d7a1d0a6a340e465f0cd197fed966c4a093826 SHA1: a5a45ed7d8577af914690588a0561e15e85b9822 MD5sum: 977d44ac62125328c302017e888ec2f8 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: 2.4, 2.5 Package: python-networkx Version: 1.0.1-0.1~intrepid.nd1 Architecture: all Maintainer: Cyril Brulebois Installed-Size: 1976 Depends: python (>= 2.4), python-support (>= 0.7.1) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: https://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.0.1-0.1~intrepid.nd1_all.deb Size: 537010 SHA256: b28f92b8ac4e4267d29b649d0fa40d12923f4e3178da4eed1150d88b2a32b0db SHA1: 59e4b4b4633070a5c1de01336d28d0cf3f1e056f MD5sum: 5a2f588836553fa95128c0999803ea58 Description: tool to manipulate and study more than complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph we mean a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network we usually mean a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-nifti Source: pynifti Version: 0.20100412.1-1~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 1408 Depends: libc6 (>= 2.4), libnifti1 (>> 1.1.0-2), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext, libjs-jquery Provides: python2.4-nifti, python2.5-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100412.1-1~intrepid.nd1_i386.deb Size: 338458 SHA256: 704eb7bf7c89cabbcf40c2c88eecded906b884529bf516d27631dba5d9f1fe6c SHA1: 449908148a549ccb102ef3ee76100a87656515ae MD5sum: 46cd42c6292138eca598349ff3758bf7 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: 2.4, 2.5 Package: python-openopt Source: openopt Version: 0.25+svn291-1~intrepid.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 1196 Depends: python (>= 2.5), python-central (>= 0.6.7), 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 Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.25+svn291-1~intrepid.nd1_all.deb Size: 153000 SHA256: c24c871de2015c5192a519071b81287a01f71a71c95c13e0fe2fc79258f5c0ca SHA1: d4066eade34b61521161061b9656fd2b7f84ed9f MD5sum: 346d1ebde731713c50da4628654bdc0c 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-pyssdh Source: openelectrophy Version: 0.0.svn143-1~intrepid.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: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~intrepid.nd1_all.deb Size: 119332 SHA256: 5a4fdcb20f2252b433043fc03ff9b8480d4466c2afb6a6a7029b4abbc777999a SHA1: 8435527e9afc592017950415e1f6cb765215d399 MD5sum: 86091a280f0f2ea6449d2107e9fc154f Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-sphinx Source: sphinx Version: 0.6.3-1~bpo50+1~intrepid.nd1 Architecture: all Maintainer: Mikhail Gusarov Installed-Size: 2904 Depends: python (>= 2.4), python-support (>= 0.7.1), python-docutils, python-pygments (>= 0.8), python-jinja2 (>= 2.1), 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_0.6.3-1~bpo50+1~intrepid.nd1_all.deb Size: 527140 SHA256: 4418c4a344088c7d878ac926cf4720e2804810ef63f441b1c32ebd14adebe393 SHA1: c099c0e58c93eb570e66a9ee8eede0f888f54269 MD5sum: f69b7a17220397e5915994060a9bdda4 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~intrepid.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~intrepid.nd1_all.deb Size: 2588 SHA256: 0e710474ef8189533783f471d831d11309408c8310f742b61ce075afc59cca8e SHA1: ce767179fd66f164ab573be2948e28e1c60405ea MD5sum: 8dea95607c08bad783f4a20ddb6903fd 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~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 5028 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 (>= 4.4.3), libqt4-opengl (>= 4.4.3), libqt4-sql (>= 4.4.3), libqt4-xml (>= 4.4.3), libqtcore4 (>= 4.4.3), libqtgui4 (>= 4.4.3), 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~intrepid.nd1_i386.deb Size: 2762934 SHA256: ad0452da467f437c9ea0038086f259aff304de2ae1d7fb73697cf799f6eaca98 SHA1: 867b93b4a84bca7c9664b1dad98116e0e64e04a3 MD5sum: b079b4ae8ce3bba36ff3cde198633b6f 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~intrepid.nd1 Architecture: i386 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~intrepid.nd1_i386.deb Size: 176616 SHA256: 53af3d6a91685abdef8afd1ae69609d77788ef7b646d724f4c3f4e92488d881e SHA1: cbf63ad0f09dab4edd521a38e8cc0b7a4ded1c28 MD5sum: 9a6becf95e37ebbc1d39e5716d685ca2 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: spm8-common Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 21124 Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4010~dfsg.1-3_all.deb Size: 10086746 SHA256: 420af58742ffd8d712777d84e1b5cab7f62ffa60cc53d3cac35747af68fd57c7 SHA1: 30c639e67be5083685f97306730b186ee4b2c063 MD5sum: 89daeb63df29035e31b49719d63eb4ba Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73316 Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4010~dfsg.1-3_all.deb Size: 52168426 SHA256: a33f373c13f9142a6d423af68ff01331166451c04e51192472cc1736190706bf SHA1: 4b9731f75628adf68a2e892314976c892bf0e9cb MD5sum: e5f7efb634ddadfc7f5387d930f62872 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 11288 Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4010~dfsg.1-3_all.deb Size: 10423480 SHA256: bc4fffabe5ca9a2080d9a2532ade99a53a6c634dddf0c74b2effb107c1c28bff SHA1: 24a099d5790918edb44830153cea6c45a2d6f206 MD5sum: 1bfc3e98c3e6d7026ceafa67d7182426 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: swig Source: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: i386 Maintainer: Torsten Landschoff Installed-Size: 5236 Depends: libc6 (>= 2.8~20080505), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Suggests: swig-examples, swig-doc Replaces: swig1.3 Priority: optional Section: interpreters Filename: pool/main/s/swig1.3/swig_1.3.40-2~intrepid.nd1_i386.deb Size: 1217292 SHA256: c0d714d2941b1b494ccf29c81958bd4cdb4c351de616f2b209fa56a53523a684 SHA1: 875bad64928eb2a2097a178124c2eaa2f2c03ae3 MD5sum: 7dc70b603953859f8ef4b83b169de351 Description: Generate scripting interfaces to C/C++ code SWIG is a compiler that makes it easy to integrate C and C++ code with other languages including Perl, PHP, Tcl, Ruby, Python, Java, Guile, Mzscheme, Chicken, OCaml, Pike, and C#. . Swig takes a set of ANSI C/C++ declarations and generates an interface for them to your favorite scripting language. Package: swig-doc Source: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: all Maintainer: Torsten Landschoff Installed-Size: 5956 Suggests: swig Replaces: swig1.3-doc Priority: optional Section: doc Filename: pool/main/s/swig1.3/swig-doc_1.3.40-2~intrepid.nd1_all.deb Size: 2298848 SHA256: 997b91b92b2b1fcffaed5f3175e2a965400956bb0034956b697172d14d9b6710 SHA1: 96642f498cb8d8ea62e6dcec57530e986a04157d MD5sum: 241aac7bfd415c001a401cce7be6311b Description: HTML documentation for SWIG Contains the users' and developers' manuals for SWIG (Simplified Wrapper Interface Generator) 1.3 in HTML format. Package: swig-examples Source: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: all Maintainer: Torsten Landschoff Installed-Size: 12552 Depends: swig Replaces: swig1.3-examples Priority: optional Section: interpreters Filename: pool/main/s/swig1.3/swig-examples_1.3.40-2~intrepid.nd1_all.deb Size: 1010928 SHA256: 26b318d8706b62ad883a358f55a599d08d74e9e46b1da86ec825e93abcf2c941 SHA1: 936477339d3fde796c9bb7f17287d118b166caeb MD5sum: 9c50c87e4f827ff579794483f047eade Description: Examples for applications of SWIG Contains examples for applications of SWIG, a wrapper interface generator to integrate C code into scripting languages. Package: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: i386 Maintainer: Torsten Landschoff Installed-Size: 40 Depends: swig (>= 1.3.0) Priority: optional Section: interpreters Filename: pool/main/s/swig1.3/swig1.3_1.3.40-2~intrepid.nd1_i386.deb Size: 11434 SHA256: 427894396d553edfc1de336e8b76c6c82e69d2d360e887ba5f324b2c8aa5a7bd SHA1: efb2350ad30c7e2a419ba728fb5c8a3281f7db55 MD5sum: 6198f850d9ac7c31d5d541ed832b49b8 Description: Generate scripting interfaces to C/C++ code SWIG is a compiler that makes it easy to integrate C and C++ code with other languages including Perl, PHP, Tcl, Ruby, Python, Java, Guile, Mzscheme, Chicken, OCaml, Pike, and C#. . This is just an upgrade convenience package. For the real stuff look at the swig package. Package: swig1.3-doc Source: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: all Maintainer: Torsten Landschoff Installed-Size: 40 Depends: swig-doc Suggests: swig Priority: optional Section: doc Filename: pool/main/s/swig1.3/swig1.3-doc_1.3.40-2~intrepid.nd1_all.deb Size: 11284 SHA256: be73ed4e84d760de36b499250efeddb409352c87afe3b4985d7068f02e4782eb SHA1: 340bd0b2b9abb098520e8c2153d2493b641328dd MD5sum: fa4750f1f9c192805f18c3f430b8de6a Description: HTML documentation for SWIG This is just a convenience package to make smooth upgrades possible. The real stuff is in the swig-doc package. Package: swig1.3-examples Source: swig1.3 Version: 1.3.40-2~intrepid.nd1 Architecture: all Maintainer: Torsten Landschoff Installed-Size: 40 Depends: swig-examples Priority: optional Section: interpreters Filename: pool/main/s/swig1.3/swig1.3-examples_1.3.40-2~intrepid.nd1_all.deb Size: 11284 SHA256: 342ce8d212b55e7ddf5cc972e49e84b988d5735c68af646843365ab44d1667f6 SHA1: 381c82474f11b3fc03dd953368fa68892f5f6756 MD5sum: 64d256329b6b9f09843fe7d558636013 Description: Examples for applications of SWIG Contains examples for applications of SWIG. These examples are for the 1.3 release. . This is a dependency package for the real swig-examples package. Package: via-bin Source: via Version: 1.6.0-2~intrepid.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 900 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~intrepid.nd1_i386.deb Size: 170092 SHA256: 26547d2756e59b8d1bbe5f937b79a0d102d28a7765caa761a12158bf4f5ef82b SHA1: 73fcbc766e647a1ab8226bf02585fb8db33e5a88 MD5sum: 39dade74a921ea2f354b51c0d38143c7 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.