Package: aghermann Version: 1.0-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1547 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp8, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.6), libunique-3.0-0 (>= 2.90.1), libvte-2.90-9 (>= 1:0.27.2) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0-1~nd13.10+1_i386.deb Size: 693058 SHA256: 448752302ede5a4bf8f57e752ac2847bd602a3773e65f844fc29e24f4df9a79f SHA1: a9fb4bd5dccfcbc90c95a2d4b8b891df5adaec4c MD5sum: 746104ddf0a21f509b8e2d6b1e2f1852 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 666 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 279160 SHA256: c8ce9de9a812ea308934d08c87261fd368ab6557736f3f36bf4362bcae0a440f SHA1: 67305c7813ad262d3f29024dc143642962616a3a MD5sum: 0282f6a72360e6f96f416cead29c7f0b Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: cde Version: 0.1+git9-g551e54d-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 811 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1_i386.deb Size: 331278 SHA256: 85b596b11a489d888c4c4088aaba4b14c8d9a1ec46be6c9d58f32f207bc7ce18 SHA1: 18d82f08fd8dfe34bc28a06d63fb740965dd249c MD5sum: 77b89198ce45216fbebf6f976fd64aa6 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 45144 SHA256: 44fb798455b7984994abde260ae28995ec67dff90ede5713d21f554f81f0a2f7 SHA1: 1e99e7b106d1ff3da8e5a3de56bd0c623707b8c4 MD5sum: 15212a6959d1a058fb3d27d8fccf334a Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 7224862 SHA256: b676b82109d135052588444785b36d65fe3e96cd7199cbbb0bd7c2c07d3cd801 SHA1: f9190f6dbe6d6596884363f4aeadd7181991eb43 MD5sum: 06ebb1802f177f2a117f1d51a2213ec5 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: eegview Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libeegdev0, libmcpanel0 (>= 0.0), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegview.html Priority: extra Section: science Filename: pool/main/e/eegview/eegview_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 10624 SHA256: 77e8168cbe8d549fc1c8eebbbf7da8642f47890db8df52a5be4f4253d680b8c7 SHA1: 03acf5b9375f2c4a696282430e3e0bde86c9b9e8 MD5sum: 3ecd76bc07694be2502284cbcb894e86 Description: Software to display EEG data in realtime This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment. Package: fail2ban Version: 0.8.11-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 525 Depends: neurodebian-popularity-contest, python:any (>= 2.7.1-0ubuntu2), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: python-gamin, mailx, system-log-daemon Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.11-1~nd13.10+1_all.deb Size: 176912 SHA256: 8c211a9afaaf4847a4dd50b72622a5c5805f67b19162007df0a746c082617d0c SHA1: b401bf0e26bb45cf9f4721410c8d4c35fc5f2383 MD5sum: 4ff6bd1b562e28c47175467a8fe53d46 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Package: fslview Version: 4.0.1-2~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6017 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4 Recommends: fslview-doc, qt-assistant-compat 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_4.0.1-2~nd13.04+1+nd13.10+1_i386.deb Size: 2287390 SHA256: e70794a50e77e7ee00cb8ce6774664955b4ca9e57f95143e79af0f2e57f95dc9 SHA1: ac00682c83753c18b9d01ca8df7af472a4177d29 MD5sum: e8fa635ecafc39a01d3d2c714404ea3b 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: 4.0.1-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2874 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-2~nd13.04+1+nd13.10+1_all.deb Size: 2346584 SHA256: d18c868829872ad3b67c0902b9dba50a49c1b221a498c79efda662247520d444 SHA1: 0eee7201a822e7f6e330c233f732e29df7e2cfa1 MD5sum: 1fbf262f0226c131b9096afe8705b64b Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 344 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libx11-6 Replaces: libglew1.6 (<< 1.7) Homepage: http://glew.sourceforge.net Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 127170 SHA256: 22b722361705a985ad0d5de03b4fd5284997bb50d3ae0b467b09072c8b400695 SHA1: 0879b335df664550e890b2d002772168beaed1e6 MD5sum: 9cd9a05656c47a31a3db900192e9fb8b Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the utilities which can be used to query the supported OpenGL extensions. Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 9792 SHA256: 0b9a6311f3505e3617a06a6c9c484f2d75b0c5d72c8399f677eda471fc8d0acd SHA1: 68241f8405acc62727278602c524900998fa8dc4 MD5sum: 27174485f0fac376de0ebe388d427929 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11748 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython1x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython1x/ipython1x_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 4486488 SHA256: 6016a44c2c4ebb56d8df6ce5cc15cc7c12ab6d093667f1910829fc12ca964581 SHA1: 7a208528c1a006209745efb2e691c3b1b6770b0a MD5sum: 313e52e500fd07fe87d6e12893fa7fde Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-doc Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10391 Depends: neurodebian-popularity-contest, libjs-jquery, ipython1x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython1x/ipython1x-doc_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 4192434 SHA256: 6c1ed43bf785fc0278365207e66311c6cace48f4631178de5fcdc15fea6431cf SHA1: bd3d87ffc7b305c9db0ca716ad99fdc3c9949ede MD5sum: 120527fda1c679b4b209ed795f3c3a52 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-notebook Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-notebook_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 908 SHA256: 937c26f74dc38685ccda4a8278e7953f3b6c80aaebd36947fd876785a6429e68 SHA1: 34d85abfe2a419d600769382228b62f121a76b9d MD5sum: af008fba904dd966354b267c7819efb8 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x-parallel Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython1x/ipython1x-parallel_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 836 SHA256: d031b9d628624c792764afb15e2e0c0f4f663064bef7b0045edb641106d09310 SHA1: e894ddc3eb3662df68d481f510b7a8251f29be93 MD5sum: 8a22a6f641780b0b77f58a614c4d26f0 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython1x-qtconsole Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-qtconsole_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 924 SHA256: 71f4ce8327f6abb548302e1b70ed8d1ea0c824b0bee5f6b65b8e7d0b19c678a4 SHA1: 89622b1042ff646e64e3334bebb09e4418c144ec MD5sum: 7aefa70e0eeab5e8034b8d0230e5551c Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1323 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 411732 SHA256: 0d292e0cb2091d8ed7e39412581a105e525570302441f0c4c8d9ea8d9a542ba4 SHA1: 0bdb338f7933e8e71820e8dc2b95eb0d14d4301d MD5sum: 3b700bc1a573bacffdf114546aea7190 Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig1 Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 798 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 322824 SHA256: ef4369d3f9c56694c7abbfc21dcfbc09d1608fdcabfe77e7be860b4581758e05 SHA1: 495cd5fd43ebd590acd83a514e30b6ab60023dbd MD5sum: 5cbbcb63e5be3e0e6702a7094684a182 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig1-dbg Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 117360 SHA256: d9d54c0d2247e792972036ff75887ed1aa93e93486b6248fa6754b5292e96447 SHA1: ac3e191921feff9e76a8c9edcc41826369d8a46c MD5sum: 847ab741cf09adf2eebd37be4d7ee86d Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1 Suggests: glew-utils Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.9_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 157862 SHA256: faabf1b8b73d0a211c4100ed1b60d4812d3e9b8b22e11be7e108e68b206c984e SHA1: cc5e5e22cc2b5e85b55e6da42941349a1a79b22e MD5sum: 75c03cc7f1ea2ec51e4d13d9bf16e5c0 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 40100 SHA256: d4faf2f181fd4abef3a81ecf3c6309017e963f6fd4cf0189ffc7c43146e4acce SHA1: 64c1b2af96419358578f392cbeeb4b88aa23eb4a MD5sum: 5cc8acb2dffc49f1ae4e8cf02a3e63d4 Description: OpenGL Extension Wrangler (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglew1.9. Package: libglew1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1), libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.6-dev Provides: libglew1.5-dev, libglew1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.9-dev_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 153232 SHA256: afb5b31af16379d388e47676e605eea84492bdc5f26994bd8f014f001c7db027 SHA1: fe6648a33e8a0c83725335b3ad0af02539a39863 MD5sum: 3cee1e2e203e90b7c27eebc17a58c9ab Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development documentation as well as the required header files. Package: libglewmx1.9 Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 467 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.1.3), libgl1-mesa-glx | libgl1 Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.9_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 141926 SHA256: d1615d9ca20c88dab46453f76048b6dfe779a2de6ba57845ec82350e221763bf SHA1: 430872785a259311e3888e8db871d1310e0fc9de MD5sum: ceb24439bc21190ad5feae6fcf926a0e Description: OpenGL Extension Wrangler (Multiple Rendering Contexts) For more information about GLEW please refer to the description of the libglewmx-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.10+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 32398 SHA256: 41c1e9f63e9d8be0eab0e6e89b44ab06c7f834c1180ff34e189e3d164ee712c9 SHA1: ac4bd2d338c21701c934541b368e74cf898926bf MD5sum: 9d36cd1894d27a58f3c82687249e7984 Description: OpenGL Extension Wrangler MX (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglewmx1.9. Package: libglewmx1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.10+1) Conflicts: libglewmx-dev, libglewmx1.6-dev Provides: libglewmx1.5-dev, libglewmx1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.9-dev_1.9.0-3~bnd1~nd13.10+1_i386.deb Size: 8838 SHA256: bbb82e722cb558fbf8d695bf703ee163db4c2863e40e63d4040bf3818d324d95 SHA1: b8aecccbc9d621d719ef6708c73464445c50bc08 MD5sum: 1a19c1a356688c82cd9341081e035e6f Description: OpenGL Extension Wrangler MX - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development libraries compiled with GLEW_MX. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libdevel Filename: pool/main/m/mcpanel/libmcpanel-dev_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 2412 SHA256: d743962d1f4c8786d443b17305c03df448d2df4c16a79ce043dfb316f7244dcc SHA1: 7111e003add47a9b361591184797a32e1490e873 MD5sum: 3e1e9cc70029d8545b65653940e7bdce Description: Library to display multichannel data in realtime (Developement files) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the files needed to compile and link programs which use mcpanel Package: libmcpanel0 Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 135 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.37.3), libgtk2.0-0 (>= 2.14.0), libpango-1.0-0 (>= 1.14.0), librtfilter1 (>= 1.0) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libs Filename: pool/main/m/mcpanel/libmcpanel0_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 47676 SHA256: eceaf04b0de05a85dbfb73818e74fabc020cfec1fd655f021fb9a1dd80658b99 SHA1: 0b7daf415f411302f5db50b0dab1bb1a01b39bfc MD5sum: d2c6af5f75b4940efef25260207eb74d Description: Library to display multichannel data in realtime This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. Package: libmcpanel0-dbg Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: debug Filename: pool/main/m/mcpanel/libmcpanel0-dbg_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 6742 SHA256: 7416592080f253dfecb28ff0c47648973e1e482df114242ca0c8fcf673edd0eb SHA1: 35ae310558578987f904b91fbc8fc914b8b71432 MD5sum: 7e78934de6febb87bfd091c74191b7ed Description: Library to display multichannel data in realtime (Debugging symbols) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the debugging information of the library. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 174234 SHA256: d63377dec401dd9fbe3bf024f1dda709c6a717401b9489c64f6f639e2f2d669d SHA1: 78560d17d43ed36ab83c6b74cd05acf693baa1d3 MD5sum: 8f8746b0d2a0f04a4443595cd4fa42e0 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 498 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 177900 SHA256: feb61e45b06187a01fabd0a2032ec675df6c08fa42d6d286d15cd793bc89229a SHA1: a1e3d1e17ec3388c54de6f70bdbf4c47e7ff1ca8 MD5sum: 1b9f54a029828eaa76a02c292c5c0ec6 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1178 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 406578 SHA256: e2fd71f1904c9ca41e04300d5199f7c400457a0b9aed0a2767f0c24d50cf2547 SHA1: 678f7b45036375601a9e9084d5f4943aa04afa8f MD5sum: a3a52c331953a9eb337a1cdbc56aa250 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 11955 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_i386.deb Size: 4565618 SHA256: 1aad6471db7eeabbd6acdb082265ac62ed639897953bd6453837ba3ed490afac SHA1: 0e3d70d95300a0b9f3ff4cf50a2397de89213763 MD5sum: 2f42f1e53f1bb3d05b18315e91b0f0e2 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1678 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1664274 SHA256: 68ce273dcde27c573053b0978397336aee2bd4bd411278f9950e11a9aac27989 SHA1: 3e484323149fadfcff8ba1c124dc23cb188c9cf6 MD5sum: 895c3045ff8a360f730cb00692214f7f Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 980 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 735992 SHA256: e5a580a7bae121b13d1e22d622c6de9466ca7e01fe5abc460fe3285906c721f5 SHA1: f39199a65bb18cded064d3123319184a4c9e6878 MD5sum: 92dbcb21cb1674db34d549b65a2c61d7 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.11-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 7587 Depends: neurodebian-popularity-contest, libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libsigc++-2.0-0c2a (>= 2.0.2), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.11-1~nd13.04+1+nd13.10+1_i386.deb Size: 2607500 SHA256: 0b875fd3458c7ee87d3f700ae26c97396e9c5b8cb1ca7de2735e98fa04686eb5 SHA1: 6f4fa93078b42d429f05381637c262e1925efcae MD5sum: 39abf8c112ba426f585f177238ab746e Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.11-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3488 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.11-1~nd13.04+1+nd13.10+1_all.deb Size: 3315566 SHA256: 71442f92e14e7d4a7ede19192c4f90b7b499f2d970d23f243034a52a035cb1e9 SHA1: 93ff9dbf790cd956cdab14959d4a968a5145ba5a MD5sum: d62cbb6f62b76dbb3c632b95ec797787 Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: neurodebian-desktop Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 142 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.32~nd13.10+1_all.deb Size: 115540 SHA256: 9ba5d4dabb6e93f31272b3b486f15ac6b076af64cf23bf39344807b8dfed0d4c SHA1: 28c84332645d7e4341bc5337e9ea93b556a492d6 MD5sum: d68aaaccaf699b6dd38e1882de06e1e5 Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6842 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.32~nd13.10+1_all.deb Size: 6433068 SHA256: aa1c7d670d5242fb0a926b76a4da98688b0241afbd0930920ed750c3fee6db63 SHA1: 0db76d411ca7c35145284885f1beca74c6763675 MD5sum: feb4c2acd0742deb03aa350b145ad9b2 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd13.10+1_all.deb Size: 15362 SHA256: 87323f095aec2a104af3633b311a231531765476441b4e34dd49f40c426537cc SHA1: 6204775b5aee5af8692750f2011b1311cb16c0d5 MD5sum: 3473a9e49831da14507f033d87a05481 Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd13.10+1_all.deb Size: 7626 SHA256: 971b8c7f9c290670165b5b4480681aa056ad296d0a66d4b7f5b13699f898dcf3 SHA1: 4520e7bcbbdedcf856195ca443fef0bc0e14a99f MD5sum: 84091b28d29885a610724d371af9321c Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.32~nd13.10+1_all.deb Size: 6838 SHA256: eb7c13a98d2d0e64a57475dfb1af249c082531254bcdf62b676c43f2198918c9 SHA1: a98d5388ac8f622a3e72444192feb4e72a24f744 MD5sum: cf62e0d246ae30891e4df6332e4e3ed3 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2133 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.3, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.6-2~nd13.04+1+nd13.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.6-2~nd13.04+1+nd13.10+1_i386.deb Size: 470460 SHA256: 6442cca8a94eda85dd3e8e2e554c9c019a74f3b001ef20ad1dc2341df3221d2c SHA1: 2f3623161e0cf8c4db6711aa7186baacc07b17aa MD5sum: 711a01f34a0b76cb997b573b600351f6 Description: convert 3D medical images to DICOM 2D series Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package includes the command line tools. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 606 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.6-2~nd13.04+1+nd13.10+1_all.deb Size: 615226 SHA256: 0f0a456de3bee8393c788a8e386db5850e1114f6d0888aa2962aeaca3285701f SHA1: 1348f2d5aa245a47b7e921228df9d88801ea0037 MD5sum: 56b8ed8c1d235d57922f2fbda44bf0ed Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nuitka Version: 0.4.6.2+ds-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1904 Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.1-0ubuntu2) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6) Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.4.6.2+ds-1~nd13.10+1_all.deb Size: 509766 SHA256: 899e9ef6f5bc3fae92f6c44b2a1fe21dea3b2f8160f5e44749b498dad0d9ea0a SHA1: 010f177362353b9fc10962c7190205f52d83f549 MD5sum: 64fe93bc44017c8327d194d5537d15de Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: numdiff Version: 5.8.1-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 872 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.8.1-1~nd13.04+1+nd13.10+1_i386.deb Size: 607480 SHA256: e2ff69bc8bf13cbd3383c9f98ffd6b2e215a184df948f0717965e33e215d4a81 SHA1: 5c0616b8f7c083760626d6f83d3b5212fafe224f MD5sum: bc43f28dc80c73236e7a21bfdf19925a Description: Compare similar files with numeric fields Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 66 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liboctave1 (>= 3.6.2) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 22766 SHA256: 3b9a41c1a759c67968ecf14fe0c70cd16ad09716d653f9f4050d7bfd14da19bf SHA1: 403c4d58bba11fd5ad4480124f1a1c2269bcfc03 MD5sum: 9818052424039579e2220afa949783ca Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2627 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.1 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.9 (>= 1.9.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), liboctave1 (>= 3.6.2), libopenal1 (>= 1:1.13), libpciaccess0 (>= 0.8.0+git20071002), libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.11.20131017.dfsg1-2~nd13.10+1), psychtoolbox-3-lib (= 3.0.11.20131017.dfsg1-2~nd13.10+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.11.20131017.dfsg1-2~nd13.10+1_i386.deb Size: 864280 SHA256: aeb00b5cbaaa6962ff7ef93497c5782fb8e8a759b9b9fa7ae5f3991ec04b060c SHA1: f8385c917decec6264461f8dbb352a4cc4cbace1 MD5sum: 7a32cc79d22936fa8378f93d1dc95e6b Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: opensesame Version: 0.27.4-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26639 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd13.04+1+nd13.10+1_all.deb Size: 25359292 SHA256: 7eb6ad30eac4d0899910debe19d8f7d67bc93d31570781782b9c297f0ed84053 SHA1: 1f09336470b48636de42f67e545284e24f6b15ef MD5sum: 076b71a8a142d25cbc32e85c9e11720f Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49635 Depends: neurodebian-popularity-contest Recommends: subversion Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.11.20131017.dfsg1-2~nd13.10+1_all.deb Size: 19937316 SHA256: 1d633396593cd68aee1f7aedfd2f627c93fe031b87bee46eca446b19e5dbbc30 SHA1: e91de726712bc8e2c5710b1afb72e7e533c053c0 MD5sum: 37b535b8bc0512f543a8b4b06df40d98 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2139 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.11.20131017.dfsg1-2~nd13.10+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.11.20131017.dfsg1-2~nd13.10+1_i386.deb Size: 774968 SHA256: 6dd25c219390b8276b6e99dee661fc2ad284637b0b1da9aed746c09f3800105f SHA1: c807c4740e3d67894a76b2beee0f90ebc0787d3a MD5sum: 70531d2fb5086718949c1bd05a2a71d2 Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good, gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.11.20131017.dfsg1-2~nd13.10+1_i386.deb Size: 64348 SHA256: 3c4f38beb3c4a2c870fd54bbc12bb48828ecc7cbc3ffd56da345a89460afd492 SHA1: 2f448d1e2959bf212d85afbcf0740868de07298e MD5sum: 9eb94eb9b44627cd09220e9cf38315be Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 190 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 54100 SHA256: e2c7c82239c500ae73bb2f0a3c717541e995f62a14aaa64cd5a0e82389881500 SHA1: 326b9104e3398e16880463f4c94ea0a3fbc7e467 MD5sum: 69aef9eab0d719de09feab76ab0e3b58 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2336 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.1-1~nd13.04+1+nd13.10+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 549212 SHA256: 988ae070c4a1f6ff509598736733a666ccf337407b9f1b54fe51dcc41f453071 SHA1: c0d825559c7fa6cc94df99326cd0bf135b9af3d2 MD5sum: 19b10c71f6878e6e0ca5eea1637284fe Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6810 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 2247326 SHA256: 02613c13a722df13156e9ae18dfaa9328810fca303950ba19a1356da2a77a3a7 SHA1: 4341f8754a618702eb2f745017fc50c57b88b2e6 MD5sum: 90d9953badd70e123284cef6b7fb2904 Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 129 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python-support (>= 0.90.0), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.1-1~nd13.04+1+nd13.10+1_i386.deb Size: 52174 SHA256: c06061c2ead4c48c1856d7b409bef07d484df73aa5d72a73f793f14ba2bf818d SHA1: b3ad42a74fbc0516a47e0b43e2baf2a4028af47b MD5sum: f9ee2ae094f4ba15bc462c59a7252968 Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-joblib Source: joblib Version: 0.7.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 182 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.7.1-1~nd13.04+1+nd13.10+1_all.deb Size: 54902 SHA256: 8da3ca02ba5ac7b0ef34f0b086d3e687788a3ac689f9d9ee53d36ec03c720928 SHA1: 89ecf1f16e6ef9b552359f960e5a4ebe10c3a8fa MD5sum: 896e7ee9f14eff60a67380bde75474f3 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1495 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-scipy, python-libsvm, python-joblib, python-scikits-learn | python-sklearn, python-pp Suggests: python-py, shogun-python-modular Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 478670 SHA256: dcbf8dcbd35c93951698aa8a700355c7f7df66000b6e7e4b42432fef2a273b63 SHA1: 47eb8ef49afe92e183de028ecbe170ccc8227fad MD5sum: 3e08fab66beaacec7b7071b569c74ded Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. 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. . This package contains MDP for Python 2. Package: python-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1481 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libopenmpi1.3, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.3.1+hg20131106-1~nd13.10+1_i386.deb Size: 476578 SHA256: 7d71c9816d696051b5da0503f566041d16c319d559d1c36dd6a09bc55e0bbb3d SHA1: 9266b79a418210045b62bbbeb5ac222caa815c39 MD5sum: 2953d1c91388aa350d00d024e4c59588 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3490 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1_i386.deb Size: 1190708 SHA256: 0b8dec8e62c1d9d65bcbe93dd6e9767fbe1d47215cfeb4f0ef0ad724169994b0 SHA1: 0b914ff6aae512c3ace6305e4944f5dc2ee6f0de MD5sum: d8116997969cb1e9521bc7414c2050b8 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 256 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.3.1+hg20131106-1~nd13.10+1_all.deb Size: 73120 SHA256: 0b134f816eac4329b2752f7b2e16c6956ecd2ffc949074ee1c9eb390675b9e18 SHA1: 81d29c74376e92ec5c3386727d44258ffba85f8a MD5sum: d041dee2f5707ed612450c5d7b65f545 Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-neo Source: neo Version: 0.3.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2485 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Suggests: python-nose Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.3.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1441986 SHA256: ec381fea8a1c2ad6d8301f88c0ca4362cbbbab180c6e618772181f5b4055fd62 SHA1: 7ae0814b66bf4f821fbb042de12c70a6cd53b3e0 MD5sum: cfd02e2d5a37dcf504472f5f31e11f67 Description: Python IO library for electrophysiological data formats NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples. . NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab). . Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement. Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd13.04+1+nd13.10+1_all.deb Size: 32584 SHA256: e38eecc0a3733f22718924755061092da20b4ce592bc1f0044cc0fcd3b5d946e SHA1: acb8d58022eca092a686c7665b5225fca8074794 MD5sum: 3eedb70c2ed5b4a73f58c6b2981af4f0 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Provides: python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 1816464 SHA256: 1e268bf6e0aedbb094d99515235bca7859435018effc35b32c1ad61bc8f45576 SHA1: b446856aaabf44b569c5fb168697b97baafc6fb2 MD5sum: 9fc3310c254316621359200032f71b23 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Python-Version: 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2446 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 441902 SHA256: 024cc31c57fad25b7ece5bf111183562ed9f306c69b9c615ada8252c8ae51f5f SHA1: 34c515cf5d1ec4eda26a1be813c65d420e3f22a0 MD5sum: 282caebc75ef0933a993491196a60143 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-openpyxl Source: openpyxl Version: 1.7.0+ds1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 452 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose, python-pil, python-imaging Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.7.0+ds1-1~nd13.10+1_all.deb Size: 91942 SHA256: 45e03738ea43ee24a77af63a0910957f19fed443bdb9fa5f0fbf8d0505002c43 SHA1: bb8bbd20152df002810b7998237cdb1ef04c7a73 MD5sum: 5dc3c2964ab771ebebbd199b4b15c60e Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-patsy Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 542 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.2.1-2~nd13.10+1_all.deb Size: 141566 SHA256: 129dbb8c395d3ec89e03e9a07c950a52657450af33b3a29987f9643a54ca5427 SHA1: bf09927d1ada6b8c4fa217cb8931cff0a5f27b98 MD5sum: 1e7166dbc44ab5325bf9e4c1bafe79c0 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 827 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.2.1-2~nd13.10+1_all.deb Size: 271938 SHA256: 961ceeb48ffbeaaff905d26aee5fc323e3f1b06cc466cd8a349f03daaf930aed SHA1: 553e1c06cd178a1c78962fcce0903dec8d2a5e5a MD5sum: b31d6af765cda6ad2f0ff8ff085917cd Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1316 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd13.10+1_i386.deb Size: 353644 SHA256: 509dbe4624d5057e3613c91eb3d372c16e0b45708df845743d7a123d1dad6a5a SHA1: 4f87aa4e3fb79b1c21c059c40b6218372daded08 MD5sum: 01c265886072cc5d8056d3934bbad992 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1_all.deb Size: 818248 SHA256: 9ce8e6041a5deeccea8c28454166623b53d9a571d442a63bc8844c07dd698293 SHA1: 90dc97067b797c017c9da331c41ed24072f8d156 MD5sum: d3ec7da2336f2e9e5ab0cff98c32ebaf Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 175892 SHA256: 0490096bb6a4e6d5ed2ec0e77261346c947d46d28d86acd3bb617c35ad3f10d2 SHA1: 0573a0e1d66e53f5af548774aae5578cc3346cc3 MD5sum: 908111812c3b5221360aff3852de45a8 Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1500 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 427706 SHA256: d03e698a45976faffb1058629ccb887ed04191cb72e2cb783550e9b165e66c72 SHA1: 7c678a86e4b05e78b760de389f5332ee272e0497 MD5sum: 3f6fae2bd1d8079747fe1264b2994b29 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pyxnat Source: pyxnat Version: 0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 862 Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 190426 SHA256: 5854904257cb3119ee3d4389a93ef91f6d0b09cb8761ad8202ad2871c93c79b5 SHA1: ab34bd5639fc33e6891167d65f60d00d368405b5 MD5sum: 3e607b3d81f724a53cce9d8e07b15a74 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-scikits-learn Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 33394 SHA256: c5c4921959294695cc1786c21f6a4221e9643c4a37dd2eb00c4fde018b09c98e SHA1: 69e189ae57b2d9d71d6163d3cad67ac43cc41b07 MD5sum: 3d82217021f148a186e7a70eabaea5ad Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scikits.statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, python-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: oldlibs Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 5690 SHA256: 32c363d5c9c614e8dc79f3e4416b5f5f130a1a14bc01a655340725b9debc7732 SHA1: 31cc26d464f24154400ac5af0077098c538e3903 MD5sum: a0418afa93e68377deca41d04268bd03 Description: transitional compatibility package for statsmodels migration Provides old namespace (scikits.statsmodels) and could be removed if dependent code migrated to use statsmodels for clarity of the namespace. Package: python-skimage Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6267 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-skimage-lib (>= 0.9.3-1~nd13.10+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-imaging, python-pil, python-matplotlib (>= 1.0), python-nose, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.9.3-1~nd13.10+1_all.deb Size: 4538212 SHA256: 38ce12bcda96fb048603a041bf97348639c933fe350844078531e0b0b0325e8a SHA1: 1326d280a0d3bd379aeabf6d2fea67d8384b150e MD5sum: ffd316ff9cf30d8cd16d769688403f46 Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 17726 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.9.3-1~nd13.10+1_all.deb Size: 14620090 SHA256: 01aafb0fe1ee85f69bd722c23a4b72f003261bd8511eacfc811590bb5249b116 SHA1: f049087ae92a499a52955ad443bbe99b6e0344af MD5sum: 1f9af2c36987770895b8dc2ca67b25ac Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5180 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Recommends: python-skimage Provides: python2.7-skimage-lib Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.9.3-1~nd13.10+1_i386.deb Size: 1844874 SHA256: de0e148e7a1c6354312d7bffaf69c56aeb47cbade5e276493af2cb450924a69d SHA1: 5c834242b1d0ec261ad9b02ae2dd55300cc33cf7 MD5sum: 957cf506b04794413de7629c197e9a3d Description: Optimized low-level algorithms for scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 2 libraries. Python-Version: 2.7 Package: python-sklearn Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3549 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn-lib (>= 0.14.1-1~nd13.04+1+nd13.10+1), python-joblib (>= 0.4.5) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1103724 SHA256: e9dd3918afc487965fa705fcf6833913aeab546ec8360f0f7dd40f476e96e382 SHA1: 907583b96f7ca554661469323cdd9d604f0a31be MD5sum: 682700752ca3096fbfef096744e44581 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 579 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 190084 SHA256: a8ff6e017748e6a98c998dc6f9967700c97ad590da834c76fe4f1f340340bd35 SHA1: d84325dd92092e8afc55efd278b283734b37de2a MD5sum: e613e6e4a1d3fd2bb50f2d8d7c0ac6db Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3488 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.14.1-1~nd13.04+1+nd13.10+1_i386.deb Size: 1400714 SHA256: a39b98db0cf64168d961decd416e7467b85430c1ef5c68c301492dfea716a770 SHA1: 27065b04a72bfb88d780a7421242bb79382ac467 MD5sum: 2a83e3f9c23b97e98036af80e6804b65 Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-spyderlib Source: spyder Version: 2.2.5+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4009 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), libjs-sphinxdoc (>= 1.0), libjs-jquery, libjs-mathjax, python-qt4 Recommends: ipython-qtconsole, pep8, pyflakes (>= 0.5.0), pylint, python-matplotlib, python-numpy, python-psutil (>= 0.3.0), python-rope, python-scipy, python-sphinx Suggests: tortoisehg, gitk Breaks: spyder (<< 2.0.12-1) Replaces: spyder (<< 2.0.12-1) Provides: python2.7-spyderlib Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: python Filename: pool/main/s/spyder/python-spyderlib_2.2.5+dfsg-1~nd13.10+1_all.deb Size: 1847912 SHA256: 5901bcb679c7ab73afcc6a5ba4e91c7d8e5f0b26e89da7dfc808ebd2efa321dc SHA1: fd5f1fc3a2f2efdd2910acf381322602cd2ae029 MD5sum: 50f033bac3cde622865ed80cb0137101 Description: python IDE for scientists Originally written to design Spyder (the Scientific PYthon Development EnviRonment), the spyderlib Python library provides ready-to-use pure-Python widgets: source code editor with syntax highlighting and code introspection/analysis features, NumPy array editor, dictionary editor, Python console, etc. It's based on the Qt Python binding module PyQt4 (and is compatible with PySide since v2.2). Package: python-spykeutils Source: spykeutils Version: 0.4.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2018 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-quantities, python-neo (>= 0.2.1), python-nose, python-sphinx Recommends: python-guidata, python-guiqwt, python-tables, libjs-jquery, libjs-underscore, python-sklearn (>= 0.11), python-joblib (>= 0.4.5) Provides: python2.7-spykeutils Homepage: https://github.com/rproepp/spykeutils Priority: extra Section: python Filename: pool/main/s/spykeutils/python-spykeutils_0.4.0-1~nd13.04+1+nd13.10+1_all.deb Size: 401644 SHA256: 602a18a5f0d14a20169f4ee7aed21ce25645fcfe8d8668731c99a71b25f1b2b2 SHA1: 6a95e964f341f0950776a46e9abad5cc30a36c82 MD5sum: b1e989f4caccc9d2ef07a86391511353 Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20496 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd13.04+1+nd13.10+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 4690538 SHA256: 38a545728cb1df2d44d1fc3579354ddfe8b89c5f207ece0cd3b2b68175730d29 SHA1: 95347b8acb0ef160eea8eb223ef7ec8d4d46f0ed MD5sum: d7b2743076ae1cc2f1aadfa920e3b4ec Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31202 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 9240594 SHA256: afc8c22ea8bad165091cb11c971caaf688a39748726afc7430379266cbd8220a SHA1: d7f880340bf05c73be55fe618e1ce0706681724a MD5sum: 8a8961c09b31992954ac76ce98daf033 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 767 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python:any (>= 2.7.1-0ubuntu2), libbiosig1, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libhdf5-7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.2.1) Recommends: python-matplotlib, python-scipy Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.13.2-1~nd13.04+1+nd13.10+1_i386.deb Size: 275952 SHA256: c144487286bfd5d5477d353b383f50dfeac154f1c644eac3cf315e3bb4a5b3b6 SHA1: 2e484ab762e1761588c31f97c87a6ed132be0563 MD5sum: 2c23b2030de352042d78fd49a88ae327 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28156 SHA256: 50ddfd6a338724eef65c70fdf5accda6cb4138a4a880812d575a3a24c82e0f4e SHA1: 3dd5e53ea0d12307cf09854ee4857f26557ed6e5 MD5sum: 5e15b6ff76d04fb48b8d45537ef67a97 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 1666 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 339040 SHA256: 97c1985de0e00173ddd21e9d1a13a0858ca5c7541e7c16ae45e53d2edab7b9cb SHA1: 954eccf9a73f90ea9f4b11c29042d4b1b0fd01ab MD5sum: 60325464694e33ed1d5e8f09594cb184 Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python3-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1457 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 472732 SHA256: 34d326fd987ac56b05616b45fdf1a1feee5c3cee4851ed34e871d9a8ef1ddf49 SHA1: 0191963e9dfae4b7b3dfe58d707a3114399d19f9 MD5sum: 2601097ca9fcd09b10342a784917d739 Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. 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. . This package contains MDP for Python 3. Package: python3-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1444 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libopenmpi1.3, python3 (<< 3.4), python3:any (>= 3.3.2-2~), python3 (>= 3.3) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_1.3.1+hg20131106-1~nd13.10+1_i386.deb Size: 465016 SHA256: 0ca117351c928d8740c401fca845080e8fdc1aa81114a1085142a25f7ed74437 SHA1: 5b565147357d90ef05103bc3ef6691766e3d952b MD5sum: aec489b00a176f20c1d807f9db934299 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3492 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3.1+hg20131106-1~nd13.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_1.3.1+hg20131106-1~nd13.10+1_i386.deb Size: 1185086 SHA256: 3d8170a807814176ec60503e3aabff76d5b6f3acbef3b162f59c5f4ee7879e97 SHA1: 2fc3a602317e40ed067a1b4dc17065785ce696a3 MD5sum: 85d3440d74edc0a591d8d429100600c9 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python3-patsy Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 535 Depends: neurodebian-popularity-contest, python3-numpy, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.2.1-2~nd13.10+1_all.deb Size: 140384 SHA256: 240fefb22e743b5a444acad849e63ae4701920fb3c7fa6cba885e0f9744ec338 SHA1: b0dbd969743a2cc6d89044af4e6575fc21f0cdef MD5sum: 3350a251e0975db1c5b799599cf525c1 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-skimage Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6161 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-skimage-lib (>= 0.9.3-1~nd13.10+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-pil, python3-matplotlib (>= 1.0), python3-nose Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.9.3-1~nd13.10+1_all.deb Size: 4529352 SHA256: 1954d095c5dda861a9a16d40bc290dd87d9c62b5a3ebffed61bca0b3940dc3be SHA1: fec0293ba0f1d43be9dc26b2a221cc88fddb4397 MD5sum: ecd693c691939be0476ffd23dda19fa6 Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-skimage-lib Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4889 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.7-0~b1), python3-numpy-abi9, python3 (<< 3.4), python3 (>= 3.3), libc6 (>= 2.4) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.9.3-1~nd13.10+1_i386.deb Size: 1701454 SHA256: 81b69453d1ee623362b518aaa0c27f8cab1351cb4a596cf773fb0aa59e649c05 SHA1: 24d663231a483027f82dd8676a48892d5611af1c MD5sum: bdf16f5fdad1103ab299f78f83d885ac Description: Optimized low-level algorithms for Python 3 scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 3 libraries. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3034 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.3, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4, nifti2dicom (= 0.4.6-2~nd13.04+1+nd13.10+1), nifti2dicom-data (= 0.4.6-2~nd13.04+1+nd13.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.6-2~nd13.04+1+nd13.10+1_i386.deb Size: 653820 SHA256: f0d0b7e139b79bf69ea2ddb910860a80f835eddcfb50b129cdde9c6cc359ba66 SHA1: 5a0e812fd7192e4b00168638f1e0eff5b78d32cd MD5sum: 24389ebfe990d4068bc1eed32e5235a2 Description: convert 3D medical images to DICOM 2D series (gui) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the Qt4 GUI. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 10744052 SHA256: 05f7ef0de3af1f49c7f7dafba91b9d8f5f082bd48ad7acd365a89a105fcd6c71 SHA1: 829ef9f220b3a9595b3acdb7ada1bedcdfdbc378 MD5sum: 137a219ff42452e9439fe275cb949cc3 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: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 52166702 SHA256: 85b2c5e9081fd7cf506defb5327413d0222f01f3b7e6fd959e5e2ccf8d83000c SHA1: 8a53b81d37062647c56fac6117a589fb776bbac5 MD5sum: 9d6cae39f3455ec2cc5a2f3ccf8b002d 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: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 8990912 SHA256: a35cf1eaaf17c77bc2c148da711ed2d386131f25f4ea98c326b36ee3a0867e07 SHA1: a21337c1d47d0ae2b39bcabb477ecbdf0fdff4f0 MD5sum: e7247d37c03ce8eafa3ae5e619c752a2 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: spyder Version: 2.2.5+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python:any, python-spyderlib (= 2.2.5+dfsg-1~nd13.10+1) Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: devel Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd13.10+1_all.deb Size: 36094 SHA256: 9b421cf2dd4baf6337fee59f8d4de941497d7c115ba7a078fbf22c0adda8a839 SHA1: e2fd2c04cce115e7fa8cdbb9005c75039af9f1fa MD5sum: 140f3abee79c6f9f3d6469c93b721c9a Description: python IDE for scientists Spyder (previously known as Pydee) is a free open-source Python development environment providing MATLAB-like features in a simple and light-weighted software Package: spykeviewer Version: 0.4.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1120 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.0-1~nd13.04+1+nd13.10+1_all.deb Size: 575306 SHA256: 959cbfd23cf8d7761d77fac41530d08a428c4f4a773f411acb5e26ecb6e5d507 SHA1: c639d49e4fe954f60c40dbccb74e9c158da58912 MD5sum: cb9540ab965b6ba06bbab01ed8f3d8b3 Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28850 SHA256: 2885d99daf2891a6f2fe488f25d5f54002ff6d6df0252f5e946ceff1f20e452b SHA1: a9e67198cec5f15cc2bc910b9a9fdbb90f7f40ac MD5sum: 505b20b36e42d72d4d7ca1bc051d90b5 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2265 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python2.7, python:any (>= 2.7.1-0ubuntu2), python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.13.2-1~nd13.04+1+nd13.10+1_i386.deb Size: 825392 SHA256: 488cb8202bb55317a50e5ca9b85edcb114143d71a39cd8eb8780a04ea1b95652 SHA1: 0dc3819536207235a110e9a05e74872807a38bd3 MD5sum: 052c13df50ba6a5d8e2fd13ff3ab39cd Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13968 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.13.2-1~nd13.04+1+nd13.10+1_i386.deb Size: 5226412 SHA256: 3c853ad23fc843f029bae72927d5ae69ce544129f569a26b94dda2874f544b1a SHA1: 5384436085840fa6e92e600b029441558596585b MD5sum: 0518d5d6a5605384da76438aba93e1f6 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 99698 SHA256: 40b0868fbb47a9758a535769ae6eaac9e3ec55f0c3b39557f43303f5fe8dd0b3 SHA1: 3ca2b3698fcbc13058665807cb8ffc9ad4fd25d9 MD5sum: a6c94efec638cee547260e58486ee71a Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 280 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 63168 SHA256: 792e29b354f6931dd256165163265c66722f40401803b0909bb4dc3ec319e909 SHA1: 05713a4b99aae7f3e6c30546289c04845ac6784e MD5sum: 650d2c43b7a7e0f4d776e32009419230 Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3836 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_i386.deb Size: 1482436 SHA256: 5eeba2eca37e982aba53f30b7a445ab2e7dadf56e0a0ad1f03c09652ed620dfc SHA1: 26da94e9e984ae34231a0f5c11998a310bd2f398 MD5sum: 3bcbc0c04b27f57f6148f2b664de55f7 Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables.