Package: afni-atlases Source: afni-data Version: 0.20180120-1.1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 109419 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni-data/afni-atlases_0.20180120-1.1_all.deb Size: 98215048 SHA256: b7b30ce4345671d92cb08f939b76de42f81a6839abe3d47dba1db0620fe64e0c SHA1: 792d6506cc866acfa54fc71475f823e686f169f7 MD5sum: deaddf5e6992face9b5edeb62644187c Description: standard space brain atlases for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provide AFNI's standard space brain templates in HEAD/BRIK format. Package: aghermann Version: 1.0.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1544 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), libitpp7, liblua5.2-0, libpango1.0-0 (>= 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_1.0.1-1~nd13.04+1_i386.deb Size: 694806 SHA256: 6338442362e7dc9936b40613e04d9c9c879eb3e1d3c4e42a828e643bb7262333 SHA1: 981c56a1d94f57896178fd8d469da7eb568a5a4e MD5sum: 768c72fc84c2283dc12a334d5386eea3 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 679 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_i386.deb Size: 286554 SHA256: 5446015a9a5f3fcd651c5f2ebdadde043bb8b94c58dd55a7da6101f7846c568b SHA1: 1f757fb6f3a34accb2b54d913209f255e734bc3b MD5sum: 5c5585acc6f228680acdd1fb23209dae 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 803 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~nd13.04+1_i386.deb Size: 331886 SHA256: 902e806c46296216fc9045815ab9d55d8fba1a1f7ece5736bbeb02cbf4dc318f SHA1: aade301f0cb538014b5a002c7c2c8ac0e8789ca1 MD5sum: d2282236f34e4172d4306823f42447a3 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: cmtk Version: 3.2.2-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 22277 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.7), libdcmtk2 (>= 3.6.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libmxml1, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_3.2.2-1~nd13.04+1_i386.deb Size: 6549654 SHA256: cad6b2316da41534d2c7c837598153dfbfd690fcdf93415f099265a42008f8df SHA1: abfba947de8862a822a1adec6851fe1de49fc82a MD5sum: a08ed2198245fff8ca79a93e941b7177 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cnrun Version: 1.1.14-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 284 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libreadline6 (>= 6.0), libstdc++6 (>= 4.6), libxml2 (>= 2.6.27) Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun_1.1.14-1~nd13.04+1_i386.deb Size: 122764 SHA256: e292a3bb725be4ceafde19408215fe49a156041e0a5625ed7d14904a7b0ac54b SHA1: 4c9053cc448b466e72718041094cb9e5b9ff6601 MD5sum: fdae57596bb0909de47637c614ccf5d2 Description: NeuroML-capable neuronal network simulator CNrun is a neuronal network model simulator, similar in purpose to NEURON except that individual neurons are not compartmentalised. It can read NeuroML files (e.g., as generated by neuroConstruct); provides a Hodgkin-Huxley neuron (plus some varieties), a Rall and Alpha-Beta synapses, Poisson, Van der Pol, Colpitts oscillators and regular pulse generator; external inputs and logging state variables. Uses a 6-5 Runge-Kutta integration method. Basic scripting and (if run interactively) context-aware autocompletion. Package: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 13163 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.7), libclassad3, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-common0 (>= 14), libglobus-ftp-control1 (>= 4), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gsi-credential1 (>= 5), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 8), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 9), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgsoap2, libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libldap-2.4-2 (>= 2.4.7), libpcre3 (>= 8.10), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), python, perl, adduser, libdate-manip-perl Recommends: dmtcp Suggests: coop-computing-tools Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/condor_7.8.8~dfsg.1-2~nd13.04+1_i386.deb Size: 4651814 SHA256: 5a681e8c813e45d2486fb2e2c47f06753aa66a0d9fe93a91c1e7e995170da2ba SHA1: 8035d35cf90efdaabf3685cd32fcba36e78aba8d MD5sum: af449510f8eb47cf95f5001f239dfb3a Description: distributed workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package can set up an appropriate initial configuration at install time for a machine intended either as a member of an existing Condor pool or as a "Personal" (single machine) Condor pool. Package: condor-dbg Source: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 32241 Depends: neurodebian-popularity-contest, condor (= 7.8.8~dfsg.1-2~nd13.04+1) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.8.8~dfsg.1-2~nd13.04+1_i386.deb Size: 12171464 SHA256: ca6466e10832adafb2149dacbf22d80796e80791d48d0cd0633ed240aee49ebf SHA1: b65dba7dd5970cc80223b6c5493c8c5737d19603 MD5sum: 0ff13457ed85e8ea0721c9cc810dd9db Description: distributed workload management system - debugging symbols Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-dev Source: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1574 Depends: neurodebian-popularity-contest Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: devel Filename: pool/main/c/condor/condor-dev_7.8.8~dfsg.1-2~nd13.04+1_i386.deb Size: 422512 SHA256: e2b91f99d6fbb1270c282c785b28f85f67bf6a8263ff51e7cd40b04e278d56ec SHA1: be2609cd1c1f66bd8f4858b2103008a2cc0d02d0 MD5sum: 1e1322c512e653d94466e3bf34d454d8 Description: distributed workload management system - development files Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of Condor add-ons. Package: condor-doc Source: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6118 Depends: neurodebian-popularity-contest Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.8.8~dfsg.1-2~nd13.04+1_all.deb Size: 1459864 SHA256: 70fd12501ed9c750b5e148e55bc2335501daaaf6b77ff80dc728277c4a68f4f6 SHA1: c659a0a5d89550d08188b5f04afba63c467db9fd MD5sum: 32fab8d8211465476741f9d83cf1ec9e Description: distributed workload management system - documentation Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: connectome-workbench Version: 1.0-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 36740 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.4), libosmesa6 (>= 6.5.2-1) | libgl1-mesa-glide3, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.7.0~beta1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.3) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.0-1~nd13.04+1_i386.deb Size: 24083546 SHA256: 7085502178b7be10cdb5da1c9d7188ae341708f7833ab17722672d5279e8c21a SHA1: 6b3911f5fb96fe1605ed64af13240d168e429d9b MD5sum: f4b315ddd61b90c8eb1ce7defe2af7a2 Description: brain visualization, analysis and discovery tool Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. Package: connectome-workbench-dbg Source: connectome-workbench Version: 1.0-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 93184 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.0-1~nd13.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.0-1~nd13.04+1_i386.deb Size: 92281930 SHA256: b84f0f481587e0c153b75d9211a12030d670552a0eb721a361f2d020d2dc37d2 SHA1: 0dcb0147a14daa49aebeb89b2db12ece76e4acba MD5sum: 4191fa47f3bde25378765689bbf808b0 Description: brain visualization, analysis and discovery tool -- debug symbols Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. . This package contains debug symbols for the binaries. Package: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 224 Depends: neurodebian-popularity-contest, python3-datalad (= 0.17.5-1~nd+1), python3-argcomplete (>= 1.12.3), python3:any Suggests: datalad-container, datalad-crawler, datalad-neuroimaging Homepage: https://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.17.5-1~nd+1_all.deb Size: 187092 SHA256: dcfab5ab31ab85c685b4439648c3095efb236b34c92eb2f870fc1376dd0dbab1 SHA1: e8a088bc96e73f10444588eede93689410943c07 MD5sum: a4020bc221d05979fe1738d432660717 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+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_i386.deb Size: 45456 SHA256: 4192fd988eb86f76ffd0203b8ea2b8681fbc16c95e3e24340e6157b29949f9ee SHA1: 46a6ca113905327dd09cced37d6afc65ba034996 MD5sum: 488b6f1d862438aec226e6f5a99d3134 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: dh-systemd Source: init-system-helpers Version: 1.18~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, perl, debhelper Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/dh-systemd_1.18~nd13.04+1_all.deb Size: 14646 SHA256: 7fc34fd43ae4d4dd192fe8cb680c62da436441c1288b9067fbbce237dbf32719 SHA1: c1901cac36deb3c11c83b058439c6c20756cd0aa MD5sum: 5137130f51fc0e91c2a515d1f6276bf8 Description: debhelper add-on to handle systemd unit files dh-systemd provides a debhelper sequence addon named 'systemd' and the dh_systemd_enable/dh_systemd_start commands. . The dh_systemd_enable command adds the appropriate code to the postinst, prerm and postrm maint scripts to properly enable/disable systemd service files. The dh_systemd_start command deals with start/stop/restart on upgrades for systemd-only service files. Package: dmtcp Version: 2.3.1-3~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2604 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_2.3.1-3~nd13.04+1_i386.deb Size: 1078164 SHA256: b466e8a468dfb47c99570a0498b93b8f826b6b47d8a4faed1d1b469379a6de7d SHA1: 6c3a0da174b9717c374b7cd04df7c0b5a28aa7ac MD5sum: c360e69cd220246b5e39925110815a6f Description: Checkpoint/Restart functionality for Linux processes DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains DMTCP binaries. Package: dmtcp-dbg Source: dmtcp Version: 2.3.1-3~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 17492 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_2.3.1-3~nd13.04+1_i386.deb Size: 6285126 SHA256: 773de78c6b65e9f5598d1fa1818ac56ca34dcdf7101614ad12a6f8a5e31fa787 SHA1: 9730b96de694aff68e6d6690123c61e7383ccb94 MD5sum: 9b054e9b3fb4e610b71067b46978e47d Description: Debug package for dmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. 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 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_all.deb Size: 7224822 SHA256: e03522059ac09830cf48fd4f41780c0e6fcc7c4d1f3c331f213dbc6743c49565 SHA1: d9675743da0b53adc7682ebacfc6a4922f7a0880 MD5sum: 8a6520b56c5bf5302d61f9eb27b6a847 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 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_i386.deb Size: 10702 SHA256: b72cb86c50b070c6720c7efde62ec856bbf3f45815f7a9f3eb3783cfc8726c21 SHA1: 4d222c0608d0f212041a4f6a9c919d8e216f88c0 MD5sum: 9243c648fdf1e6538a7f3651c307c2c1 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: environment-modules Source: modules Version: 3.2.10-8~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, debhelper (>= 9), tcl8.6 (>= 8.6.0), libc6 (>= 2.4) Homepage: http://modules.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/m/modules/environment-modules_3.2.10-8~nd13.04+1_i386.deb Size: 86060 SHA256: b2c3d8c5c0fd5c70ba1687bd3bca1a583fd47935f0aeb57213b37542a5051a29 SHA1: dc01924c4650c44aae40a069913cb79746c0d224 MD5sum: 0f3606481b183e1f1fef2d33dabebae8 Description: Modular system for handling environment variables The Modules package provides for the dynamic modification of a user's environment via modulefiles. Each modulefile contains the information needed to configure the shell for an application. Once the Modules package is initialized, the environment can be modified dynamically on a per-module basis using the module command which interprets modulefiles. Typically modulefiles instruct the module command to alter or set shell environment variables such as PATH, MANPATH, etc. modulefiles may be shared by many users on a system and users may have their own collection to supplement or replace the shared modulefiles. The modules environment is common on SGI/Crays and many workstation farms. Package: fail2ban Version: 0.8.13-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 563 Depends: neurodebian-popularity-contest, python (>= 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_0.8.13-1~nd13.04+1_all.deb Size: 185306 SHA256: 294b6f3edba827bc5a0cc861678855645e237c3fea6d1bbc57171f52f610d791 SHA1: 9bc959bc346d2f3d03dc349363a7ec7b0504b9d7 MD5sum: 58e2d3ff48f89916ee96f129597b3975 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: fis-gtm Version: 6.0-003-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, fis-gtm-6.0-003 Provides: mumps Homepage: http://sourceforge.net/projects/fis-gtm Priority: optional Section: database Filename: pool/main/f/fis-gtm/fis-gtm_6.0-003-2~nd13.04+1_all.deb Size: 15118 SHA256: 62a3d1064045f0c9adc75259bdd44bece502402aa6af5a7a910453caea3a8d7d SHA1: 407dbe9fde129c6716b52b6b44a54c23d118cb80 MD5sum: 12b9bdc8bd351655f2d686c5efe6c92c Description: metapackage for the latest version of FIS-GT.M database GT.M is a database engine with scalability proven in large real-time transaction processing systems that have thousands of concurrent users, individual database file sizes to the Terabyte range (with virtually unlimited aggregate database sizes). Yet the light footprint of GT.M allows it to also scale down for use in small applications and software appliances (virtual machines). . The GT.M data model is hierarchical associative memory (i.e., multi-dimensional array) that imposes no restrictions on the data types of the indexes or content - the application logic can impose any schema, dictionary or data organization suited to its problem domain. (Database engines that do not impose schemas, but which allow layered application software to impose and use whatever schema that is appropriate to the application are popularly referred to as "document oriented", "schemaless" or "schema-free" databases.) . GT.M's compiler for the standard M (also known as MUMPS) scripting language implements full support for ACID (Atomic, Consistent, Isolated, Durable) transactions, using optimistic concurrency control and software transactional memory (STM) that resolves the common mismatch between databases and programming languages. Its unique ability to create and deploy logical multi-site configurations of applications provides unrivaled continuity of business in the face of not just unplanned events, but also planned events, including planned events that include changes to application logic and schema. . This metapackage always depends from the default fis-gtm version. Package: fslview Version: 4.0.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5941 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_i386.deb Size: 2278974 SHA256: 79bfcf3729f0d1aa3ed5061dcc58df9a149cd85503eec3ab20be41e7d94d5bb3 SHA1: 270416e4c73176daf82a3ff7e4a22945cbe7b96f MD5sum: b878919366f45172f72e2f424c3afc23 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 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_all.deb Size: 2346538 SHA256: 21191091e9505223e32987c04eb1acbe3829ae341eef5525489f97a1a2d457bf SHA1: 33c8b353b6b9e7b5824704f2f58440ec2d4ad6f0 MD5sum: 66d92ab90f1579986c945c1cf4e2f90f Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: git-annex-standalone Source: git-annex Version: 10.20241031-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 236968 Depends: git, netbase, openssh-client Recommends: lsof, gnupg, bind9-host, yt-dlp, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, adb, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Breaks: datalad (<= 0.12.3~) Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_10.20241031-1~ndall+1_i386.deb Size: 68790604 SHA256: 54a538b686e2e3c42f6cf7260adc0ffe9710f3c6acc07a3b0832df703dba5a6b SHA1: be36d7de781610ad2928fe4ce19fa9ff92631f78 MD5sum: 97eb9b52c155f9c314da9711f48b2ed7 Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing large files with git, without storing the file contents in git. It can sync, backup, and archive your data, offline and online. Checksums and encryption keep your data safe and secure. Bring the power and distributed nature of git to bear on your large files with git-annex. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with dozens of cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 344 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.04+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~nd13.04+1_i386.deb Size: 127012 SHA256: 08bb11d8f7b512ed0911c553efe5baa625d53ae5a61430cbf6ab23c5c8ef2820 SHA1: c4a7126aaa518d7706662f86e5524ec07be9b7cd MD5sum: 681ef1da2f98471900e80adab0716621 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: gmsl Version: 1.1.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd13.04+1_all.deb Size: 16560 SHA256: 453f04ef8d618aaab33916a7b225e764d671e59df9c9da3145fde6e50af1a90f SHA1: af7f5500dc2b910c0c300a4ff839fe573686e345 MD5sum: 3aed20b76cee6ebb63367d39ab517e30 Description: extra functions to extend functionality of GNU Makefiles The GNU Make Standard Library (GMSL) is a collection of functions implemented using native GNU Make functionality that provide list and string manipulation, integer arithmetic, associative arrays, stacks, and debugging facilities. . Note that despite the name of this project, this library is NOT standard and is NOT written or distributed by the GNU project. Package: golang-github-ncw-rclone-dev Source: rclone Version: 1.41-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 2492 Depends: golang-bazil-fuse-dev, golang-github-aws-aws-sdk-go-dev, golang-github-mreiferson-go-httpclient-dev, golang-github-ncw-go-acd-dev, golang-github-ncw-swift-dev, golang-github-pkg-errors-dev, golang-github-pkg-sftp-dev, golang-github-rfjakob-eme-dev, golang-github-skratchdot-open-golang-dev, golang-github-spf13-cobra-dev, golang-github-spf13-pflag-dev, golang-github-stacktic-dropbox-dev, golang-github-stretchr-testify-dev, golang-github-tsenart-tb-dev, golang-github-unknwon-goconfig-dev, golang-github-vividcortex-ewma-dev, golang-golang-x-crypto-dev, golang-golang-x-net-dev, golang-golang-x-oauth2-google-dev, golang-golang-x-sys-dev, golang-golang-x-text-dev, golang-google-api-dev Homepage: https://github.com/ncw/rclone Priority: optional Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.41-1~ndall0_all.deb Size: 399416 SHA256: 528b53f3312375d31d5cebb95472a57272cf242e14a92cfdf99c45be2ff5511d SHA1: 75f8871fd668e815023267a857b37ad60b9d1c2f MD5sum: a87865eafe10185420838e2e4ffd7b55 Description: go source code of rclone Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers. . This package contains rclone's source code. Package: guacamole Source: guacamole-client Version: 0.8.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 475 Depends: neurodebian-popularity-contest, guacd Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole_0.8.3-1~nd13.04+1_all.deb Size: 428594 SHA256: d55f6232980dc1ef9045b48139a91d4dba50bbf0ccd4f1b9985e49b867d8e1d7 SHA1: 190bdcbe59f8d3376a740ea165eaf0d2e2a6a89f MD5sum: 6d1a33f6ffebe3d47914824494caee9c Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole-client Version: 0.8.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole-tomcat_0.8.3-1~nd13.04+1_all.deb Size: 6954 SHA256: 86720dba22910a24bf42d89d963cc85eebdb3473d0b2cd3d024e303fe3c08d58 SHA1: dadcc37c8a43d8983e56f5b9c8b7c034e36907c4 MD5sum: 65573fafba4caf4845f917da4c2539d0 Description: Tomcat-based Guacamole install with VNC support Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. . This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.15), libguac5, libssl1.0.0 (>= 1.0.0) Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-server/guacd_0.8.3-1~nd13.04+1_i386.deb Size: 15172 SHA256: a307e4dae45b09ed4743351183aa1093a4625e5b25ec7a2eb8eca754b2b04a32 SHA1: f2dd506f709e2e9358beb0abb452064ad4fcfb98 MD5sum: 33e9c64cc436d5e9f135ebd45d05d97e Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: impressive Version: 0.10.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 331 Depends: neurodebian-popularity-contest, python-opengl, python-pygame, python-imaging, poppler-utils | xpdf-utils (>= 3.02-2) Recommends: pdftk, perl Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.10.5-1~nd13.04+1_all.deb Size: 163108 SHA256: 2a4e67ce0cf84aeac26c708e6484e9e31a959200add9ba1eb1a96769898204e5 SHA1: a7f675b792fd558ced0c9b76a81b1e8cb3598c02 MD5sum: d095bba9049d200de56b51cc4e2b1962 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+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_all.deb Size: 9762 SHA256: 1b70856f5e29f4ff05b8faf310211265c11d0e9b6b78f8bd46101218ed941444 SHA1: 727d17fe0fae14cde238acfc92e4c478e60c84af MD5sum: 60d09f476bd15e66eb89d054f2be4951 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: init-system-helpers Version: 1.18~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, perl Breaks: systemd (<< 44-12) Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/init-system-helpers_1.18~nd13.04+1_all.deb Size: 14338 SHA256: 2834618c3ef83955eb6bb220a65101ae33afa1f33c98cecea4db07aef364addc SHA1: 36c58ce17ed94979417519131ffbccb0457baf82 MD5sum: b7a68e5912a00453b475029931a6dbc8 Description: helper tools for all init systems This package contains helper tools that are necessary for switching between the various init systems that Debian contains (e.g. sysvinit, upstart, systemd). An example is deb-systemd-helper, a script that enables systemd unit files without depending on a running systemd. . While this package is maintained by pkg-systemd-maintainers, it is NOT specific to systemd at all. Maintainers of other init systems are welcome to include their helpers in this package. Package: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.2.1-2~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2677 Depends: neurodebian-popularity-contest Suggests: libinsighttoolkit4-dev Conflicts: insighttoolkit-examples Replaces: insighttoolkit-examples Homepage: http://www.itk.org/ Priority: optional Section: devel Filename: pool/main/i/insighttoolkit4/insighttoolkit4-examples_4.2.1-2~nd12.10+1+nd13.04+1_all.deb Size: 2408122 SHA256: 65e6c7472a8a92b3ce0c45d17ffb3483e73a2dac7e24c4ba5175cbf31ca7ea99 SHA1: f8cb4f79f753bfd22d7a9a07470b3c8814a656dd MD5sum: 074628f846a92252222964aefd06d892 Description: Image processing toolkit for registration and segmentation - examples ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the source for example programs. Package: ipython01x Version: 0.13.2-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4665 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython01x-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/ipython01x/ipython01x_0.13.2-1~nd12.10+1+nd13.04+1_all.deb Size: 1286080 SHA256: b735f17a5d75039971d01bafcae7e4eb301a795277414ecebd0064d375dad79c SHA1: a5085547449b24edb309ce17e432dde037a2d232 MD5sum: 0789a3e20beda824754862ced7bcdf5e 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 IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.13.2-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16686 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.13.2-1~nd12.10+1+nd13.04+1_all.deb Size: 7246220 SHA256: f98bd7d37f0204febffa5709f09eb5124cc1f376e53aa7d79d9538ad05cec0f7 SHA1: aa53cd815c0dc66eb3991d7ce8c5fd84b9b4fff9 MD5sum: 811804ffc2f242722732f1bfd66a90bf 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 IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-notebook Source: ipython01x Version: 0.13.2-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-notebook_0.13.2-1~nd12.10+1+nd13.04+1_all.deb Size: 910 SHA256: e712c2d41ec3b89d4633e58ccdc1f15893b9ac1296d4b9aae04e193ba2aae489 SHA1: 2afc184179ee99033f71f6b7f4cc6ac7e8deff23 MD5sum: 8a3db4e3c7b89648db43bb4aa8dc9b3d Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x 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: ipython01x-parallel Source: ipython01x Version: 0.13.2-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython01x/ipython01x-parallel_0.13.2-1~nd12.10+1+nd13.04+1_all.deb Size: 834 SHA256: 8dae62722abf91c76d20ca6d926382fa4197efa7d815c1973ab67ade497cd432 SHA1: b39f45f0df6f3fff98b23c54fb2cbadc6db01b1f MD5sum: aca06ab4c7848644ab4e9807593aa026 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython01x-qtconsole Source: ipython01x Version: 0.13.2-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.13.2-1~nd12.10+1+nd13.04+1_all.deb Size: 920 SHA256: 9438c824e04211686d5b9bb4c9a3a5eeedaa619255054650c85642c7e7a97395 SHA1: a1e7af1ada5039a1022157445773c5cf9c931597 MD5sum: af5c4bc8bc33c1c950d56f879b3d1e90 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x 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: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11748 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7.1-0ubuntu2), python (<< 2.8) 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~nd13.04+1_all.deb Size: 4486534 SHA256: 94324cd485722db64cddadc7bfd1ebf13e71ff6e45c532a24dfd4952f380a287 SHA1: f6f1a41353f31ba8f0886ca23e778e989db1aec9 MD5sum: 9362cc9f7293e4a0fb8597dc71456e6f 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~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10403 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~nd13.04+1_all.deb Size: 4191858 SHA256: fbeb5290528cfca96b94b65cbfa132d97608f6f5a651294aed932d7423b27bf3 SHA1: d6f03dbf53b09e44d6b43a614646a182e75fc7c2 MD5sum: 9b59122dee64e866196af3d1690393ae 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~nd13.04+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~nd13.04+1_all.deb Size: 914 SHA256: ab5fbda2005a1d46b4250a354bc3448b549f11c15b8b1676d224361f108f7ba7 SHA1: 7242d729a32fe408f059430a5968889d0ee717f6 MD5sum: 05a7f10ee24405419cf88a47f39ddd71 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~nd13.04+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~nd13.04+1_all.deb Size: 838 SHA256: 43315410a21249c1c7d2d5a4ebdba410e73469d8af202da572e571c6159adc29 SHA1: 723104e9bf1bde1e5cea3eef9e7e34a0c5a10c7e MD5sum: 3a7f4a7e5c24c95d2e5c3f08a5815d3d 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~nd13.04+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~nd13.04+1_all.deb Size: 926 SHA256: a0c02b115f2b0311d514a7c1752b7d93847cc8d1a0947ae9e730cf7245590b06 SHA1: d8425631e03d417deb9841e72d2cddb0f89ea711 MD5sum: a4d2ae8a03caea83f7430a598f7b0d4b 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1338 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+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_i386.deb Size: 419246 SHA256: c53aba78f038c39cc92a5188a1903a519880ffdde9a0f2595685d51329140141 SHA1: 3c516bae6e8107ae7e8698d8cc846ab2f7c75044 MD5sum: 1785e9107d12148f9d4d44e197e0aca2 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 811 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_i386.deb Size: 329150 SHA256: f9524b9e759e8387c66a899534630359670b79477ceb91f2ef85a5a8a4e1a2a1 SHA1: f4469805a0c2dba70dd911166395a0b5d2b9b74d MD5sum: a2d53a9aa4e0f6a613d983453007994c 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+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_i386.deb Size: 118630 SHA256: ab6435df49234f2ea8a701100e38f62d0b397193a5c6a393000ee5a6036161ad SHA1: 555aa921107113f80eb46506a19e389857cc9180 MD5sum: 78c64694935417b930f3a553af7e0305 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: libclassad-dev Source: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 2195 Depends: neurodebian-popularity-contest, libclassad3 (= 7.8.8~dfsg.1-2~nd13.04+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_7.8.8~dfsg.1-2~nd13.04+1_i386.deb Size: 485892 SHA256: 777f3159df72e008789dbfeeef1d5e528dceb88c88cd94f018106723720cbf08 SHA1: ea3a0f048b80f541191c374e815ebdb8cbf45be8 MD5sum: 8bca0e83cc2b4b1b3a6d783d5461b3ef Description: Condor classads expression language - development library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the static library and header files. Package: libclassad3 Source: condor Version: 7.8.8~dfsg.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 828 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/libclassad3_7.8.8~dfsg.1-2~nd13.04+1_i386.deb Size: 272528 SHA256: 99c9deaf5f869434303cd1772a9c744145950edf7620be04c23216799e3aaaaf SHA1: b543d53a74f478481d6feda8629be9b4f1bb1c55 MD5sum: fc31bd7f3431a7a1b9ee1b725f6b46ad Description: Condor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libdouble-conversion-dbg Source: double-conversion Version: 2.0.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 107 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd13.04+1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: debug Filename: pool/main/d/double-conversion/libdouble-conversion-dbg_2.0.1-1~nd13.04+1_i386.deb Size: 96936 SHA256: cb01a8a4f8a1fdc246c6ab8090734e40d46b7856424061713c9dbb5716c70285 SHA1: 00cf8bca82d695ff808a0d538a9c7b47b19efe4c MD5sum: 0cf3c7e7bd5e5fbcbad2e08f32c3fa13 Description: routines to convert IEEE floats to and from strings (debugging symbols) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains the detached debugging symbols of the library. Package: libdouble-conversion-dev Source: double-conversion Version: 2.0.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd13.04+1) Homepage: http://double-conversion.googlecode.com Priority: extra Section: libdevel Filename: pool/main/d/double-conversion/libdouble-conversion-dev_2.0.1-1~nd13.04+1_i386.deb Size: 58232 SHA256: 9b1e3cfbcacf56ea5bd1c93d1b1c8da0c6ce15c9848ea88f70b28ed5a618139a SHA1: 71558ae0beea8d7a988a7363243423069c77a3ca MD5sum: 19d1784dbc654abadb77fbf286c2b479 Description: routines to convert IEEE floats to and from strings (development files) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a static version of the library and development headers. Package: libdouble-conversion1 Source: double-conversion Version: 2.0.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 77 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: libs Filename: pool/main/d/double-conversion/libdouble-conversion1_2.0.1-1~nd13.04+1_i386.deb Size: 38468 SHA256: 593e155b9f0c6ef8b71ca86df059a9fa3c89aa1555af4b21a796bc17e030e311 SHA1: bc62c29101ef73f717df8c6adcf954b4574ac184 MD5sum: 82b589f2be43eb3226daf7f5b4cbc672 Description: routines to convert IEEE floats to and from strings This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a shared version of the library. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd13.04+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~nd13.04+1_i386.deb Size: 157916 SHA256: 1c85496177948d16e9151c85a7771e2006717b89ea060898de1ca28635251453 SHA1: 9f3a07ae499ff27fda21a10b2fd04f96a759bbe6 MD5sum: 64c640ebce85af44e872ef813d6bd39b 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd13.04+1_i386.deb Size: 40096 SHA256: 3e57bbebca5a45291f57602e3d4e95b7aaf9e60ef661a97b80f0fc2e02322de2 SHA1: 12f77d8caadf6afd1563ea8b4b04049d1178d448 MD5sum: d07d382f1736dc0fa9cb614d31bda7cc 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~nd13.04+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~nd13.04+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~nd13.04+1_i386.deb Size: 153240 SHA256: 68c187cb56d03a5dd1697e71c62f200282b51a1143f9da53edf324c79beb99fc SHA1: 62e3b836806a76ac4bc0b602a0b2e25c99e312fc MD5sum: 0a47fa0c80395b75bd2a0f6a012cb556 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~nd13.04+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~nd13.04+1_i386.deb Size: 141952 SHA256: c40f0acb8f44d526e7dcd4eb0248aad01ab10a248f828b7feaf65e80e9693617 SHA1: 381862ca2a2a49e5de34ece9d44b03a47a6f1422 MD5sum: 869a860d7221cb448e384622cd8ddf5f 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.04+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd13.04+1_i386.deb Size: 32392 SHA256: 5fb80c744e5432e02085a864aa9085d661dfb85db1f9787d0ff8717a59368b73 SHA1: 4170f5942537e3fa8549bb6e1b31fbec67fa29e5 MD5sum: a582eb8042620e11c985b963611b92dd 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.04+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~nd13.04+1_i386.deb Size: 8832 SHA256: eb8eff4d598b7b2d7333fa71604f86c044bb632a84b8fc79742830ab90f47abe SHA1: ff28e7c220b6d03128c4e37f3068b9eb9797388a MD5sum: ce182eb97521e6572e03a5974954075d 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: libguac-client-rdp0 Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 85 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libcairo2 (>= 1.6.0), libfreerdp1 (>= 1.0.1), libguac5, libogg0 (>= 1.0rc3), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2), ghostscript Recommends: libfreerdp-plugins-standard Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-rdp0_0.8.3-1~nd13.04+1_i386.deb Size: 35688 SHA256: 392655621b75751805c3550a1c5ada39620c30a7dcb3d1dfdf49d239a7806eb2 SHA1: cebbd4173bda4705fed6c36a03b27517de1287e0 MD5sum: 6923fbf2ee4481caae01e72d40949aea Description: RDP support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the RDP protocol (Windows Remote Desktop). Package: libguac-client-ssh0 Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libguac5, libpango1.0-0 (>= 1.22.0), libssh-4 (>= 0.3.91) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-ssh0_0.8.3-1~nd13.04+1_i386.deb Size: 25560 SHA256: 2cdee0899c29a6604415dab9445a079ecbb3daed4c3a36e28f19e3da68f4fe2b SHA1: 9d9fcae4d531d4e941c23a8058ce7aea0aff23d2 MD5sum: a7db603fd43b490990129b94e55c02ea Description: SSH support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the SSH protocol. Package: libguac-client-vnc0 Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.6.0), libguac5, libpulse0 (>= 1:0.99.1), libvncserver0 Recommends: vnc4server Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-vnc0_0.8.3-1~nd13.04+1_i386.deb Size: 11680 SHA256: ab5ca6f0cdbf42908966898d9147b490875e8710ea559ac6d583273b6461a37b SHA1: 05356f8f84e46f2c6cc271fd558ddeddf73bab9d MD5sum: d421875fe0e79880e7a46b07e0c612a7 Description: VNC support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 188 Depends: neurodebian-popularity-contest, libguac5 (= 0.8.3-1~nd13.04+1) Replaces: libguac1-dev Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libdevel Filename: pool/main/g/guacamole-server/libguac-dev_0.8.3-1~nd13.04+1_i386.deb Size: 43354 SHA256: c0d4eedc5adbb3de02a68ebd1360b1c2979e017661021e2b3cfbbe29a38104c8 SHA1: 67f6dd10c5c41a97210204c9bb322e2041ddafa7 MD5sum: 8996a6a607353e4802fa012bd03fc616 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac5 Source: guacamole-server Version: 0.8.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 58 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.17), libcairo2 (>= 1.2.4), libogg0 (>= 1.0rc3), libpng12-0 (>= 1.2.13-4), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac5_0.8.3-1~nd13.04+1_i386.deb Size: 25576 SHA256: 8cbfb7154225d210192cb3f005e54bd36b6837462e390cbab9102700bcecf8a4 SHA1: 5a994a54182976a613db3289eff7fc4c23acccca MD5sum: f82a109dfc17f6d19b00b6cec7be6ef4 Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libinsighttoolkit4-dev Source: insighttoolkit4 Version: 4.2.1-2~nd12.10+1+nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 25779 Depends: neurodebian-popularity-contest, libinsighttoolkit4.2 (= 4.2.1-2~nd12.10+1+nd13.04+1), libgdcm2-dev Recommends: libfftw3-dev, uuid-dev Suggests: insighttoolkit4-examples Conflicts: libinsighttoolkit-dev, libinsighttoolkit3-dev Replaces: libinsighttoolkit-dev Homepage: http://www.itk.org/ Priority: optional Section: libdevel Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4-dev_4.2.1-2~nd12.10+1+nd13.04+1_i386.deb Size: 5275850 SHA256: ba9ec061432045f550b273c5ec6a13761fd8dfc4dbd895fc7877489257dabd55 SHA1: 820969441a9927cfc14f1591066753b582045489 MD5sum: 9bf7547dc7e2deeed23c181f20674d05 Description: Image processing toolkit for registration and segmentation - development ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the development files needed to build your own ITK applications. Package: libinsighttoolkit4.2 Source: insighttoolkit4 Version: 4.2.1-2~nd12.10+1+nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20377 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libgdcm2.2, libjpeg8 (>= 8c), libminc2-1, libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.3) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.2_4.2.1-2~nd12.10+1+nd13.04+1_i386.deb Size: 6820470 SHA256: a59274fc382af253677dd8ed17eba8172366f04d0ef41a084ac93e478a313832 SHA1: d31ef04af11dd05501abacfc3d7cf08247f84c15 MD5sum: 2fa4b45917da66a3c0870b38a8ece561 Description: Image processing toolkit for registration and segmentation - runtime ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the libraries needed to run ITK applications. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+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) 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_i386.deb Size: 2408 SHA256: 409c1f4d348b0b4c335499d37c5a5d678f7588035bdc65c129f704f2c180b3e7 SHA1: 5cd4e3eb18218f8bd730d88e1d13df94428e5827 MD5sum: 108bd991c2e7f228f8042e2cdd270bc0 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 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 (>= 2.31.8), libgtk2.0-0 (>= 2.14.0), libpango1.0-0 (>= 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_i386.deb Size: 48880 SHA256: 993a00a82f3fb5b5cebd48ae066b77557732de6411cf8de91c00af35b261b7b2 SHA1: b0a126e83cea00ebdaac09b87acab3357bd345dc MD5sum: 54cfefc125809ddfc2aabf732c55e39e 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+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_i386.deb Size: 6572 SHA256: f30713afa2881e8b3f238a6921383e41e42876d77146ae7b0633a544b4c9515a SHA1: 5effc30d4e54a0618d220ca2f47f6dd2cdf60317 MD5sum: 0b9869971d31693cc119d8bd252559a0 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: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21876 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-serialization1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-test1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libdcmtk2 (>= 3.6.0), libfftw3-single3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.33.13), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp7, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2 (>= 2.1~), libtiff5 (>> 4.0.0-1~), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.34.2) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd13.04+1_i386.deb Size: 3479410 SHA256: 69c16c95fb2f83055ed0c5e86aba6015e7e9aeb72513509b67ed47daf271a587 SHA1: a9656bb83d7a7e1b2d850c8076726d4aef78242f MD5sum: 6a532e62cc9ebee5331a2478c4a15d08 Description: library for 2D and 3D gray scale image processing libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. Package: libmia-2.0-8-dbg Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 56241 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd13.04+1_i386.deb Size: 50848964 SHA256: 2d601d155f31a9e781dd5d4f5c455169ddddd66b837257cfc7464e72e448ae48 SHA1: 53b0167e0cb9878cc4b9bfe61bff975487eda710 MD5sum: df96f5ea62721084d9f7237f4b2f6982 Description: Debug information for the MIA library libmia comprises a set of libraries and plug.ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. libmia is library for general purpouse 2D and 3D gray scale image processing. This package provides the debug information of the library. Package: libmia-2.0-dev Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1087 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.04+1), libxml++2.6-dev (>= 2.34.1), libitpp-dev (>= 4.2), libtbb-dev, libgsl0-dev, libboost-all-dev (>= 1.46.1), libfftw3-dev, libblas-dev Recommends: libmia-2.0-doc Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/m/mia/libmia-2.0-dev_2.0.13-1~nd13.04+1_i386.deb Size: 170584 SHA256: 5697eff349570a9cd149f4e05107df0c11fac03170d320a9d6b41e77418ecae9 SHA1: 22c1802c8c7296976eec9d1bc2acf5848369b5eb MD5sum: 2c1a4b37e26a57bdbc9dcdad0d281d76 Description: library for 2D and 3D gray scale image processing, development files libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the development files for the library. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12977 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd13.04+1_all.deb Size: 778794 SHA256: a27c7f64692b847ab2d3c3beaa9b41810055bd2eebeec0dbb85c85441b6b298b SHA1: 3e13b1a709d58c78f44ac3a570eac301456a9372 MD5sum: 426e7747fea1774f40ddfad9b2d9eb9e Description: library for 2D and 3D gray scale image processing, documentation libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the Doxygen generated API reference. Package: libmialm-dev Source: libmialm Version: 1.0.7-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 284 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libm/libmialm/libmialm-dev_1.0.7-2~nd13.04+1_i386.deb Size: 113242 SHA256: 8c2ff10f46eab3f0d393a4fd94ca4a84ca63c9e2cccf6f8244d90f572f6a27a9 SHA1: 40391c65a4da0d5be61ec7b190615f7fd270a852 MD5sum: 98885d469dc9ff10949547a8ad9dc552 Description: Development files for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the development files - headers, shared libraries, and pkg-config files. Package: libmialm-doc Source: libmialm Version: 1.0.7-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest Suggests: devhelp Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/libm/libmialm/libmialm-doc_1.0.7-2~nd13.04+1_all.deb Size: 25102 SHA256: f8de6602cafe72cf37dee0373dcc59c165e2241e04497a7feb21898fe3bf8c1f SHA1: c910483d2ccecbe624859a282676baeb37fd65a5 MD5sum: 0647a0bcaa78adafc9973ec5b16e4b4b Description: Documentation for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the library documentation. Package: libmialm3 Source: libmialm Version: 1.0.7-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libglib2.0-0 (>= 2.16.0), libxml2 (>= 2.7.4) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libm/libmialm/libmialm3_1.0.7-2~nd13.04+1_i386.deb Size: 21286 SHA256: ebb84a07469824d80dae937bc47b6990317b4b5a4d1fe655c572e5d75bcc4985 SHA1: da2324bf1fd3874a9dbf18d2204535d301c59e0e MD5sum: 34c16f14cf24fe66106a40d39d55df30 Description: Landmark handling for the MIA tool chain This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. Package: libmialm3-dbg Source: libmialm Version: 1.0.7-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 66 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libm/libmialm/libmialm3-dbg_1.0.7-2~nd13.04+1_i386.deb Size: 57368 SHA256: f1b2ee434e58e004644d55f924f2f0a2924c614758c414b0965f7eeec03ace5d SHA1: c301e8ec13a815703515936e4aef2a2c9148f1dd MD5sum: a9952ad64ebe884bdf237da3efce4b34 Description: Debug information for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package provides the debug information of the library. Package: libnlopt-dev Source: nlopt Version: 2.4.1+dfsg-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 526 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd13.04+1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libdevel Filename: pool/main/n/nlopt/libnlopt-dev_2.4.1+dfsg-1~nd13.04+1_i386.deb Size: 200406 SHA256: ab0206402d4b3f63917c07798908fd7807588ef8df864c3263e79e595a2b781b SHA1: bf27191ce48a7d01b45a3db0f6dd28795f352156 MD5sum: f1f9452b176ef14fa24ed9a91e50d5fb Description: nonlinear optimization library -- development package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the header files, static libraries and symbolic links that developers using NLopt library will need. Package: libnlopt-guile0 Source: nlopt Version: 2.4.1+dfsg-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 132 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd13.04+1), libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), guile-1.8 Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt-guile0_2.4.1+dfsg-1~nd13.04+1_i386.deb Size: 48672 SHA256: d4884253ce38122623e4a095612035b5d8d3131df3cc82a363a0428045b33318 SHA1: 228b6fe011cffc93d49a5eedbf80acff505c80d1 MD5sum: 16355aea285aa9a8d9074b7eaf77eefe Description: nonlinear optimization library -- Guile bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the bindings for GNU Guile. Package: libnlopt0 Source: nlopt Version: 2.4.1+dfsg-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt0_2.4.1+dfsg-1~nd13.04+1_i386.deb Size: 177764 SHA256: cbffe76bcbcb585aa5edf94d8dc5cced0d0cc2fd6f395558c6466465f5bf7f72 SHA1: 2b671f51fed73bc6bba49315c218afec93b9cee2 MD5sum: fa42483260bdc2987ab31e8a7d37062c Description: nonlinear optimization library NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package provides the shared libraries required to run programs compiled with NLopt. To compile your own programs you also need to install libnlopt-dev. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7044 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.49.0 (>= 1.49.0-1), libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph80, libopenthreads14, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1_i386.deb Size: 1932698 SHA256: 7b51bb7a21309487e783d0d87cada28c9b483db8ea77027222ac141afda708e5 SHA1: d33afbb9a8bcb7d9baefb833d8e09fa4b5f35678 MD5sum: f85f36ed9f294bcc604107a0530d223e Description: Framework for multi-modal medical and brain data visualization OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 3.0.0), libopenthreads-dev (>= 3.0.0), libboost-dev (>= 1.46.0), libboost-program-options-dev (>= 1.46.0), libboost-thread-dev (>= 1.46.0), libboost-filesystem-dev (>= 1.46.0), libboost-date-time-dev (>= 1.46.0), libboost-system-dev (>= 1.46.0), libboost-signals-dev (>= 1.46.0), libboost-regex-dev (>= 1.46.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1_i386.deb Size: 339170 SHA256: 3771f420982a755c96c8223b4c58ffb6c70b810d0cf6cd758c26efb14dbf5b6e SHA1: 2b22514e1d76b55de2016cd90478d33848a814a4 MD5sum: 007f7dbb2b5f186f716f0dd8237808b6 Description: Development files for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44739 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1_all.deb Size: 5084324 SHA256: b0a7dc413175f3597402e70161e959884e8d518a36f152ffed90116a8b7c08d3 SHA1: 5451a819a3383183cd061292e50caeb81828a791 MD5sum: 1a7be52bebeadb6f18f29fe54bef6238 Description: Developer documentation for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libvistaio-dev Source: libvistaio Version: 1.2.16-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 172 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libv/libvistaio/libvistaio-dev_1.2.16-1~nd13.04+1_i386.deb Size: 111918 SHA256: 611f09cccc999f1ba3c42060f61ba5b07e6c01729ce96616038bad5bb0b267e2 SHA1: 28060005201e5f835bc0b65c364de4febac2d827 MD5sum: 83e5b691c6cec817a34563e9191ed7d7 Description: Development files for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is the development package containing the header files, and pkg-config script, and man pages. Package: libvistaio14 Source: libvistaio Version: 1.2.16-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libv/libvistaio/libvistaio14_1.2.16-1~nd13.04+1_i386.deb Size: 41098 SHA256: 5b046ee2e23920cea5919cb491603199ad1e45a5d8bb957bf21cb3129e1d2e48 SHA1: 7f6898ffff9f1955fd076c27a4f7f88b9c7ba23f MD5sum: 4fa33e92387e7a747b840c4f5782d3e5 Description: Library for loading and storing various types of binary data Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. Package: libvistaio14-dbg Source: libvistaio Version: 1.2.16-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libv/libvistaio/libvistaio14-dbg_1.2.16-1~nd13.04+1_i386.deb Size: 79708 SHA256: a33986ec32761ba1db8eb855d9439685462e8d012d02dbd76a038b0b59aff3fe SHA1: 9d61be58096c8639e0010814e84403b2457f4d43 MD5sum: 8e677bec6934ad683f774c4d7e7a1b2c Description: Debug information for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is package containing the debug information. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+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), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+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_i386.deb Size: 174196 SHA256: c44f7ad756b31ea9f4563c4df4ceb56119ad37507f1c226c834975abc5e5e541 SHA1: a7350ed4f8bf1408d3ae518714546114797fb6c8 MD5sum: c858aae84df48b228adec9b743e1418c 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 510 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_i386.deb Size: 184454 SHA256: dd2c652780033dccc1f2de3e839218acbd6431d164bba42361d6dc0106c02cfc SHA1: 51c912031c38ea3b772979befc6615c8f8fe18c7 MD5sum: 06b8c7b0262283cd10c41e9ba399c968 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1214 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_i386.deb Size: 425558 SHA256: 1c83bbe5d9b0ce8eebbc53eb108718597004382777f1e4a9b3ffe7e43be2e45a SHA1: 06faeefb4ae4622d25b5e20d4b73e6e27dacfc94 MD5sum: 2bc52092e7102fc7d0ad2480615b264b 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: libvw-dev Source: vowpal-wabbit Version: 7.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1898 Depends: neurodebian-popularity-contest, libvw0 (= 7.3-1~nd13.04+1) Homepage: http://hunch.net/~vw/ Priority: optional Section: libdevel Filename: pool/main/v/vowpal-wabbit/libvw-dev_7.3-1~nd13.04+1_i386.deb Size: 534990 SHA256: 5b59c8c0762a114de6373b1742be7ea4a98feb39b1490ba81031db7849afed56 SHA1: ad550d8f9fef93d89d8db81f6af78ffb6805142f MD5sum: d277632cd3b8ebf7af437f80c4370887 Description: fast and scalable online machine learning algorithm - development files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains development files needed to compile and link programs which use vowpal-wabbit's libraries. Package: libvw0 Source: vowpal-wabbit Version: 7.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 696 Depends: neurodebian-popularity-contest, libboost-program-options1.49.0 (>= 1.49.0-1), libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.2.3.3) Homepage: http://hunch.net/~vw/ Priority: optional Section: libs Filename: pool/main/v/vowpal-wabbit/libvw0_7.3-1~nd13.04+1_i386.deb Size: 294636 SHA256: 63f8cc623c7469fbcebaa72851a1f772eba9055e3a43fd0e5b727cc73c6215ad SHA1: f538d64bc6a266c340427ce3ed70214100696768 MD5sum: d8399434ec1df3ab6bd5cbe2c17f50d5 Description: fast and scalable online machine learning algorithm - dynamic library Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains vowpal-wabbit's dynamic libraries. Package: mia-tools Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7991 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.04+1), libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-serialization1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-test1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.33.13), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2 (>= 2.1~), libtiff5 (>> 4.0.0-1~), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.34.2) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd13.04+1_i386.deb Size: 1463658 SHA256: 2b9ee11f71a5607c6c1552cbd2594b0322b749d706bc0f97cf1edfa26399fdbd SHA1: 7b4fc86dd793162f6423ce12ed05b9585dc21a21 MD5sum: 9214b35c50711ff882f1f59975512919 Description: Command line tools for gray scale image processing Command lines tools to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-dbg Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 24966 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd13.04+1_i386.deb Size: 22806014 SHA256: c264520fecff2c289531d42b3a9b5baa6f8ed2e5ce81cce8b27cfa33dee03701 SHA1: 4c59d3a71815d5c7f93fd144a3342ae099d9777e MD5sum: a11e38d85f9f682de1da94007bfa4215 Description: Debugging information for the MIA command line tools Debug information for the MIA command lines tools. These tools provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1134 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd13.04+1_all.deb Size: 72790 SHA256: ee3a4b4aec826682d9db0129ee48d93528e1a1677bd906ee8fb55b9290c4eacf SHA1: 767900133589f8ea59fbcbfa6fd3abc55010b53f MD5sum: 752a1e81809d66f44decdc745fa5cf6d Description: Cross-referenced documentation of the MIA command line tools Cross referenced documentation of the command line tools and plug-ins that are provided by the MIA gray scale image processing tool chain. These lines tools to provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes interactively from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statistics over images. Package: mialmpick Version: 0.2.10-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 168 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.1), libglib2.0-0 (>= 2.31.18), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd13.04+1_i386.deb Size: 79744 SHA256: c4703b5147437e4d26d3bf543c9a3f7d7292808cad40f9d52ebfa5ce022ac1f2 SHA1: 9d690f997c94a8de1b0e7ffb6feb0dfa2bd06174 MD5sum: b69599773604d16805e206705b7ec5a6 Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 186 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd13.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd13.04+1_i386.deb Size: 166744 SHA256: 0f793d88845fed36cfd58912e6e674f64a56dd79e04c78c539d8dce5a02a3374 SHA1: 92cd6ddb2c291d6472df1d56d5cce2484d9fd41a MD5sum: cf2b158692acf6421244d8b72ebfdb15 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Package: mriconvert Version: 1:2.0.7-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 3159 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.7-1~nd13.04+1_i386.deb Size: 1043118 SHA256: 7f7986dd07f4742ffa26ad4258c9090e28697018efac8e1af81eb36e6bcacc96 SHA1: 2cee29b863d6c5dcfac2b3f95d9c84745045bea5 MD5sum: e99084a5814322cf4fc26d29895f7438 Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 14420 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), libpango1.0-0 (>= 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_i386.deb Size: 5567928 SHA256: 3c78c8ddd35cd80243540b330df941e3b1301d056ff25953d04c9f097ace5bea SHA1: 7c10b49297fc87b4cdc25118f22d09575dde7319 MD5sum: 1240f83c992e5e4008601b2351f3b51c 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1710 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_all.deb Size: 1664524 SHA256: 179f46350fc86243f6af340e0ba92f4d8cbafb46d0c085be129f29f8ac846159 SHA1: cfa43237268d891d2472016ee77e8c7470298c30 MD5sum: cb9e0cda7870731a8d15ff9e016e002b 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 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1019 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_all.deb Size: 737510 SHA256: f6522a77a07ff991e70a16fbeb0a146e3744049373534f465c99da6da03aabe7 SHA1: fdfd8b08dfb6c00c23ceb6b8b139ba16d80e09a1 MD5sum: c16e9f95bb777af9a6fa7517187931d4 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: 0.2.12-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 8543 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 (>= 2.33.13), 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_0.2.12-1~nd13.04+1_i386.deb Size: 2890444 SHA256: a2ea3a9bc9efbc082db3438ad8732c1a785519b5500d61a5fb0b3ec3da0c66af SHA1: 78a6c9f54ea8c8c600dabe542a1be8574c2bf936 MD5sum: 17bc82f6cbca120ac3c2a7799691e740 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: 0.2.12-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3522 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.12-1~nd13.04+1_all.deb Size: 3316748 SHA256: 8d6e51d5d33441b9dd92cf3f79517636166e1f864d52e2a1b2e8a9b1a294c464 SHA1: 2875d1896c02c71b25ccd158bb4ab7f725fb8ef3 MD5sum: 54a504dc376ef7e2fad515f88d32e960 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: netselect Version: 0.3.ds1-25~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 50 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd13.04+1_i386.deb Size: 32388 SHA256: 9888a25e5c5f8c3e56064526ed831ae0ef85ab546c11c80fb71cf2696d6d395b SHA1: f3972e5b957aed46aec286d94744a87ae50bc925 MD5sum: dd20ea08f1b8c9be451378e4af729833 Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd13.04+1_all.deb Size: 17854 SHA256: 26e593f988079fc2a6960f50adb16cd4bb3b10fc61ecb91b4ca0e56f4dc891a8 SHA1: 2ad9d34f766aa3282b89fb54560cd6633e497e1f MD5sum: b2905fed81d545b50bf473bbb4d7a42b Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.34~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.34~nd13.04+1_all.deb Size: 21428 SHA256: e14fd2d11da6b2fb34f39802c8f8e9ceba6dccaef76d5627e893344b96f0de8e SHA1: 45c3475edf719bea844fc7d14be6f60552851958 MD5sum: f74b14d8b514562f254da1306b9f6f05 Description: turnkey platform for the neuroscience The NeuroDebian project integrates and maintain a variety of neuroscience-oriented (such as AFNI, FSL, PsychoPy, etc.) and many generic computational (such as condor, pandas, etc.) software projects within Debian. . This package enables NeuroDebian repository on top of the stock Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.34~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.34~nd13.04+1_all.deb Size: 9406 SHA256: 5d584cf074bb63fc121a69bb7d4e6865a758dc061649ff121639f0299322492d SHA1: 0aeca35e5e5f810fd8afe8b50ce545fbdc2a6f38 MD5sum: fed6d093119268d7603a18b575f0db83 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-desktop Source: neurodebian Version: 0.34~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 146 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_0.34~nd13.04+1_all.deb Size: 117568 SHA256: d9cf3b9e4b50817f1af38b70867af5c46a132f5d34cc8f63ae91a1f5c4523ba2 SHA1: 4416f9538c0cf85d4ac4511aafe4a5d183b3ba8a MD5sum: c3653b7581d3b6a9bf7249b57137ea90 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: 0.34~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: devscripts, cowbuilder, neurodebian-archive-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_0.34~nd13.04+1_all.deb Size: 34226 SHA256: 3a706051cfac62e526b9266a4000d55aaeea01f2d5d0f672f3dd96296cfdfa28 SHA1: 28559611e0e10350b90ad561cc4521b377467e3b MD5sum: cf04ecace2166d2d18a79293a9d83300 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~nd13.04+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~nd13.04+1_all.deb Size: 15368 SHA256: a17f7ae3ceef942087450f8d19e2b87b142f5787ec1981beb22a29499f735bde SHA1: c801838145de1ee7c04f30b6f725c5922174205d MD5sum: e931791983e6ca2f27adfa619982b7d0 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~nd13.04+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~nd13.04+1_all.deb Size: 7624 SHA256: 239d23454e0e47195450883b29b63d8f417dd5719c390765a69518f4e6af075f SHA1: 8e8b3228adaa59e3178d615bf671324fb96e8eb6 MD5sum: f7f0dd6a1bc84b7d45235919ecc716c0 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: 0.34~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.34~nd13.04+1_all.deb Size: 11490 SHA256: 5d019234fcd6a50ab44a783b325e61accc1842eb586ad96a22216a6c15f49838 SHA1: 0da2ae023075753fa2c7a37544bf7fac21231c7f MD5sum: f1a813821b385b146a8e629b5fe8faf0 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: 0.4.8-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2180 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.3, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.8-1~nd13.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.8-1~nd13.04+1_i386.deb Size: 492858 SHA256: b516eb91147fa065bf6d005a5cb423ced2f44af88f2cc2f2675f18f25b96f910 SHA1: a0f2cb9221614bb409c80d7838d4827fc9e4c58a MD5sum: d9b5a70848dac4a7993878256a5fdfd3 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: 0.4.8-1~nd13.04+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_0.4.8-1~nd13.04+1_all.deb Size: 615082 SHA256: a195fb674c4a1a95c42be1473d9076f64cc477e1dd4f2bf37e82917a950751cf SHA1: f3ae918562a0170f5b586531bf5d33cff047fb9c MD5sum: ad045f98465c1036f31f13903462b814 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: 0.5.4+ds-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2218 Depends: neurodebian-popularity-contest, g++-4.9 | g++-4.8 | g++-4.7 | 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 (>= 2.7.1-0ubuntu2) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.4+ds-1~nd13.04+1_all.deb Size: 591380 SHA256: 07783d25700e01e1275180e8ec1b1ac15d3834fb5f58260ee3e8414c513a4b34 SHA1: ab477225567e887e3f068a1b374670572730350b MD5sum: ae4079333b9491cfbb851c63cffeb2d4 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 876 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_i386.deb Size: 608042 SHA256: f33c3a8c9a0777274106fed8987f4b28561589903ebdc8c055f65728275f1562 SHA1: 1c198ea0c973fd4816dc1cc99fb0905c1c344c45 MD5sum: 2465319762d4c7eaccf495e3093276d0 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 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_i386.deb Size: 23656 SHA256: 1497c9919123fcb8e809a3a00d3f0468ebf01acc02b16c457cc02cd39e6a8aa5 SHA1: 6af4452d580400054065e6e0c6f725e9841f4f68 MD5sum: 0c809588befe1648db398b3b03b24560 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-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd13.04+1), libc6 (>= 2.3.4), libgcc1 (>= 1:4.1.1), liboctave1 (>= 3.6.2), libstdc++6 (>= 4.1.1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: math Filename: pool/main/n/nlopt/octave-nlopt_2.4.1+dfsg-1~nd13.04+1_i386.deb Size: 31104 SHA256: 211b43fda3894c787ed30410cffae0fc51b2a7fd26e1c5d1971365d732c6813a SHA1: 120425aa589270733850672d153026cdda130e2a MD5sum: 235004600a7b75bf0544fd1bbee066b7 Description: nonlinear optimization library -- GNU Octave package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the module for the GNU Octave. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.11.20140816.dfsg1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2725 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), 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 (= 3.0.11.20140816.dfsg1-1~nd13.04+1), psychtoolbox-3-lib (= 3.0.11.20140816.dfsg1-1~nd13.04+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_3.0.11.20140816.dfsg1-1~nd13.04+1_i386.deb Size: 897084 SHA256: ab6a124b90f63fdd2c310fd7ccb9e27c76921ebb89023e440807cafe7114b452 SHA1: 981999849a100fe13771bf34b1107b19afefa9bc MD5sum: 47175388ab1f1054e56a8dc3364dfb50 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 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_all.deb Size: 25359352 SHA256: be473efbb1a3c74f86b5d05bd4d841ec3bee3c0e6e61451bd2aa3673834c9c22 SHA1: 1f1e9c48706fb0075bcdce01889f29457ab7efad MD5sum: db4fbffa3d4dc3eb61e2c40cc52fc9a4 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: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 20107 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph80, libopenthreads14, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1_i386.deb Size: 6544886 SHA256: 9c39fba3a47de9a878d5310149fb2f6551d87cc4a52a3be1fbd2e71cfd6ede0c SHA1: 5fc028ffc57e6e29aed79b18443765037498441e MD5sum: 912222a3ba6c62a2e6d7196bc36d2803 Description: Loaders, algorithms and visualization modules for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2116 Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-program-options1.49.0 (>= 1.49.0-1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libopenscenegraph80, libopenthreads14, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.6), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd13.04+1_i386.deb Size: 956112 SHA256: 7b84abdb66cb351f49a6a997ea8917c1c5887f45def58d5f70b044c8d80ca504 SHA1: 37e4ed0bd7e1e8a1e63e7d7e98e9ce71dd37fa04 MD5sum: f550d4a50cf9f760b1a9c62256a5ed98 Description: Qt based user interface for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: packaging-tutorial Version: 0.8~nd0+nd13.04+1 Architecture: all Maintainer: Lucas Nussbaum Installed-Size: 1550 Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.8~nd0+nd13.04+1_all.deb Size: 1488406 SHA256: 2080837f62cdfe9c3cdd6abbe134a1672da2a73335dd213fc8c80732244c40a9 SHA1: 15eaae4fe59ba4f53545db6406d8f51e61692eea MD5sum: 27e78cb1c4edc8953cf73e9a71350c36 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: psychopy Version: 1.79.00+git16-g30c9343.dfsg-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12186 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-pyo, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.79.00+git16-g30c9343.dfsg-1~nd13.04+1_all.deb Size: 8109658 SHA256: d348a51d0d94f052bb8300a1ca7526ccd90e923b93b02cf856b44d36c0d60919 SHA1: 72b7fa77df11a89b72ad018f4960184d7a402fba MD5sum: ffd2d612a22696e4f3de3bf70383f721 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.11.20140816.dfsg1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58476 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_3.0.11.20140816.dfsg1-1~nd13.04+1_all.deb Size: 24812342 SHA256: 1ff10b65645327e6d169c49bee8164895503a4109ee6a3600e766ab7cbb89604 SHA1: 8d355ffcbc8c536ca000449c689edaf45ef0814d MD5sum: dcc7ad2b0cf90a7646c5702651d16818 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: 3.0.11.20140816.dfsg1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2413 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.11.20140816.dfsg1-1~nd13.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.11.20140816.dfsg1-1~nd13.04+1_i386.deb Size: 851412 SHA256: 6eda567640fec2e0cf23b3da6e1353e61fe095d5e5adc8aee9e1d337d5e51a04 SHA1: 44518fd4ed7b78170bf36c60006175307be3133c MD5sum: cc170c39f4b5c4af7019f34327756102 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: 3.0.11.20140816.dfsg1-1~nd13.04+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_3.0.11.20140816.dfsg1-1~nd13.04+1_i386.deb Size: 65290 SHA256: 1a9999159f27ec5ef4c5abf548f5835af41f84ba44d06bc52300e18375608621 SHA1: 5021452bdf09f88e8a96c155bcd6f2055ef0e1cd MD5sum: c50a032ed268d3494aa04267efc3e431 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 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_i386.deb Size: 55290 SHA256: 6537dfdaf7872f6d1a656a2102374c0079dbfb34a6702c787f9452d0acdbc1f0 SHA1: b43e85c2883f2a299aedcee4165507f5371f271d MD5sum: 6a90926a0847aeaae3684115886340ce 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 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), 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_all.deb Size: 549182 SHA256: 9eced6619fb84aea48b5a3fcbc2866e03897ae230c42de1363a01e9dd5b54f91 SHA1: 3ca4a641e5ded2df230142d5a767dacb02e2c1fd MD5sum: 1e3f0dd840e5c40b39c063a9ec88305d 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6811 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_all.deb Size: 2247196 SHA256: d155efe0ac801294667b2a44eb58bcb3b0298e73ff97556f8829de8710828f81 SHA1: c247d3f619f28dacd1fe308e61c674ee3556c2f1 MD5sum: bc1ad205f7e25c67460319c0ce2c290c 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 124 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_i386.deb Size: 52284 SHA256: e6f96fc6e7b864591abe7379dd4656162691f173315a0bfac9960ed15c02cff6 SHA1: 1d5d599ddb1fe1aafa1820c4aa58570399dc19fc MD5sum: fbef8a2a0459378d4eb5aca6b75b98b2 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-dicom Source: pydicom Version: 0.9.8-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1814 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.8-1~nd13.04+1_all.deb Size: 422952 SHA256: e0bb4d271da30d345a5c89117eaebdf7d1c82f408c4f986929b6d5e604973d75 SHA1: 6ee33331ca955f59b15399c0d87a87c477f6fa2f MD5sum: 30b896304847513cf9c2de454d7e1bf1 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.7.1-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2952 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-dipy-lib (>= 0.7.1-2~nd13.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.7.1-2~nd13.04+1_all.deb Size: 1884922 SHA256: 4aaebc71adf63de47fed59e1a026888898be04eec6e6fd2a930398bf96e03d5f SHA1: 42b55691b4fe067ee5553c5f70bafa2d109340ce MD5sum: c7bebc892e2ead6dba29ce64fb6ecf0e Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.7.1-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9459 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.7.1-2~nd13.04+1_all.deb Size: 7616954 SHA256: 4bbc31a702c0e2e1ccdb7b98ddbf7bf403682f60ee87ae723d73eb30fb53bcc5 SHA1: 215be000a820571cbec1439ebbfc84a3db3f87d0 MD5sum: 4f56a88dc0de1f99a2374f9f14e39772 Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.7.1-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 898 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libc6 (>= 2.4) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.7.1-2~nd13.04+1_i386.deb Size: 352248 SHA256: c6159e66a8c048d0bc2a4430220b784f29e5c5e87d82bf356937aa29509dab7f SHA1: 51d994e6a3f5a706d696f6ec4958a52c2731ee6b MD5sum: 29ab40304704d3aa47dcb6aac4990f66 Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2413 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd13.04+1_all.deb Size: 838738 SHA256: a391537a771e0c1d78b68951a52127ee2131befd9cf76913638a01e4f62c567c SHA1: 03ac5a2e9e0aa1536f355e53f5d8404a36a575db MD5sum: e22aedabcfe6986fa6216dba50e18443 Description: Python library for cognitive and neuroscientific experiments Expyriment is a light-weight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments. The major goal is to provide a well-structured Python library for a script-based experiment development with a high priority on the readability of the resulting programme code. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones. Package: python-joblib Source: joblib Version: 0.8.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.8.3-1~nd13.04+1_all.deb Size: 75586 SHA256: fb3e999102437355a5bd35c20ef455f7378dabada4684f195dd665207a0a574e SHA1: f9030cbd6d99f67a6cc8fe48550de0926ed6a130 MD5sum: 87f43c6377f52b17724b96b1000f2308 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. . This package contains the Python 2 version. Package: python-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1495 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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_all.deb Size: 478658 SHA256: f64b49dd6826c89a25593bc9a05d154599fed318b5bb9a3c8e99c6ce9ba6dd5a SHA1: 1d63f0f452c4d60af96494263e7f75b724ee7a56 MD5sum: 4d9fb528cbf2c338a7562b20dcfd8a4d 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-mne Version: 0.7.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6208 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man Recommends: python-nose, mayavi2 Suggests: python-dap, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.7.3-1~nd13.04+1_all.deb Size: 4053356 SHA256: 1859e5d1d072111c55949e4c5189ad5675bb318c9d7e31d82840ac22a531094b SHA1: 62a3641be07443909cb2a261edc72d151b743dfe MD5sum: 6d95517850ff369c73ce19cda7513b18 Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-mpi4py Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1548 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libopenmpi1.3, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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~nd13.04+1_i386.deb Size: 489176 SHA256: 8268304229da91e5b2afea34a242acd6551058038947814711a2a710a6caa5f2 SHA1: 0a617463949f0de13df6604f09b193e903dd6453 MD5sum: 0015cf13d30e5b4c86ce50d602a56d77 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3606 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3.1+hg20131106-1~nd13.04+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~nd13.04+1_i386.deb Size: 1206634 SHA256: 572eeb4e5a1653904d113d513c5810c3619bf35ac51f7657a5b84da58dce94d9 SHA1: e653ebeda3eb68e95c1ebce59f8a0ec98d7dc69d MD5sum: c4c383c908935748b15b532556169861 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~nd13.04+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~nd13.04+1_all.deb Size: 73120 SHA256: 0d1ac85177ba65bb8362f9af8645361a0d352ae7b56575cd5be8c81f2b98b1f1 SHA1: b966da7d5a6d6e6b1c991dbed503f58be1e14e41 MD5sum: a90f44ff9721a35d7f3f388834bbb808 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-mvpa2 Source: pymvpa2 Version: 2.3.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6541 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7.1-0ubuntu2), python-numpy, python-mvpa2-lib (>= 2.3.1-1~nd13.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, shogun-python-modular, liblapack-dev, python-pprocess Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.3.1-1~nd13.04+1_all.deb Size: 3907266 SHA256: 546bb274975957f8630eaa073c8d2ff841677f8680cbc02b0b7d67c3da89650e SHA1: bb69e09e4a6817cd881f0c6e1ce29c4549aa5138 MD5sum: 0898824edc81730df022921373c0a29c Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.3.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27414 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.3.1-1~nd13.04+1_all.deb Size: 6495174 SHA256: 095ad31ca4d2395d9e71d7b5c70900b88c36bfbcbbefe58068b382d0959abc74 SHA1: 24bcdb494f18d5374da0ca7f67cc85e2c4d6f14a MD5sum: 82c36b17f6575115a280988695cbeb1a Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.3.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.3.1-1~nd13.04+1_i386.deb Size: 50934 SHA256: eecddd426da46e119a8f38dca77d5f4ead9f6db62c03178e48f0fd15323d495e SHA1: a9cc3c95e8be5c4a7b3690d517e304226478e63d MD5sum: 374655263993a616d9f02e201b724fa0 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neo Source: neo Version: 0.3.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2913 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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_0.3.3-1~nd13.04+1_all.deb Size: 1503960 SHA256: a89c10210269720f42fa1d4986f09ecaa13fc4ea78f1d75fc5ed7ddc6352827f SHA1: c883688f279ec7aaac4c0cc5ac8d1ff27f183533 MD5sum: 015d0c523b10e217eb75e781759c8a80 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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_all.deb Size: 32522 SHA256: 6f15ee7476bbfde85706a4c2f3d03cda6040abdbd999b3894242c38a6b5e5e15 SHA1: 6d50b9fdc6cc95d65b5a36dff938dc20a53f85a6 MD5sum: 490b03520a88f2609b103c8f9e81d538 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 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_all.deb Size: 1816392 SHA256: 5471327f1b831976c7f5fd2e640cea5ad293f6fe3d5dc5c90cad27576dd31c7b SHA1: 24a7b6779e812cb2e0141392940f64f5f9654eab MD5sum: c0d6269ba81e7cde8a02b4ecf5d09a9a 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 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_all.deb Size: 441852 SHA256: c393586f5d860ad1367c994624f64e56f5142eb810b1c7eb398b3a4514ba1e59 SHA1: d709ae60593669a10a6ba1bce7e3597b4ec0cdf9 MD5sum: debae32aab1b2c3078bcd33a7e0a3dbd 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-nipype Source: nipype Version: 0.9.2-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3521 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.9.2-1~nd13.04+1_all.deb Size: 768506 SHA256: 6031eca5799cfec9f8d0037cfd1424c66967f861b44c89e1f3b559f8924171a0 SHA1: 5cd1b910d0a1997524c2ed2e26a6e86439dd5ff9 MD5sum: bde560f80b6cc7937bb7aaf91e010225 Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.9.2-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16563 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.9.2-1~nd13.04+1_all.deb Size: 7621042 SHA256: 18db5684e0554436f54dedafb4d3d73295c326ebfc9ac827fd2cb49cce9ff085 SHA1: ed3323cfa8556d3310f3077224f8075a34005955 MD5sum: 5e2862423bb79616ae1dad000bee10c7 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9348 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.5-1~nd13.04+1_all.deb Size: 3927898 SHA256: 99d1ee2b3f50023989bfbed655b03410d2df4a9b2c37c6831ce5107555c760f4 SHA1: b0ada9f6dfcdaf29008f8233f7894e81f012019d MD5sum: 3472f022b7cb83e5e71251ee60eb7610 Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7693 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.5-1~nd13.04+1_all.deb Size: 6059462 SHA256: cc4bfb0d86027eb98312eb622a6e6834dea2709427e778939db7870731af7ab1 SHA1: 992801b810fcfdb3cf135db1b94e5647b5361e89 MD5sum: c34b07b82384ae963cf656a8e09cea8c Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 247 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd13.04+1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Provides: python2.7-nlopt Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: python Filename: pool/main/n/nlopt/python-nlopt_2.4.1+dfsg-1~nd13.04+1_i386.deb Size: 83454 SHA256: 45a1388ccc5641c043c18766866d591c6bee1c19119f4b0b424ee612070dbe62 SHA1: 5629bf7d445ad37cbf15a25f371bcd9a8abe1c8f MD5sum: db2ca4b670603e4cbd3c949fa4ec4326 Description: nonlinear optimization library -- Python bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the Python bindings. Package: python-openpyxl Source: openpyxl Version: 1.7.0+ds1-1~nd13.04+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~nd13.04+1_all.deb Size: 91950 SHA256: 85b2b60b87f158f379a654ac99c15239a6095024efc9eb2b97ba2e2e4052c4e5 SHA1: d26ab1a664555bb012e58aa4fc3ad4ca3ac9b876 MD5sum: b88ed9a7467757e920c2ede8e5826755 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-pandas Source: pandas Version: 0.14.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8987 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.6~), python-pandas-lib (>= 0.14.1-1~nd13.04+1), python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.14.1-1~nd13.04+1_all.deb Size: 1666616 SHA256: 415e45189af6824076fe30b7dfacb9fdaa34c9fa1e24ab4849f420a263944667 SHA1: 4aaf310205af86773927a404327c5e669b1e8e78 MD5sum: f6c65440c7a279841f070b4e8c36ecfa Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-lib Source: pandas Version: 0.14.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4822 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.14.1-1~nd13.04+1_i386.deb Size: 1745700 SHA256: 465cadb80c7aa33defe90622a78c06a9973d14135a79618fcb0eede884018e43 SHA1: 116fd06cb96b3157d7b067f532c602b6b7c71d0f MD5sum: 2e18b5fdec5bb1afc4a91bbc28096f90 Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.3.0-3~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 725 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.3.0-3~nd13.04+1_all.deb Size: 215588 SHA256: 4416ecd1d0516c35b7ec792b2bab8851e2860d30f14bda2f928c98c92537d8c3 SHA1: 4293cf540754e8158e27eeca8f02af177d85fc99 MD5sum: 46d488174bd34884ae8e01d50ead227e 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: 0.3.0-3~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1243 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_0.3.0-3~nd13.04+1_all.deb Size: 551348 SHA256: b05b6ab08afc6ea3061d54d64ad602d8b7ffaa38677c0453bd40c7337f0ca3cc SHA1: 8eb377439cb246d668408af96cd28c9bdf2d7e0f MD5sum: 818327a07662765b36135f04f5cf41ae Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd13.04+1_all.deb Size: 108522 SHA256: 5c2afaaea25f2e23d0c8b715a21196da047034de4e26227bd3e42a6b5f30d7aa SHA1: a10d6cc71e421d327f2a3b83e719bc67cc3630a7 MD5sum: 550613922b0b145cd729e657a220a429 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1328 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.04+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~nd13.04+1_i386.deb Size: 356226 SHA256: 7f89dd2b116c203d629afe8c4a0c718464eb11861e8cd03c439715102ba0a0df SHA1: 69e0f124f306e2f16995c45516c69913b05e6274 MD5sum: 6c22c6ec0bd5f57e54fdffa7fa278c20 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~nd13.04+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~nd13.04+1_all.deb Size: 818248 SHA256: db03e0e6da1604340b0e261b32b5fbfeb29c5ce61c377a0143c68970b8c84527 SHA1: 66261c89106edb13ad1415cfdc8f980ec0b0b383 MD5sum: 634c2710263e8349bd60a73fd742d18d 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 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_all.deb Size: 175824 SHA256: 8739a9484b7006b204e2cd7d530501ee969178ae5f0e291ef1d7243a6a5cfa6b SHA1: 6a89717511066991e428fc8e7efec413b51d4008 MD5sum: c6787a9174e58de883cd75f9682891f7 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-pyo Version: 0.6.6-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9482 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), libc6 (>= 2.4), liblo7 (>= 0.26~repack), libportaudio2 (>= 19+svn20101113), libportmidi0, libsndfile1 (>= 1.0.20), python (<< 2.8) Recommends: python-tk, python-imaging-tk, python-wxgtk2.8 Homepage: http://code.google.com/p/pyo/ Priority: optional Section: python Filename: pool/main/p/python-pyo/python-pyo_0.6.6-1~nd13.04+1_i386.deb Size: 4807524 SHA256: f1b1f7e33cd76dada443bd67d31dea0844ddf8328d68ba1e073a0801a9c4950a SHA1: 4604c3b3fcc26d3c9603c5e06e7247f8369a9611 MD5sum: ba96359f40fc3e6bd867410712f85b09 Description: Python module written in C to help digital signal processing script creation pyo is a Python module containing classes for a wide variety of audio signal processing types. With pyo, user will be able to include signal processing chains directly in Python scripts or projects, and to manipulate them in real time through the interpreter. Tools in pyo module offer primitives, like mathematical operations on audio signal, basic signal processing (filters, delays, synthesis generators, etc.), but also complex algorithms to create sound granulation and others creative audio manipulations. . pyo supports OSC protocol (Open Sound Control), to ease communications between softwares, and MIDI protocol, for generating sound events and controlling process parameters. . pyo allows creation of sophisticated signal processing chains with all the benefits of a mature, and wildly used, general programming language. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1488 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_i386.deb Size: 425390 SHA256: 2bd1cc8c3df764d58ade43d75766c9c5ad2500e0c28587b536430ac0bb7bb0e6 SHA1: 100b3a8457467b26b5e8b53ae975df21aee96fe3 MD5sum: 15b622ac6a5533ba793064bde47f8dfb 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 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_all.deb Size: 190396 SHA256: a742f5f47842ee38e7491416ea0de9e721716c69c4cf32cae51ad2367a8d89c2 SHA1: c687df5e68cc79fba85924061a7f8e3d9732903e MD5sum: 4e5a040be6b4430eab9ed7922df103ee 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: 0.15.2-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44 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_0.15.2-2~nd13.04+1_all.deb Size: 41384 SHA256: b20d5b695324b092d24fb92e65af6ba3185dbb21f702b56d8eabafb1a67a3d0b SHA1: 1359921e8c83c166dddd18382665be431aa9a50c MD5sum: acfa1426f0494d68b05937b548e51e27 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 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_all.deb Size: 5636 SHA256: edd8cc37a13fde303ab919fcf0382e1537107b555ee4063bb0fdf252aefb265f SHA1: 47674665c8a46c2db0e7fec5f3788e0508a769ea MD5sum: 5c856d0a92039b7a0d29eb5a2a90a834 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~nd13.04+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~nd13.04+1), python (>= 2.7.1-0ubuntu2), python (<< 2.8) 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~nd13.04+1_all.deb Size: 4538304 SHA256: 70a57093bb1b630c026bc7cacb220b8745bef71790b64b81f3ee91e94bc3fe29 SHA1: f58745e31575ab0834728c289ee0351e1f0d3a8b MD5sum: ac02970dbde3897c72124b6c1d595a18 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~nd13.04+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~nd13.04+1_all.deb Size: 14618750 SHA256: 96d3ce3d82f535b0cf4761e0ab80b663a0d3834c95f07554b0b2567c276a59f7 SHA1: a97e414b8b7f6f32a00963a443ccf564b8fa868a MD5sum: ebbd55b17d3d641ab3331eecc156900a Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.10.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7411 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), 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_0.10.1-1~nd+1_i386.deb Size: 982388 SHA256: 83280730f9df605f66d977c739ce7aa0d73fd1767f134c8d291aa6fc4ef599f5 SHA1: 2e4534cc9093f56dac786064ae17ce303e20b706 MD5sum: 9e9046ee03889bee0c75b6c331520edf 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: 0.15.2-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4068 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy, python-scipy, python-sklearn-lib (>= 0.15.2-2~nd13.04+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_0.15.2-2~nd13.04+1_all.deb Size: 1210566 SHA256: c95c530c8f8321536d1386a68b3206d4155101f84c7c77afb37ac4e42c03894f SHA1: e81c1fa90d793c3aee290dc647c627c1ae2a80c8 MD5sum: 3500ea1f29fda760aa00ce842ea83ad0 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: 0.15.2-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 66389 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_0.15.2-2~nd13.04+1_all.deb Size: 50993768 SHA256: 7c107594d78a3ad17cf037d5f8ca417bc741edac6bdeb737e1d7ff955dc4f3f6 SHA1: d6bf646a4ba82601060f744c0664454479ed16bb MD5sum: 778773f831bfb6f11e7bc5bd6b98a049 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: 0.15.2-2~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3874 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_0.15.2-2~nd13.04+1_i386.deb Size: 1576064 SHA256: dea91e401dac72fa43252871dfede99857ca834cd1b583140e263ac9c8cec3f0 SHA1: 6e89b69c6f675762e7aaf9680a15fd1d3ee9a8f9 MD5sum: 90625db3b4e8a8dbe2b06c84f36a967d 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~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4009 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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~nd13.04+1_all.deb Size: 1847880 SHA256: 379f4058e083e07aa6eacb71e7c8a0660492df755ff7cd485b1448eae26e97d4 SHA1: e3c7c59a3341f43168d321a74e13607cf3ebd756 MD5sum: 794e56f72fc037355fc68d1dd24408e9 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: 0.4.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2017 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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_0.4.1-1~nd13.04+1_all.deb Size: 401300 SHA256: 7e36271bebc926fd6a4137f162575178a763ebd5b4204d62d790f4d93d95f5a5 SHA1: 3046c2f4388c1ef502b2b67d596b9eb185eee1b4 MD5sum: 4182e8a63e9605ed55f30a3bacf36789 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20432 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd13.04+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_all.deb Size: 4682438 SHA256: 2a21d2b08addd50290ec03381e2ee92c1e7be25e9a5ef0abd907c4416442f933 SHA1: c98e31786fde183d1d5ab82dccd28a1547f61941 MD5sum: bbfda8bb9802b1ab252f1414f429f82a 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32549 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_all.deb Size: 9253286 SHA256: 6fe726032db301674769285750d43dabeadc30ff9771efcc14e2095f0f911177 SHA1: be795b20ee9adfe7fcb982602430c5d89c70e8b7 MD5sum: 2d2d70302b9c703bc34ff802b3d9830b Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-statsmodels-lib Source: statsmodels Version: 0.5.0-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.5.0-1~nd13.04+1_i386.deb Size: 91578 SHA256: b3d915773f6d0799e61e5e4a4171c79fb4209d04a3b18356c90d373db0f1d573 SHA1: 85d809a856c478997446a175b21803c8ccb2fd24 MD5sum: ce07a5cb349c61af2a1b39c252420678 Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.13.18-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 519 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, libbiosig1, libc6 (>= 2.4), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libhdf5-7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libbiosig-dev, libsuitesparse-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.13.18-1~nd13.04+1_i386.deb Size: 229016 SHA256: bc093f01db9ab79c22a423bfbc7182958472b6bbc1941c52f9994247c92fa228 SHA1: f90a1312913aba6df1530f361840bd957661c8a6 MD5sum: fbc80814fc0ecbf18f6d6bb3b1d9891d 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 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_all.deb Size: 28126 SHA256: d027822bf6edf7f8e4a4726abfa4bff05a553010e617229cf66c9ebc39f260ae SHA1: ae3d0fa877af7818bb783d737f8a8df882765042 MD5sum: db1308bda1624dc4cacc037c4519bbc7 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 Architecture: i386 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 1662 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_i386.deb Size: 338370 SHA256: c65bcafa75da76cf07ad3f82c619d45c6587a4e9232133ac99aa483dc7cf98f1 SHA1: b2ee7268590847385f596c7f3e780f903e0d57eb MD5sum: da1b4ba4998e09f36f3e5d7a86af2629 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: python-visionegg Source: visionegg Version: 1.2.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1726 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgl1-mesa-glx, python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Homepage: http://www.visionegg.org Priority: optional Section: python Filename: pool/main/v/visionegg/python-visionegg_1.2.1-1~nd13.04+1_i386.deb Size: 665440 SHA256: 79b33672568837eb36447ee03067eb67bddc1afc061f61ee0e53addb966acc4b SHA1: 353d1d6d2ad25ef3caedd3a009d42a2fd4d5e89d MD5sum: 2ff6bfb840fc9f1efb9b6fb7ea1f371f Description: Python library for 2D/3D visual stimulus generation The Vision Egg is a programming library that uses standard, inexpensive computer graphics cards to produce visual stimuli for vision research experiments. Package: python3-datalad Source: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4665 Depends: neurodebian-popularity-contest, git-annex (>= 8.20200309~) | git-annex-standalone (>= 8.20200309~), patool, p7zip-full, python3 (>= 3.7), python3-annexremote, python3-distro, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners (>= 0.14~), python3-gitlab, python3-humanize, python3-importlib-metadata | python3 (>> 3.10), python3-iso8601, python3-keyring, python3-keyrings.alt | python3-keyring (<= 8), python3-mock, python3-msgpack, python3-pil, python3-platformdirs, python3-requests (>= 1.2), python3-secretstorage, python3-simplejson, python3-six, python3-tqdm, python3-chardet, python3-packaging, python3:any Recommends: python3-boto, python3-exif, python3-html5lib, python3-httpretty, python3-jsmin, python3-libxmp, python3-lzma, python3-mutagen, python3-pytest, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, datalad-container, datalad-crawler, datalad-neuroimaging, python3-bs4, python3-numpy Breaks: datalad-container (<< 1.1.2) Homepage: https://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.17.5-1~nd+1_all.deb Size: 958872 SHA256: 1f3e16c16863bab40ba92405109ab26c78f19e3e86e2b38733a035221c4e7744 SHA1: 873da190eb5ee83576ff519c2d564e1f841abe5b MD5sum: 7a97a6f55929cc103dd60d7783a9565e Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python3-joblib Source: joblib Version: 0.8.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 251 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.8.3-1~nd13.04+1_all.deb Size: 71374 SHA256: 5effc03ece7128e7da9949182a4c6c1804e6847d104ccc7704e5c3bae83d34de SHA1: 552d1ec1bd839fc7dcadfd2d92342735ca217c4e MD5sum: b1bad6cfa47344140752d2976ade04de 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. . This package contains the Python 3 version. Package: python3-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1457 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), 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_all.deb Size: 472534 SHA256: d3239c36162185a4ef03148ce61949c6f7a9e74670d56c88722e4200721b57dc SHA1: 2562033ca9918601e8f0cd28eff8146a5a610d52 MD5sum: 735efdc181c99b658b0e9276ea66e384 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1502 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libopenmpi1.3, python3 (>= 3.3), python3 (<< 3.4) 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~nd13.04+1_i386.deb Size: 479116 SHA256: 6f635e412ec6d65c45353d895c752d8b588e7b768fe7f406c896b612061d01d7 SHA1: 29fac90a097a982724eec7ec2cf9e2d5ebd41df6 MD5sum: 69aa8e0afe6c584d391d0fc635821a5c 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~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3583 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3.1+hg20131106-1~nd13.04+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~nd13.04+1_i386.deb Size: 1198848 SHA256: 8164caaaf322b6325ec4b7f7dffa9a04d7492d2a784f5a404ba7d82aada2f442 SHA1: eaab0aa730bbedbfb10753bac1e46045b11c6aa6 MD5sum: 60d2cf0687c78473d2b8c9236ec73617 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-pandas Source: pandas Version: 0.14.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8918 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3-dateutil, python3-tz, python3-numpy (>= 1:1.6~), python3-pandas-lib (>= 0.14.1-1~nd13.04+1) Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-six Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.14.1-1~nd13.04+1_all.deb Size: 1660912 SHA256: b7342abe703832329309a13101abd14ad713050bad039efdbd87e1dd4b962ada SHA1: 11f747c7cfc07072008407b09a02e9c1a81f5149 MD5sum: aeb0a6fc27b5fa3a22ab8012695a2d1f Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.14.1-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4774 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), python3-numpy (>= 1:1.7-0~b1), python3-numpy-abi9, python3 (>= 3.3), python3 (<< 3.4) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.14.1-1~nd13.04+1_i386.deb Size: 1711396 SHA256: 8b44e307bcd6fce513b3aac7b6a44abcd17a0d1be93b6224c75456aaffd41d4c SHA1: 6b91f04490a5e903ecf16c8d62afb350313deea8 MD5sum: 7ca28911d14dfb6b2ddb10eedd0ad39a Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.3.0-3~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 719 Depends: neurodebian-popularity-contest, python3 (>= 3.2.3-3~), python3-numpy Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.3.0-3~nd13.04+1_all.deb Size: 214108 SHA256: 704c310f30f81fe11cd54fb5f7f78746d376f330caa0e687a45395786ee91446 SHA1: d02159d5e72db8b2d12b1a1f9d48e7769a459c11 MD5sum: 122a913f8d691558eba553f43dbbd72a 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~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6178 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-skimage-lib (>= 0.9.3-1~nd13.04+1), python3 (>= 3.2.3-3~) 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~nd13.04+1_all.deb Size: 4532470 SHA256: 4989d126acf8958f76b2f68cf79647afe8691c728f77de03475724b66b1fb20e SHA1: 8fdf86d214857739d84c324e38b7916a16813234 MD5sum: 97688f6d6ac6038b1e1cfeda08e9281e 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: 0.10.1-1~nd+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6883 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.4) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.10.1-1~nd+1_i386.deb Size: 905700 SHA256: 27be3eefe96e8c1754b96646fa70e371b1591252f34764203a9de515b9d6fc52 SHA1: 4bc5d6a4a4dbed47658f1c4ffee0680e4f152318 MD5sum: 95b2fb523aa05ad91dda93474ddf14c2 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: 0.4.8-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2954 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 (>= 4.4.0), libvtk5.8, libvtk5.8-qt4, nifti2dicom (= 0.4.8-1~nd13.04+1), nifti2dicom-data (= 0.4.8-1~nd13.04+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.8-1~nd13.04+1_i386.deb Size: 633156 SHA256: f6c9ddbaf5425df42deaee3d6d3f6a699e6a36b933840da53ad9ab0e412c8964 SHA1: ae8a7f1c6b5f8fce12520a9fa46dcd3528546853 MD5sum: 783b84bd865c537aaa031d9ba47783f6 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: rclone Version: 1.41-1~ndall0 Architecture: i386 Maintainer: Debian Go Packaging Team Installed-Size: 16874 Depends: libc6 (>= 2.3.6-6~) Built-Using: go-md2man (= 1.0.8+ds-1), golang-1.10 (= 1.10.3-1), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-github-a8m-tree (= 0.0~git20171213.cf42b1e-1), golang-github-abbot-go-http-auth (= 0.0~git20150714.0.46b9627-2), golang-github-aws-aws-sdk-go (= 1.12.79+dfsg-1), golang-github-azure-azure-sdk-for-go (= 10.3.0~beta-1), golang-github-azure-go-autorest (= 8.3.1-1), golang-github-coreos-bbolt (= 1.3.1-coreos.5-1), golang-github-davecgh-go-spew (= 1.1.0-4), golang-github-dgrijalva-jwt-go-v3 (= 3.1.0-2), golang-github-djherbis-times (= 1.0.1+git20170215.d25002f-1), golang-github-dropbox-dropbox-sdk-go-unofficial (= 4.1.0-1), golang-github-go-ini-ini (= 1.32.0-2), golang-github-google-go-querystring (= 0.0~git20170111.0.53e6ce1-4), golang-github-jlaffaye-ftp (= 0.0~git20170707.0.a05056b-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kardianos-osext (= 0.0~git20170510.0.ae77be6-5), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-mattn-go-runewidth (= 0.0.2+git20170510.3.97311d9-1), golang-github-ncw-go-acd (= 0.0~git20171120.887eb06-1), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-google-cloud (= 0.9.0-5), golang-goprotobuf (= 0.0~git20170808.0.1909bc2-2) Homepage: https://github.com/ncw/rclone Priority: optional Section: net Filename: pool/main/r/rclone/rclone_1.41-1~ndall0_i386.deb Size: 4618876 SHA256: f3d9fca60ef0cfd3221be8ef088af8a9fc3a2a2c99955034fe6b29a9e18eb42e SHA1: 50b47feb7ce2f1441e1a5cef84f91ef20d1e104f MD5sum: 8c73c00b1e80467960cb535af6d6e58f Description: rsync for commercial cloud storage Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers: . - Google Drive - Amazon S3 - Openstack Swift / Rackspace cloud files / Memset Memstore - Dropbox - Google Cloud Storage - Amazon Drive - Microsoft One Drive - Hubic - Backblaze B2 - Yandex Disk Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+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_all.deb Size: 10744012 SHA256: 8cbaf2ef8a3621e1a45f8046a5a4b3f5018599cd5fd061dbdab3f6f636db55dc SHA1: 358a47eca3c2a8e45383012ebb1db5ed7e315d4f MD5sum: 2ea4c1626f3ecc1a0f8b72afe93d7325 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 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_all.deb Size: 52166644 SHA256: adf5ccd28c33d360fddc672827cc45f128dd95d107e6fc80ec7b5f01013199b8 SHA1: 555fd27c1066c8cdc3f9d5ca88e1a5604af0f318 MD5sum: 007b37221423d90e041d57b47f112413 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 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_all.deb Size: 8990888 SHA256: 26ace888d49d3abb1c4525fff11e3538aaf54bdeb7bd0f37720b5a32c211055d SHA1: 3e7bd77be9b08a8227586a6138fba786fa7a5365 MD5sum: 823a54d07acd71360de860ff3f62e019 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~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python, python-spyderlib (= 2.2.5+dfsg-1~nd13.04+1) Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: devel Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd13.04+1_all.deb Size: 36074 SHA256: 95beb4bfca945126e17f36852c4a4ce3cc8f7e7875c21f22d8e7b6de27cb0e73 SHA1: b6377d55d2fb282b643d0e6aca5498fcd1b905eb MD5sum: c15381c5f383a2cb05d27e0ab7c20525 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: 0.4.2-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1128 Depends: neurodebian-popularity-contest, python (>= 2.7.1-0ubuntu2), python (<< 2.8), 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_0.4.2-1~nd13.04+1_all.deb Size: 577518 SHA256: ec09902351934aa97cdaea413bcfb81849d1ece62997ce6d2b2825cb49ea7077 SHA1: 82f0bf3a62774c8225474e519c5d1e61d448585c MD5sum: 14d4df8a1ad15126c3a87f890cd14823 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 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_all.deb Size: 28806 SHA256: f4d0a92bd82ccf13995bd023e60482c9bb6e5bcc276aacf8d6d71f47c726ac91 SHA1: 5d37dfd09ba13dca96797dc779dfd58616624062 MD5sum: 64c06762e13f6bd6a33f11383612ccc0 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: 0.13.18-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2098 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 | libatlas3-base, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1), python (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python2.7, libbiosig-dev, libsuitesparse-dev, 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_0.13.18-1~nd13.04+1_i386.deb Size: 795020 SHA256: 7b5b00421a81b409c4ec4c3aabe1e56dceafb4fbaa8f3bce610ea8da6e786e86 SHA1: 6a81bdd6f0693e852af5bb41fb2bb9733be0fa04 MD5sum: cc4a250a51325d3576fb0f0db438cf04 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: 0.13.18-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 15794 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_0.13.18-1~nd13.04+1_i386.deb Size: 5944952 SHA256: ecd9af6d22232f7629953b931fbab626374f9d988919163a390d02dbc7e173f0 SHA1: c4786e0943076eb0fe6ab1ea55f49fb54f90a1a1 MD5sum: 1c22173cd7bcc691b86971344c6072f6 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. This package contains the debug symbols for Stimfit. Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+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_all.deb Size: 99674 SHA256: 4bb183a82062eea15a25438731463d7d3a57ac1fd8bbe3f38101b6c3c08c6db2 SHA1: 045ce201ed946332c8971bc0b8f92774aa49e90b MD5sum: 7b33e1503852f85c3d82cd5c0d1c0e54 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: utopia-documents Version: 2.4.4-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18721 Depends: neurodebian-popularity-contest, libboost-python1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.11), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.8 (>= 1.8.0), libglu1-mesa | libglu1, libpcre3 (>= 8.10), libpcrecpp0 (>= 7.7), libpython2.7 (>= 2.7), libqglviewer-qt4-2 (>= 2.3.4), libqjson0 (>= 0.7.1), libqt4-network (>= 4:4.7.0~beta1), libqt4-opengl (>= 4:4.5.3), libqt4-script (>= 4:4.5.3), libqt4-svg (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libraptor1 (>= 1.4.21-3), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), python (>= 2.7.1-0ubuntu2), python2.7, python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_2.4.4-1~nd13.04+1_i386.deb Size: 7539414 SHA256: 9309b627fefb3cdf4a50bc6c40dcbc5370943df3ba94303cb9ad93be9cfece4e SHA1: 8ca4b20adf3fa290003d0b4256e6adf772d0926b MD5sum: 60323058526c32b098228d3a1c0e1a5e Description: PDF reader that displays interactive annotations on scientific articles. Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. It makes it easy to explore an article's content and claims, and investigate other recent articles that discuss the same or similar topics. . Get immediate access to an article's metadata and browse the relationship it has with the world at large. Generate a formatted citation for use in your own work, follow bibliographic links to cited articles, or get a document's related data at the click of a button. . Various extensions provide links to blogs, online data sources and to social media sites so you can see what other researchers have been saying about not only the article you're reading but its subject matter too. Package: utopia-documents-dbg Source: utopia-documents Version: 2.4.4-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 43041 Depends: neurodebian-popularity-contest, utopia-documents (= 2.4.4-1~nd13.04+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_2.4.4-1~nd13.04+1_i386.deb Size: 42137996 SHA256: 9199b660eb896c17fcc8b834fb2f4b4f8f08c76245a81548953e9b1f83c3e95f SHA1: 31f884111d109ec954ed3f448352dd5bc5e67ee7 MD5sum: 6efbc60a04af99f9219b7a329a104b4e Description: debugging symbols for utopia-documents Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. . This package contains the debugging symbols for utopia-documents. Package: vowpal-wabbit Version: 7.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libvw0 (= 7.3-1~nd13.04+1) Suggests: vowpal-wabbit-doc Homepage: http://hunch.net/~vw/ Priority: optional Section: science Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit_7.3-1~nd13.04+1_i386.deb Size: 20502 SHA256: 35319d6ea28bd344f2f4addfba47f0dbd8841a065b523dd0d968f8ec60af96f8 SHA1: ed933ac6adfe712b64d5e00be1cfd515dd2426e3 MD5sum: 127977d29df55ff99131ff1960bae19b Description: fast and scalable online machine learning algorithm Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing Package: vowpal-wabbit-dbg Source: vowpal-wabbit Version: 7.3-1~nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5608 Depends: neurodebian-popularity-contest, vowpal-wabbit (= 7.3-1~nd13.04+1) Homepage: http://hunch.net/~vw/ Priority: extra Section: debug Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-dbg_7.3-1~nd13.04+1_i386.deb Size: 2167174 SHA256: 94d948a923fe144fdba1b1bed5e567f8e3854d87865e0cfc0b82ba6cb2d39ab2 SHA1: 546b18999ea73f6dc1029711fb39f90374ee6cd2 MD5sum: fa2653ab7d32ad6c68a876344cbcc2ce Description: fast and scalable online machine learning algorithm - debug files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains debug symbols for the binaries shipped by vowpal-wabbit packages. Package: vowpal-wabbit-doc Source: vowpal-wabbit Version: 7.3-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70918 Depends: neurodebian-popularity-contest Recommends: vowpal-wabbit Homepage: http://hunch.net/~vw/ Priority: optional Section: doc Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-doc_7.3-1~nd13.04+1_all.deb Size: 50202370 SHA256: 9dddf9b5b7a2237d4f2a93efd545d867f3d204f1d05ab4d462bf15ea4b55e986 SHA1: 8e49788bf4e88ece7e82ef40224840f79f2eee52 MD5sum: 55654e0768d8a01e3e339294bbb06565 Description: fast and scalable online machine learning algorithm - documentation Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains examples (tests) for vowpal-wabbit. Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 284 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), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+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_i386.deb Size: 64378 SHA256: 11584fd469c60b38d7722fb52e4224dcd11b9f87b9baced4969e2eedb73064cd SHA1: 895242ad867135ee02f52140ac3783e118fb4ba9 MD5sum: 23e840b1017aece1283396ee89026933 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 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4162 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+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_i386.deb Size: 1592158 SHA256: c8966dd758e36af76a5820259c7e138488d7aa67cfac882f1c133eb5d78b56f0 SHA1: 49c835f7a4162ee9dda93a87cb15aee9025a8f69 MD5sum: 2ad28e221c53bfa49d1f9b936298d15e 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. Package: youtube-dl Version: 2021.12.17-1~nd110+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5937 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3:any Recommends: aria2 | wget | curl, ca-certificates, ffmpeg, mpv | mplayer, python3-pyxattr, rtmpdump, python3-pycryptodome Suggests: libfribidi-bin | bidiv, phantomjs Homepage: https://ytdl-org.github.io/youtube-dl/ Priority: optional Section: web Filename: pool/main/y/youtube-dl/youtube-dl_2021.12.17-1~nd110+1_all.deb Size: 1128692 SHA256: 75859d2f34a475fc0f199cd6d2b73e18c29cda44406530964890dcb790008eca SHA1: 09f85f2abc32eb5e9c2ccd6bfd1354ea332b6489 MD5sum: 6d04814be91bd9f85a7d3793ff2a2fb3 Description: downloader of videos from YouTube and other sites youtube-dl is a small command-line program to download videos from YouTube.com and other sites that don't provide direct links to the videos served. . youtube-dl allows the user, among other things, to choose a specific video quality to download (if available) or let the program automatically determine the best (or worst) quality video to grab. It supports downloading entire playlists and all videos from a given user. . Currently supported sites (or features of sites) are: . 1tv, 20min, 220.ro, 23video, 24video, 3qsdn, 3sat, 4tube, 56.com, 5min, 6play, 7plus, 8tracks, 91porn, 9c9media, 9gag, 9now.com.au, abc.net.au, abc.net.au:iview, abcnews, abcnews:video, abcotvs, abcotvs:clips, AcademicEarth:Course, acast, acast:channel, ADN, AdobeConnect, adobetv, adobetv:channel, adobetv:embed, adobetv:show, adobetv:video, AdultSwim, aenetworks, aenetworks:collection, aenetworks:show, afreecatv, AirMozilla, AliExpressLive, AlJazeera, Allocine, AlphaPorno, Amara, AMCNetworks, AmericasTestKitchen, AmericasTestKitchenSeason, anderetijden, AnimeOnDemand, Anvato, aol.com, APA, Aparat, AppleConnect, AppleDaily, ApplePodcasts, appletrailers, appletrailers:section, archive.org, ArcPublishing, ARD, ARD:mediathek, ARDBetaMediathek, Arkena, arte.sky.it, ArteTV, ArteTVEmbed, ArteTVPlaylist, AsianCrush, AsianCrushPlaylist, AtresPlayer, ATTTechChannel, ATVAt, AudiMedia, AudioBoom, audiomack, audiomack:album, AWAAN, awaan:live, awaan:season, awaan:video, AZMedien, BaiduVideo, Bandcamp, Bandcamp:album, Bandcamp:weekly, bangumi.bilibili.com, bbc, bbc.co.uk, bbc.co.uk:article, bbc.co.uk:iplayer:playlist, bbc.co.uk:playlist, BBVTV, Beatport, Beeg, BehindKink, Bellator, BellMedia, Bet, bfi:player, bfmtv, bfmtv:article, bfmtv:live, BibelTV, Bigflix, Bild, BiliBili, BilibiliAudio, BilibiliAudioAlbum, BiliBiliPlayer, BioBioChileTV, Biography, BIQLE, BitChute, BitChuteChannel, BleacherReport, BleacherReportCMS, blinkx, Bloomberg, BokeCC, BongaCams, BostonGlobe, Box, Bpb, BR, BravoTV, Break, brightcove:legacy, brightcove:new, BRMediathek, bt:article, bt:vestlendingen, BusinessInsider, BuzzFeed, BYUtv, Camdemy, CamdemyFolder, CamModels, CamTube, CamWithHer, canalc2.tv, Canalplus, Canvas, CanvasEen, CarambaTV, CarambaTVPage, CartoonNetwork, cbc.ca, cbc.ca:olympics, cbc.ca:player, cbc.ca:watch, cbc.ca:watch:video, CBS, CBSInteractive, CBSLocal, CBSLocalArticle, cbsnews, cbsnews:embed, cbsnews:livevideo, CBSSports, CCMA, CCTV, CDA, CeskaTelevize, CeskaTelevizePorady, channel9, CharlieRose, Chaturbate, Chilloutzone, chirbit, chirbit:profile, cielotv.it, Cinchcast, Cinemax, CiscoLiveSearch, CiscoLiveSession, CJSW, cliphunter, Clippit, ClipRs, Clipsyndicate, CloserToTruth, CloudflareStream, Cloudy, Clubic, Clyp, cmt.com, CNBC, CNBCVideo, CNN, CNNArticle, CNNBlogs, ComedyCentral, ComedyCentralTV, CommonMistakes, CondeNast, CONtv, Corus, Coub, Cracked, Crackle, CrooksAndLiars, crunchyroll, crunchyroll:playlist, CSpan, CtsNews, CTV, CTVNews, cu.ntv.co.jp, Culturebox, CultureUnplugged, curiositystream, curiositystream:collection, CWTV, DailyMail, dailymotion, dailymotion:playlist, dailymotion:user, daum.net, daum.net:clip, daum.net:playlist, daum.net:user, DBTV, DctpTv, DeezerPlaylist, defense.gouv.fr, democracynow, DHM, Digg, DigitallySpeaking, Digiteka, Discovery, DiscoveryGo, DiscoveryGoPlaylist, DiscoveryNetworksDe, DiscoveryVR, Disney, dlive:stream, dlive:vod, Dotsub, DouyuShow, DouyuTV, DPlay, DRBonanza, Dropbox, DrTuber, drtv, drtv:live, DTube, Dumpert, dvtv, dw, dw:article, EaglePlatform, EbaumsWorld, EchoMsk, egghead:course, egghead:lesson, ehftv, eHow, EinsUndEinsTV, Einthusan, eitb.tv, EllenTube, EllenTubePlaylist, EllenTubeVideo, ElPais, Embedly, EMPFlix, Engadget, Eporner, EroProfile, Escapist, ESPN, ESPNArticle, EsriVideo, Europa, EWETV, ExpoTV, Expressen, ExtremeTube, EyedoTV, facebook, FacebookPluginsVideo, faz.net, fc2, fc2:embed, Fczenit, filmon, filmon:channel, Filmweb, FiveThirtyEight, FiveTV, Flickr, Folketinget, FootyRoom, Formula1, FOX, FOX9, FOX9News, Foxgay, foxnews, foxnews:article, FoxSports, france2.fr:generation-what, FranceCulture, FranceInter, FranceTV, FranceTVEmbed, francetvinfo.fr, FranceTVJeunesse, FranceTVSite, Freesound, freespeech.org, FreshLive, FrontendMasters, FrontendMastersCourse, FrontendMastersLesson, FujiTVFODPlus7, Funimation, Funk, Fusion, Fux, Gaia, GameInformer, GameSpot, GameStar, Gaskrank, Gazeta, GDCVault, generic, Gfycat, GiantBomb, Giga, GlattvisionTV, Glide, Globo, GloboArticle, Go, GodTube, Golem, google:podcasts, google:podcasts:feed, GoogleDrive, Goshgay, GPUTechConf, Groupon, hbo, HearThisAt, Heise, HellPorno, Helsinki, HentaiStigma, hetklokhuis, hgtv.com:show, HiDive, HistoricFilms, history:player, history:topic, hitbox, hitbox:live, HitRecord, hketv, HornBunny, HotNewHipHop, hotstar, hotstar:playlist, Howcast, HowStuffWorks, HRTi, HRTiPlaylist, Huajiao, HuffPost, Hungama, HungamaSong, Hypem, ign.com, IGNArticle, IGNVideo, IHeartRadio, iheartradio:podcast, imdb, imdb:list, Imgur, imgur:album, imgur:gallery, Ina, Inc, IndavideoEmbed, InfoQ, Instagram, instagram:tag, instagram:user, Internazionale, InternetVideoArchive, IPrima, iqiyi, Ir90Tv, ITTF, ITV, ITVBTCC, ivi, ivi:compilation, ivideon, Iwara, Izlesene, Jamendo, JamendoAlbum, JeuxVideo, Joj, Jove, JWPlatform, Kakao, Kaltura, Kankan, Karaoketv, KarriereVideos, Katsomo, KeezMovies, Ketnet, khanacademy, khanacademy:unit, KickStarter, KinjaEmbed, KinoPoisk, KonserthusetPlay, KrasView, Ku6, KUSI, kuwo:album, kuwo:category, kuwo:chart, kuwo:mv, kuwo:singer, kuwo:song, la7.it, laola1tv, laola1tv:embed, lbry, lbry:channel, LCI, Lcp, LcpPlay, Le, Lecture2Go, Lecturio, LecturioCourse, LecturioDeCourse, LEGO, Lemonde, Lenta, LePlaylist, LetvCloud, Libsyn, life, life:embed, limelight, limelight:channel, limelight:channel_list, LineTV, linkedin:learning, linkedin:learning:course, LinuxAcademy, LiTV, LiveJournal, LiveLeak, LiveLeakEmbed, livestream, livestream:original, livestream:shortener, LnkGo, loc, LocalNews8, LoveHomePorn, lrt.lt, lynda, lynda:course, m6, mailru, mailru:music, mailru:music:search, MallTV, mangomolo:live, mangomolo:video, ManyVids, Markiza, MarkizaPage, massengeschmack.tv, MatchTV, MDR, MedalTV, media.ccc.de, media.ccc.de:lists, Medialaan, Mediaset, Mediasite, MediasiteCatalog, MediasiteNamedCatalog, Medici, megaphone.fm, Meipai, MelonVOD, META, metacafe, Metacritic, mewatch, Mgoon, MGTV, MiaoPai, minds, minds:channel, minds:group, MinistryGrid, Minoto, miomio.tv, MiTele, mixcloud, mixcloud:playlist, mixcloud:user, MLB, Mms, Mnet, MNetTV, MoeVideo, Mofosex, MofosexEmbed, Mojvideo, Morningstar, Motherless, MotherlessGroup, Motorsport, MovieClips, MovieFap, Moviezine, MovingImage, MSN, mtg, mtv, mtv.de, mtv:video, mtvjapan, mtvservices:embedded, MTVUutisetArticle, MuenchenTV, mva, mva:course, Mwave, MwaveMeetGreet, MyChannels, MySpace, MySpace:album, MySpass, Myvi, MyVidster, MyviEmbed, MyVisionTV, n-tv.de, natgeo:video, NationalGeographicTV, Naver, NBA, nba:watch, nba:watch:collection, NBAChannel, NBAEmbed, NBAWatchEmbed, NBC, NBCNews, nbcolympics, nbcolympics:stream, NBCSports, NBCSportsStream, NBCSportsVPlayer, ndr, ndr:embed, ndr:embed:base, NDTV, NerdCubedFeed, netease:album, netease:djradio, netease:mv, netease:playlist, netease:program, netease:singer, netease:song, NetPlus, Netzkino, Newgrounds, NewgroundsPlaylist, Newstube, NextMedia, NextMediaActionNews, NextTV, Nexx, NexxEmbed, nfl.com (CURRENTLY BROKEN), nfl.com:article (CURRENTLY BROKEN), NhkVod, NhkVodProgram, nhl.com, nick.com, nick.de, nickelodeon:br, nickelodeonru, nicknight, niconico, NiconicoPlaylist, Nintendo, njoy, njoy:embed, NJPWWorld, NobelPrize, NonkTube, Noovo, Normalboots, NosVideo, Nova, NovaEmbed, nowness, nowness:playlist, nowness:series, Noz, npo, npo.nl:live, npo.nl:radio, npo.nl:radio:fragment, Npr, NRK, NRKPlaylist, NRKRadioPodkast, NRKSkole, NRKTV, NRKTVDirekte, NRKTVEpisode, NRKTVEpisodes, NRKTVSeason, NRKTVSeries, NRLTV, ntv.ru, Nuvid, NYTimes, NYTimesArticle, NYTimesCooking, NZZ, ocw.mit.edu, OdaTV, Odnoklassniki, OktoberfestTV, OnDemandKorea, onet.pl, onet.tv, onet.tv:channel, OnetMVP, OnionStudios, Ooyala, OoyalaExternal, OraTV, orf:burgenland, orf:fm4, orf:fm4:story, orf:iptv, orf:kaernten, orf:noe, orf:oberoesterreich, orf:oe1, orf:oe3, orf:salzburg, orf:steiermark, orf:tirol, orf:tvthek, orf:vorarlberg, orf:wien, OsnatelTV, OutsideTV, PacktPub, PacktPubCourse, pandora.tv, ParamountNetwork, parliamentlive.tv, Patreon, pbs, PearVideo, PeerTube, People, PerformGroup, periscope, periscope:user, PhilharmonieDeParis, phoenix.de, Photobucket, Picarto, PicartoVod, Piksel, Pinkbike, Pinterest, PinterestCollection, Pladform, Platzi, PlatziCourse, play.fm, player.sky.it, PlayPlusTV, PlaysTV, Playtvak, Playvid, Playwire, pluralsight, pluralsight:course, podomatic, Pokemon, PolskieRadio, PolskieRadioCategory, Popcorntimes, PopcornTV, PornCom, PornerBros, PornHd, PornHub, PornHubPagedVideoList, PornHubUser, PornHubUserVideosUpload, Pornotube, PornoVoisines, PornoXO, PornTube, PressTV, prosiebensat1, puhutv, puhutv:serie, Puls4, Pyvideo, qqmusic, qqmusic:album, qqmusic:playlist, qqmusic:singer, qqmusic:toplist, QuantumTV, Qub, Quickline, QuicklineLive, R7, R7Article, radio.de, radiobremen, radiocanada, radiocanada:audiovideo, radiofrance, RadioJavan, Rai, RaiPlay, RaiPlayLive, RaiPlayPlaylist, RayWenderlich, RayWenderlichCourse, RBMARadio, RDS, RedBull, RedBullEmbed, RedBullTV, RedBullTVRrnContent, Reddit, RedditR, RedTube, RegioTV, RENTV, RENTVArticle, Restudy, Reuters, ReverbNation, RICE, RMCDecouverte, RockstarGames, RoosterTeeth, RottenTomatoes, Roxwel, Rozhlas, RTBF, rte, rte:radio, rtl.nl, rtl2, rtl2:you, rtl2:you:series, Rtmp, RTP, RTS, rtve.es:alacarta, rtve.es:infantil, rtve.es:live, rtve.es:television, RTVNH, RTVS, RUHD, RumbleEmbed, rutube, rutube:channel, rutube:embed, rutube:movie, rutube:person, rutube:playlist, RUTV, Ruutu, Ruv, safari, safari:api, safari:course, SAKTV, SaltTV, Sapo, savefrom.net, SBS, schooltv, screen.yahoo:search, Screencast, ScreencastOMatic, ScrippsNetworks, scrippsnetworks:watch, SCTE, SCTECourse, Seeker, SenateISVP, SendtoNews, Servus, Sexu, SeznamZpravy, SeznamZpravyArticle, Shahid, ShahidShow, Shared, ShowRoomLive, Sina, sky.it, sky:news, sky:sports, sky:sports:news, skyacademy.it, SkylineWebcams, skynewsarabia:article, skynewsarabia:video, Slideshare, SlidesLive, Slutload, Snotr, Sohu, SonyLIV, soundcloud, soundcloud:playlist, soundcloud:search, soundcloud:set, soundcloud:trackstation, soundcloud:user, SoundcloudEmbed, soundgasm, soundgasm:profile, southpark.cc.com, southpark.cc.com:español, southpark.de, southpark.nl, southparkstudios.dk, SpankBang, SpankBangPlaylist, Spankwire, Spiegel, sport.francetvinfo.fr, Sport5, SportBox, SportDeutschland, spotify, spotify:show, Spreaker, SpreakerPage, SpreakerShow, SpreakerShowPage, SpringboardPlatform, Sprout, sr:mediathek, SRGSSR, SRGSSRPlay, stanfordoc, Steam, Stitcher, StitcherShow, Streamable, streamcloud.eu, StreamCZ, StreetVoice, StretchInternet, stv:player, SunPorno, sverigesradio:episode, sverigesradio:publication, SVT, SVTPage, SVTPlay, SVTSeries, SWRMediathek, Syfy, SztvHu, t-online.de, Tagesschau, tagesschau:player, Tass, TBS, TDSLifeway, Teachable, TeachableCourse, teachertube, teachertube:user:collection, TeachingChannel, Teamcoco, TeamTreeHouse, TechTalks, techtv.mit.edu, ted, Tele13, Tele5, TeleBruxelles, Telecinco, Telegraaf, TeleMB, TeleQuebec, TeleQuebecEmission, TeleQuebecLive, TeleQuebecSquat, TeleQuebecVideo, TeleTask, Telewebion, TennisTV, TenPlay, TestURL, TF1, TFO, TheIntercept, ThePlatform, ThePlatformFeed, TheScene, TheStar, TheSun, TheWeatherChannel, ThisAmericanLife, ThisAV, ThisOldHouse, TikTok, TikTokUser (CURRENTLY BROKEN), tinypic, TMZ, TMZArticle, TNAFlix, TNAFlixNetworkEmbed, toggle, ToonGoggles, tou.tv, Toypics, ToypicsUser, TrailerAddict (CURRENTLY BROKEN), Trilulilu, Trovo, TrovoVod, TruNews, TruTV, Tube8, TubiTv, Tumblr, tunein:clip, tunein:program, tunein:shortener, tunein:station, tunein:topic, TunePk, Turbo, tv.dfb.de, TV2, tv2.hu, TV2Article, TV2DK, TV2DKBornholmPlay, TV4, TV5MondePlus, tv5unis, tv5unis:video, tv8.it, TVA, TVANouvelles, TVANouvellesArticle, TVC, TVCArticle, TVer, tvigle, tvland.com, TVN24, TVNet, TVNoe, TVNow, TVNowAnnual, TVNowNew, TVNowSeason, TVNowShow, tvp, tvp:embed, tvp:series, TVPlayer, TVPlayHome, Tweakers, TwitCasting, twitch:clips, twitch:stream, twitch:vod, TwitchCollection, TwitchVideos, TwitchVideosClips, TwitchVideosCollections, twitter, twitter:amplify, twitter:broadcast, twitter:card, udemy, udemy:course, UDNEmbed, UFCArabia, UFCTV, UKTVPlay, umg:de, UnicodeBOM, Unistra, Unity, uol.com.br, uplynk, uplynk:preplay, Urort, URPlay, USANetwork, USAToday, ustream, ustream:channel, ustudio, ustudio:embed, Varzesh3, Vbox7, VeeHD, Veoh, Vesti, Vevo, VevoPlaylist, VGTV, vh1.com, vhx:embed, Viafree, vice, vice:article, vice:show, Vidbit, Viddler, Videa, video.google:search, video.sky.it, video.sky.it:live, VideoDetective, videofy.me, videomore, videomore:season, videomore:video, VideoPress, Vidio, VidLii, vidme, vidme:user, vidme:user:likes, vier, vier:videos, viewlift, viewlift:embed, Viidea, viki, viki:channel, vimeo, vimeo:album, vimeo:channel, vimeo:group, vimeo:likes, vimeo:ondemand, vimeo:review, vimeo:user, vimeo:watchlater, Vimple, Vine, vine:user, Viqeo, Viu, viu:ott, viu:playlist, Vivo, vk, vk:uservideos, vk:wallpost, vlive, vlive:channel, vlive:post, Vodlocker, VODPl, VODPlatform, VoiceRepublic, Voot, VoxMedia, VoxMediaVolume, vpro, Vrak, VRT, VrtNU, vrv, vrv:series, VShare, VTM, VTXTV, vube, VuClip, VVVVID, VVVVIDShow, VyboryMos, Vzaar, Wakanim, Walla, WalyTV, washingtonpost, washingtonpost:article, wat.tv, WatchBox, WatchIndianPorn, WDR, wdr:mobile, WDRElefant, WDRPage, Webcaster, WebcasterFeed, WebOfStories, WebOfStoriesPlaylist, Weibo, WeiboMobile, WeiqiTV, Wistia, WistiaPlaylist, wnl, WorldStarHipHop, WSJ, WSJArticle, WWE, XBef, XboxClips, XFileShare, XHamster, XHamsterEmbed, XHamsterUser, xiami:album, xiami:artist, xiami:collection, xiami:song, ximalaya, ximalaya:album, XMinus, XNXX, Xstream, XTube, XTubeUser, Xuite, XVideos, XXXYMovies, Yahoo, yahoo:gyao, yahoo:gyao:player, yahoo:japannews, YandexDisk, yandexmusic:album, yandexmusic:artist:albums, yandexmusic:artist:tracks, yandexmusic:playlist, yandexmusic:track, YandexVideo, YapFiles, YesJapan, yinyuetai:video, Ynet, YouJizz, youku, youku:show, YouNowChannel, YouNowLive, YouNowMoment, YouPorn, YourPorn, YourUpload, youtube, youtube:favorites, youtube:history, youtube:playlist, youtube:recommended, youtube:search, youtube:search:date, youtube:subscriptions, youtube:tab, youtube:truncated_id, youtube:truncated_url, youtube:watchlater, YoutubeYtBe, YoutubeYtUser, Zapiks, Zattoo, ZattooLive, ZDF, ZDFChannel, zingmp3, Zype