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: amd64 Maintainer: Michael Hanke Installed-Size: 532 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_amd64.deb Size: 159478 SHA256: 20fa212edde65ff3be65bd6972b1602761d9febec958f119b93f7f747213c1f0 SHA1: 74a936f423fe2ec80eef9e6de9e87917027221fc MD5sum: 54c6800f3bf5ee829debf27091efffbb 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: amd64 Maintainer: Michael Hanke Installed-Size: 4192 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_amd64.deb Size: 1524374 SHA256: 3786ec98370d3f7d4821123e9e889a5e2acd7f7d2598e424a24f4348af5674e3 SHA1: 7e5a4951c0449db9a0e05ad6c5f4d74dd33c3a96 MD5sum: 61fdadae2c3b2981fb430db97fb2f02c 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: 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~intrepid.nd1_amd64.deb Size: 796812 SHA256: 982cb23cc1a5681aae7b6d93fd4625a68084f620a415959723c19e6778f82add SHA1: 3e1114fcf79c0b36145fc23009eb2e9569282e6a MD5sum: 7a87aebf551f632b32df101418043960 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: 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~intrepid.apsy1_amd64.deb Size: 119760 SHA256: 29f7f873e87c669223f0f2b886161674a0adc1113575908348e3a86049c27d11 SHA1: 297ea79544450a66b28741919bc83d5897a2dbc9 MD5sum: a14ef0b7628000622e4aa044ace8519a 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: amd64 Maintainer: Michael Hanke Installed-Size: 616 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_amd64.deb Size: 167800 SHA256: 914af4d4dea4a5a6d9242e902cfba3b1ccab984945c10e5f8fffbc014d43a5e7 SHA1: 18b06700b0cd8e77ae4b5b8b20824ef09a2e22d8 MD5sum: c9cfacd7dd30f9b99e2d3268cc4c9da2 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: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 21148 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.0-1~intrepid.nd1_amd64.deb Size: 4066614 SHA256: 41cf13ed2106e464f8ce71cc567d1522f23d5a4339615ce2dfc76f7abf64f1ca SHA1: 142fefd307edcac59297b986676d1d3bea2be330 MD5sum: 1c4755d05962850bf7096b1d6a447fae 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: amd64 Maintainer: Michael Hanke Installed-Size: 916 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_amd64.deb Size: 243456 SHA256: 03e67c6c13dfb07dc6a5437f862177d1ed83554d6831a0ec2f13d754a9fe245e SHA1: 41ce936ce36fc36ae0fc565b2fb23f0d8eec33a2 MD5sum: 78d55097879cf5afe896855d8b577e19 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: 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~intrepid.nd1_amd64.deb Size: 190764 SHA256: 3865e76a82356dc6814ac2305c0677891e37ea289e04ad6824595f3cb081b1bf SHA1: 9c6994625f96936f2abd214a83ee53fb09f7ae19 MD5sum: d2aff84029b4c4a44950075e617eb435 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: amd64 Maintainer: Michael Hanke Installed-Size: 3952 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), 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_amd64.deb Size: 1334844 SHA256: 984a953786b3dd918a646662559efccf56b934b26a3131a0032badf0db37e761 SHA1: 9f20bd4be42abedc18504a37dec0d2db18bbdaf7 MD5sum: f2de1591b6d393e9394dc55d0e206be1 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: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 6816 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_amd64.deb Size: 2255856 SHA256: 37d6bb7e96178c9bd74fa3043ba653ca974eb386d03f7dd2454fde62ce37de51 SHA1: e3a8aa5cb518749060e824bac3fc0f8116ba9374 MD5sum: ec8fd922108bb947f087ff5f5b53da67 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: amd64 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_amd64.deb Size: 62364 SHA256: 988786bb4952154bcebf30e00d3892af68192aaf4342ff0f0fac299114af0cc0 SHA1: 1573584980636b22d587dd076afb28bddeb26be9 MD5sum: 79d17527140b964f381b90531f7f3f4b 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: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 3972 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_amd64.deb Size: 1511050 SHA256: cfaabefda9ec6bdd8f03b097dbfe2e452fc546a800b7254c0503c2d3f4603358 SHA1: 2cde80b4853ae54b0f00ba225aa65d24044c4cb3 MD5sum: 6a6a8e911f453203670f05de67b2d5ee 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: amd64 Maintainer: Michael Hanke Installed-Size: 268 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_amd64.deb Size: 71512 SHA256: cc4eb9b924a8905e8261b34569f127ae77b34ec6cdbf432c647960c4a6bf5a2a SHA1: b369519d77dc751f9618cebb4986969e6974524f MD5sum: 03e46c228303ab85b6793320109b9c1a 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: amd64 Maintainer: Michael Hanke Installed-Size: 416 Depends: libc6 (>= 2.2.5), 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_amd64.deb Size: 92654 SHA256: b704c9ff54da54a441b4cc54ac245de4808f172d3041f83e1cc8f5911a598201 SHA1: cafb33728b3647c5c14a5a0616eeb0653d7d20c3 MD5sum: afe3abcc2c0c59e5ff52d2324e9d5c9b 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: amd64 Maintainer: Piotr Ożarowski Installed-Size: 512 Depends: python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), libc6 (>= 2.2.5) 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_amd64.deb Size: 76832 SHA256: f10c4c4f9fa362c259a73031b410ce09dd2a7f0c1584813cf7563017e8381a42 SHA1: bf91a195bf828cdc041e47f8cacf2be0cd42c4cd MD5sum: 61e6dad011384acda322a091702e3987 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: amd64 Maintainer: Piotr Ożarowski Installed-Size: 196 Depends: python-jinja2 (= 2.1.1-2~bpo50+1~intrepid.nd1), python-dbg, libc6 (>= 2.2.5) 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_amd64.deb Size: 24964 SHA256: 8ab9058f62b4154f1748a99375aa751497d7b8e0a1e6cb200a56afb2fd281f76 SHA1: 83e7da6000dbfa56374d697ddc56291168c9a4fc MD5sum: c17d175257a7b075aca38913a0708257 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: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 304 Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.6), 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_amd64.deb Size: 59852 SHA256: 9576d79b4bfc78a8637b5f0be263c447cd75b69e15133d0e84af485ca3ab0a14 SHA1: c190df84582fa2638978f1c4af92d735d3af0827 MD5sum: eec6158bc247bfe31a20417f6b58ddd8 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: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 308 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_amd64.deb Size: 60764 SHA256: 60aedee748b597dcf6d949f23fe8fa0f777be1ac444c44270d6a625781a1877c SHA1: 0777fbe29d86665f82bf64b3d7bebf1e3251a993 MD5sum: 67f3f89178a0bbd37731955b031141bf 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: amd64 Maintainer: Michael Hanke Installed-Size: 1512 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_amd64.deb Size: 361518 SHA256: 848331c57c0f11b214c4b30b823541e15e751f8cc9666672d330b4eed36bf990 SHA1: a7098d4a4d3c2d90a08dbe8cd7ee7b9443cbb221 MD5sum: a3566725df574a62ff4d53c71087f418 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: amd64 Maintainer: Michael Hanke Installed-Size: 4988 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_amd64.deb Size: 2739116 SHA256: d037dfbba820a71bb5d4c4e9954ae5d542a4d0f4ec4e08715c3e002990760774 SHA1: 973fe234421da429c400bf5119ad08f88a6a26cd MD5sum: 9786d5d857a08ceb4b89e6a63fbf4848 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: 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~intrepid.nd1_amd64.deb Size: 178052 SHA256: 288000ea865c0e2717c263e960086462bea0eb68bd3649503a580e3e5de4cab1 SHA1: 7876b901e4cb0f8f4dc0ee94cd31992a84e02b7e MD5sum: a91aafe966696652a922ac38615c8541 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: amd64 Maintainer: Torsten Landschoff Installed-Size: 5216 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_amd64.deb Size: 1242410 SHA256: 141353d3aeec74e9b73b78c377c37b6876b788f2bcf324cff77afe9e506d32a4 SHA1: 60d5f222899daea838f85e39538f33bb4567c772 MD5sum: 294fb9d0eb93e1862055a418475169a7 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: amd64 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_amd64.deb Size: 11432 SHA256: 96c0594c179337e1611993f98be4643a67551300cf3fbc216941503498acb937 SHA1: f5fa3c1cfa123c8388d147c45e39c1be5e0df13f MD5sum: 0c682ac5bd395802ee87aba2c1e18f9b 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: 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~intrepid.nd1_amd64.deb Size: 190260 SHA256: 8d0cac463e532940fe0c22759273e9d7b1b042b90fa35e22b4014d0aac389d4b SHA1: 7b21f0651b8c7e96d76ef370f5a3ec33ef586a39 MD5sum: 42f424c11cf548cff99b776fd54bef9e 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.