Package: aghermann Version: 1.0.6-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1501 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp8v5, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 5.2), libunique-3.0-0 (>= 2.90.1), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.6-1~nd15.04+1+nd15.10+1_i386.deb Size: 527790 SHA256: cedcf548f47fc09ffe3844d78f5cd3be39088f154c91ce42185978fa80d27ca1 SHA1: 22ba0a341754f99baeb0b901fb2fb530aa4c34c8 MD5sum: f5c203a9ddb504bc1d71ca81d9b6c834 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: bats Version: 0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: neurodebian-popularity-contest Homepage: https://github.com/sstephenson/bats Priority: optional Section: shells Filename: pool/main/b/bats/bats_0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 14512 SHA256: 6881fb51498874279b777b47edf727399a415a395d2680fc9ce2982ca4d62931 SHA1: 544960ea5fd3dbc490f0b8f6b7aacdc64759e076 MD5sum: 5eaaf67aeab77cb9788aef572aae6d42 Description: bash automated testing system Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. Bats is most useful when testing software written in Bash, but you can use it to test any UNIX program. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 724 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod2.1.2, 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_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 256914 SHA256: e62db57ce0d573cf7e9ba6c39cf2d24192deb4006e24b1aa56ad14152f8c6226 SHA1: f6a793f384c73a0839fe83eb6e5e45be1c1ae472 MD5sum: b657293de77e29a794488695a26f7a8b 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: btrbk Version: 0.20.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, perl, libdate-calc-perl, btrfs-tools (>= 3.14) Suggests: openssh-client Homepage: http://www.digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.20.0-1~nd15.04+1+nd15.10+1_all.deb Size: 32996 SHA256: 64771353bbba494c07255cfb872406e92ba45128061cddef3616cc95ab724358 SHA1: ec74b9f39f7596110520e91445430228c13e9a05 MD5sum: 459c2cea7715513b4bf1a1e6e0b01ac1 Description: backup tool for btrfs volumes Backup tool for btrfs volumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations at once, with ssh and configurable retention support (daily/weekly/monthly). Package: btrfs-tools Version: 4.1.2-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3639 Depends: neurodebian-popularity-contest, e2fslibs (>= 1.42), libblkid1 (>= 2.17.2), libc6 (>= 2.8), libcomerr2 (>= 1.01), liblzo2-2, libuuid1 (>= 2.16), zlib1g (>= 1:1.2.0) Homepage: http://btrfs.wiki.kernel.org/ Priority: optional Section: admin Filename: pool/main/b/btrfs-tools/btrfs-tools_4.1.2-1~nd15.04+1+nd15.10+1_i386.deb Size: 529750 SHA256: eaeb9a2e8bacb3cabdaf78ccbf6b420daf1256bfcb65f107a8611a99084fc071 SHA1: 298c379e574783e1b0e3639c3dbeb69145daab85 MD5sum: 9a42edcea69a155d7e2327beb1e34901 Description: Checksumming Copy on Write Filesystem utilities Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains utilities (mkfs, fsck) used to work with btrfs and an utility (btrfs-convert) to make a btrfs filesystem from an ext3. Package: btrfs-tools-dbg Source: btrfs-tools Version: 4.1.2-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5094 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd15.04+1+nd15.10+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd15.04+1+nd15.10+1_i386.deb Size: 4238262 SHA256: 0d9efe85c437384726b1215a2a24911bb37949b7c9d8818922b4453d5bf06869 SHA1: 9136916d535bee4880c887b774c6cc22b6a7314b MD5sum: 439a5fe284623d39990c5f8aea964a5c Description: Checksumming Copy on Write Filesystem utilities (debug) Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains the debugging symbols. Package: cde Version: 0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 903 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 151236 SHA256: 0ebcde49377373c0cec19acd9fb4a7c1279755a3fd8b9beffdeb0f5d0662dce1 SHA1: 202f02f2b1a9007e0bde7f7481ae5c36951c0203 MD5sum: a361f5a642a2b245e5dfe7e8d0952865 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: cnrun-tools Source: cnrun Version: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 54 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.3-1~nd15.10+1_i386.deb Size: 17608 SHA256: f1fbc2b696d0510dd12cf7fda0b51361290894081294d3edb85cb6b18e067b5d SHA1: 0d2b093731bf8c38673d8dc3689a9d28257082d0 MD5sum: eb4c7a5414e56bd7143f21a8324bc6f2 Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15696 SHA256: 9446cf3dc32428e31abba6f37f8ee70e4c72b623421e7b720734cb91a8423d2f SHA1: 50cb948a2ef0e59005fc394ece350ee2d2d015cd MD5sum: e8f39c3fea6a6fb2d9738d19dd2acda3 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15706 SHA256: c6739597f455d15f2d66e36a86527ec4848bf6efacfa5e167cba5cf68c49c111 SHA1: 4fb6d0d470ec33d187f36339c681327ee893ee80 MD5sum: db768bde0769b36c2d98ba681f6e9c93 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15704 SHA256: a3bb994ee3797ad5762fbeefd4c9bf172db5aa8adf43b4e018b0edbb4bf26798 SHA1: 5751d282c0fc3bdd1d953562a157d09a50a8f810 MD5sum: a5f950875317d283ff02c6188eff4b4f Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 28 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 15706 SHA256: 4c54ed054045eb3703e0894e1f8457b97a60d68798c3bc7d60aa8304850f46bb SHA1: afa7450cc412a8289853bb2d2e06e0ab101061ac MD5sum: 0fd9590de47f6118ced61dafb416b94e Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: connectome-workbench Version: 1.1.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 39068 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 (>= 4.9), libosmesa6 (>= 10.2~), 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 (>= 5.2), zlib1g (>= 1:1.2.3.4) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.1.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 19655884 SHA256: 3676785a85a419feb0b0b3538b19ba1fb30ff4c37f025446de6b042cb9cd16fc SHA1: 12c0a607810ab5462330f051635f629b3d935226 MD5sum: ef9efdf622b7530b2b34fcbd2523fc3c 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: 1.1.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 104095 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.1.1-1~nd15.04+1+nd15.10+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.1.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 102562550 SHA256: 4c72eefa11ef7f3bef36fd1ad8839144f1cd5e19722104276d523d9fc9579928 SHA1: 5f0cf21c92a1cc6335ce9382b4f62d151094320a MD5sum: 141a0da7698718a5e078ec7796c50947 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: dcm2niix Version: 0.20150909.1+git1-g8914c07-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 207 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_0.20150909.1+git1-g8914c07-1~nd15.04+1+nd15.10+1_i386.deb Size: 88820 SHA256: d325a93eccf92eadf1e869bcd2e3e9432edd1ae68de1e259c4f55affa59f773a SHA1: c400cbd246105907129a05047aa83b89a59df949 MD5sum: 045e0a0c809a18468bba8ed600118152 Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 37288 SHA256: dfee2d62a8b21f45486fd0b2c5a442910dae14e76707ffb567b9b17439a17606 SHA1: 06f0dbaa7d4fb3c93f289e3cd7aa335d7b680047 MD5sum: f004ec2ca398fdd609a45e2e1b35f54e 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: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd15.04+1+nd15.10+1_all.deb Size: 1182 SHA256: 60b6d2c21158c4b47d2345eed3adfce849ecddb95da5e5f6eab8147e1702e10b SHA1: 56bcaf82bfd7a9b340454c6740d80b6853fe800d MD5sum: e72f3aca5118a4c29a8b436cc7095d92 Description: GNU implementation of the IPMI protocol FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This metapackage depends on all separate modules of freeipmi. Package: freeipmi-bmc-watchdog Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 45170 SHA256: f954f6a13827e02cb456f8b7853797c0fb7f62247f0ef4245eac0c8d9800155b SHA1: 3463eebbbe23bb3328cc97941e33d6a75852ba24 MD5sum: 13c674760db2880505efa06ebb488a9f Description: GNU implementation of the IPMI protocol - BMC watchdog FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a watchdog daemon for hardware BMC watchdogs. Package: freeipmi-common Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 344 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest Suggests: freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-common_1.4.9-1~nd15.04+1+nd15.10+1_all.deb Size: 189340 SHA256: 8c8771e9f18e42173b0e14bab4ca2f15ec66624697b7f2742331e2a3db33e670 SHA1: ac695cc3eeeedfa7c22d9153d669a72bbc905ebd MD5sum: 1c4ac4e1b0f954c734cb90717604f6db Description: GNU implementation of the IPMI protocol - common files FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package provides configuration used by the rest of FreeIPMI framework and generic documentation to orient the user. Package: freeipmi-ipmidetect Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 39722 SHA256: 2ae6f6d3bb6d4b3f1a05d66e5171ccaaa64f662d201ece4ccd594e8f98903723 SHA1: 7e000609c6ab2829412547c6f19b16f2888bd0d2 MD5sum: 0dbe5e90d6202a4512cd783bbaeff683 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a tool and a daemon for detecting IPMI nodes. Package: freeipmi-ipmiseld Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 215 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 81510 SHA256: ba91bd5a287199d91e5dcd4a12af2d5115324b191d71119dff4fe847ff2d2065 SHA1: 06a95d3dc6bc3c9228b4ac09e83034243e49d5fe MD5sum: 6619562353fe9e7f54c6699ff89621d0 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains ipmiseld which takes the system event log from the BMC and imports it to syslog Package: freeipmi-tools Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3035 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.9-1~nd15.04+1+nd15.10+1), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Suggests: freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-tools_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 621360 SHA256: 4751473665e4be39ad27ddcc33e563849d34eafec68cae8fc0d8668f03d034a7 SHA1: eb7423b8f5a6100999f72eb509ae6ad354e1b64d MD5sum: e968fcf1f9041883ce40115e488d5c44 Description: GNU implementation of the IPMI protocol - tools FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains assorted IPMI-related tools: * bmc-config - configure BMC values * bmc-info - display BMC information * ipmi-chassis - IPMI chassis management utility * ipmi-fru - display FRU information * ipmi-locate - IPMI probing utility * ipmi-oem - IPMI OEM utility * ipmi-pet - decode Platform Event Traps * ipmi-raw - IPMI raw communication utility * ipmi-sel - display SEL entries * ipmi-sensors - display IPMI sensor information * ipmi-sensors-config - configure sensors * ipmiconsole - IPMI console utility * ipmiping - send IPMI Get Authentication Capabilitiy request * ipmipower - IPMI power control utility * pef-config - configure PEF values * rmcpping - send RMCP Ping to network hosts Package: freenect Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.5, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.5.3-1~nd15.10+1_i386.deb Size: 8638 SHA256: 0d8849549cbd84991fbc3a56014e88f8b6c39cb5b57f326e6410bc5623109ac8 SHA1: 76aac5ecc0935cd7eb6cd20984837be5f0a47d92 MD5sum: 8ec8f8719b29a89ec36d15b03eb3ecc6 Description: library for accessing Kinect device -- metapackage libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the metapackage to install all components of the project. Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 74 Depends: neurodebian-popularity-contest, python, python-matplotlib, python-nibabel, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 14008 SHA256: 7914c84001d5d40395cd90f595918f2d555e064191eb0c82e12482b8f9342b51 SHA1: 29f0aa4897a3ab0df34c0714b15c4edb0ca36a9c MD5sum: d276326178c61759af9fbda0e55984fe Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: gcalcli Version: 3.3.2-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1763 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.3.2-1~nd15.04+1+nd15.10+1_all.deb Size: 1669548 SHA256: 04a1ba2fcaaf60aed7be641d21c048c3544c6c7e38b47f93ae7ae6cdd721ba93 SHA1: ec99b16d7ddc52b469f57735f3d847e0025538fe MD5sum: b6e4b4b45ec43d2850198dd064c0c8a6 Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: git-annex-standalone Source: git-annex Version: 6.20160115+gitg1fe1308-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 403350 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: graphviz, bup, tahoe-lafs, libnss-mdns Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20160115+gitg1fe1308-1~ndall+1_i386.deb Size: 28688570 SHA256: ba9776c0c2f9d3b30af6303c0a7f1a7245d53079baefa647c64e70ca2079863f SHA1: 9b80479d79bf015de55f34e8dc6b151958ea899c MD5sum: a54769d703bd6ec982263d0be58a6b9d Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . 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 a dozen 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: git-annex-standalone-dbgsym Source: git-annex Version: 6.20160115+gitg1fe1308-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 39 Depends: git-annex-standalone (= 6.20160115+gitg1fe1308-1~ndall+1) Homepage: http://git-annex.branchable.com/ Priority: extra Section: debug Filename: pool/main/g/git-annex/git-annex-standalone-dbgsym_6.20160115+gitg1fe1308-1~ndall+1_i386.deb Size: 9128 SHA256: 7e87d731bfb7c6ef265f068306a521c9cfe037d3027faaa0f18c1b70a803dfc5 SHA1: 391e41254bd20cf2a5942f36690b34d09bcf3b82 MD5sum: 9e0fc7d13b6d8e13f97b835513e8342e Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 8f6f3d23dd9d1fb3f208bf0b95fc198d8d444fc8 8f6f3d23dd9d1fb3f208bf0b95fc198d8d444fc8 Package: heudiconv Version: 0.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 49 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd15.04+1+nd15.10+1_all.deb Size: 10308 SHA256: 30d0e4ed576cac2717b74d400973e01a200ece9ed614077c3ff559ab0c11fb6e SHA1: 660b1b59c76680b903c6185b7b433335e4e2cf5d MD5sum: 10f70c3a99e585206dee3f9403d8f7fe Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: htcondor Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 12774 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1), perl, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-callout0 (>= 3), libglobus-common0 (>= 15), libglobus-ftp-client2 (>= 7), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gram-protocol3 (>= 11), libglobus-gsi-callback0 (>= 4), libglobus-gsi-cert-utils0 (>= 8), libglobus-gsi-credential1 (>= 6), libglobus-gsi-openssl-error0 (>= 2), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-proxy-ssl1 (>= 4), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 9), libglobus-gssapi-error2 (>= 4), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 11), libglobus-openssl-module0 (>= 3), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 5), libgsoap7, libgssapi-krb5-2 (>= 1.6.dfsg.2), libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.13~alpha1+dfsg), libkrb5support0 (>= 1.7dfsg~beta2), libldap-2.4-2 (>= 2.4.7), libltdl7 (>= 2.4.2), libpcre3, libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 5.2), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), libvomsapi1v5, libx11-6, zlib1g (>= 1:1.1.4) Recommends: dmtcp, ecryptfs-utils Suggests: docker, coop-computing-tools Breaks: condor (<< 8.0.5~) Replaces: condor (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: science Filename: pool/main/c/condor/htcondor_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 3748342 SHA256: 8e4098ab6e8eb344486d7a9ca83bc0a7a0b92565d36a9d30e7ba05ff47571118 SHA1: 884f30aec5f5d24e7277b882ba52d818c019d370 MD5sum: bb79746da7b684acfa782a56e98f1dda Description: distributed workload management system Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor 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, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor 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 HTCondor pool or as a "Personal" (single machine) HTCondor pool. Package: htcondor-dbg Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 34417 Depends: neurodebian-popularity-contest, htcondor (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1) Breaks: condor-dbg (<< 8.0.5~) Replaces: condor-dbg (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: debug Filename: pool/main/c/condor/htcondor-dbg_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 32797050 SHA256: a65819828f9f90356f3847c4de37d32c81ab447b43868493a97c4fa390246fdc SHA1: c8983423732497623a33a83167ffc637046c3a8a MD5sum: ef75c944560eb1118a20f5a54b31ac43 Description: distributed workload management system - debugging symbols Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor 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, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for HTCondor. Package: htcondor-dev Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1403 Depends: neurodebian-popularity-contest Breaks: condor-dev (<< 8.0.5~) Replaces: condor-dev (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/htcondor-dev_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 324850 SHA256: 2e9121fbdfb8ce3dc9996e7b3b7aad988f00cc776bea378983738df1d173288c SHA1: 9bcdc3c99e98ab2c4338dbf9cc633beaab4c4fcd MD5sum: 6b07c8f50505181b3b05073bf00fa4a4 Description: distributed workload management system - development files Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor 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, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of HTCondor add-ons. Package: htcondor-doc Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6028 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 1064326 SHA256: 89ecfcfb0bccc5ca4ad19fba4b3c84087f4054b9cee40d88ca16dafd992459ee SHA1: 0b354dfa51fd2ad34160d005eca34a38ea5264f2 MD5sum: 1473b4fe1f7412efebd325a5822e6093 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor 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, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.11.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 436 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil | python-imaging, poppler-utils | mupdf-tools | xpdf-utils (>= 3.02-2) Recommends: mplayer, pdftk, perl, xdg-utils 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_0.11.1-1~nd15.10+1_all.deb Size: 175612 SHA256: 85edf5251e3ca7fe619122697298346cbc81189c385325c1040321e1541cbe90 SHA1: d842248cbfecbfb42164fbe71368bbe42ca1ee08 MD5sum: 72a27ab94bb28731dd2606d51a7425f9 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 * Support of movies presentation * Active hyperlinks within PDFs Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd15.10+1_all.deb Size: 5020 SHA256: 1563317403e6ea4aafcfde81fbe117b6dfac65716db2be3a595efaaead95b6cd SHA1: 02f380f8792758da55e050c656e7373602983023 MD5sum: 929d61c356c458f97fb2dfa6014e68d0 Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1), libboost-program-options1.58.0, libc6 (>= 2.4), libfftw3-single3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd15.10+1_i386.deb Size: 127106 SHA256: e7f5513b1044bef94c318ab486eb2c865bd12dc2fdadcc42d851385247b52975 SHA1: 215a43054b2b362ef5159c0093e22add8accb9fc MD5sum: bac7bffee897b86ef1ec4d9d9a888427 Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1407 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 321234 SHA256: 52d831774169b9c59d7ffc9fe9745045bcb6215c06030b943617aed11c6088cf SHA1: 0d2e10eb71e890318d137eaa5a257333b72eb5ac MD5sum: a1c756071599a64c0759adc635c3db31 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: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 862 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_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 287814 SHA256: bfaebb165bff7880844447be3873ef7c540a78fcf018afe567c6a9935b48f200 SHA1: 2d0c36e9706aab36b0d4070e659005c70e63e23a MD5sum: 5cf7c7f412792bdb68e2508bffea5399 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: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 70346 SHA256: 107fee1f0a5412cc51e7ea08542acde57e10e58f93e85c9fa8af040d1443989f SHA1: c78102fef930f7bc697b3c41daef8c24b626cbea MD5sum: b9df9a871f9fc267216f7ac01061f3d3 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: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1156 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 244594 SHA256: 555f6af61419dcf009e53bdecad4945813b7e7bf5caf5389796dd89079494c83 SHA1: 5cc725c898abc86e68284ab563bc62adf52c60f5 MD5sum: 8b8eddad34b8e94b55df9ec05d506018 Description: HTCondor classads expression language - development library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor 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: libclassad7 Source: condor Version: 8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 596 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpcre3, libstdc++6 (>= 5.2) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.0~dfsg.1-1~nd15.04+1+nd15.10+1_i386.deb Size: 202982 SHA256: 4d117f313c0fbe00e4ef39c596774d476dac51598ebe617ee1efb8c6e97947ea SHA1: 5c067c5d330331e52ec27f4f6b4689a4e1c92476 MD5sum: 48f89557359aba952219e4a50469a85c Description: HTCondor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of HTCondor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the HTCondor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libcnrun2 Source: cnrun Version: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 5.2), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.0.3-1~nd15.10+1_i386.deb Size: 79606 SHA256: f608d061c9fc7c42c16432c08f3008bdf20e17934acc63731d656ef4211f5fa2 SHA1: bba9e55ecceba0c7963b7e74e6292720b3e35bcb MD5sum: 03f8912bfbf86985a2ca938f83a1eefb Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.3-1~nd15.10+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.3-1~nd15.10+1_i386.deb Size: 21236 SHA256: c7068c5952150ed24a23ebdb784fdb97188c6b2f387c858f08f0424f75b5cff1 SHA1: 97bd5de34156868d88d955777376fd7490cf76c2 MD5sum: a996c8bc22d42238efafa2c09ca502e6 Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6522 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libfreeipmi16 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 897828 SHA256: e0dfe6680106a49669bde643d143734a3057b859f1463317197b1be83abbe45b SHA1: 8b7db93ee31cda32094aa7e8b7531e01f5be35eb MD5sum: 436e385144c763272dd3c5badf867b71 Description: GNU IPMI - development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libfreeipmi. Package: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4219 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt20 (>= 1.6.1), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 743950 SHA256: 09f548e48661d014dfd2264d6f6023781fa95b93cc42e39c94c7e604d86da89f SHA1: a88f16f9bb1682b0258e2809fbe67ff458477479 MD5sum: 6ca2c213d9682160ad9cb6adb0a54291 Description: GNU IPMI - libraries FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . OpenIPMI, KCS, SMIC, SSIF, LAN drivers, and an IPMI API in a C Library. Package: libfreenect-bin Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 219 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.5 (>= 1:0.5.2), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 5.2) Breaks: libfreenect-demos (<< 1:0.1.2+dfsg-1) Replaces: libfreenect-demos (<< 1:0.1.2+dfsg-1) Homepage: http://openkinect.org/ Priority: extra Section: utils Filename: pool/main/libf/libfreenect/libfreenect-bin_0.5.3-1~nd15.10+1_i386.deb Size: 54774 SHA256: f24a854698a1eb13465b0deb49af413462262354851ad8435bbb97954f3b872c SHA1: 13a9eeda5404a9f25d3e4750a343b699b956e809 MD5sum: 56e16fffbcb59ea634e75a78ade1c80c Description: library for accessing Kinect device -- utilities and samples libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package includes utilities and sample programs for kinect. Package: libfreenect-demos Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.5.3-1~nd15.10+1_i386.deb Size: 8662 SHA256: 9c7aa7a4a1a9f740f7200b75e868cab23b7835bafe870356d97689900a36ae6a SHA1: 363a1bc02f08c8905e2af6292314d107dda03437 MD5sum: a0e809607693081bc13daded68598d67 Description: library for accessing Kinect device -- dummy package libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package is a metapackage to do the transition from libfreenect-demos to libfreenect-bin. This package can be removed after installation. Package: libfreenect-dev Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.3-1~nd15.10+1), libusb-1.0-0-dev (>= 1.0.18~) Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.5.3-1~nd15.10+1_i386.deb Size: 19426 SHA256: 9fbba71e92f95124ffed3820e25ec2dd20c41d3dd3770479f63596c7761a4d9e SHA1: f5d4ee3aca112d9957a4f58499744926d8986e4c MD5sum: 29043653576c1d320643884f1adb4dc4 Description: library for accessing Kinect device -- development files libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 829 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.3-1~nd15.10+1_all.deb Size: 133898 SHA256: f48d3817a02c25b6076eb52fcc7a5abbdf90b9f7278992a7cc5a7c9dcece67ea SHA1: ee48acb9c6070a8eaae4884cc160b3e584114879 MD5sum: e3a1bc6631d8f8785711280c567cd197 Description: library for accessing Kinect device -- documentation libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the documentation of the API of libfreenect. Package: libfreenect0.5 Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 134 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.12) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.5_0.5.3-1~nd15.10+1_i386.deb Size: 45446 SHA256: 392a2a04287d14be4a71e56946bdd4e121ff1b7853d5f55d4ea4034a62cf2939 SHA1: c0e4a80f69abc5c35657726c01fabd0ebfe73cf7 MD5sum: aa6e06962f2daedf2d334fcb4a756808 Description: library for accessing Kinect device libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the shared library of libfreenect. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 447 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmiconsole2 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 104830 SHA256: 059a7a3dbc09b009f0241b4e7f724ea0dc6f29ae82665cb04a7afe90c9f57783 SHA1: 8be8ec933a59c68ab8373313b5b73e593a85f784 MD5sum: 2f615ac4a9ba48c457949d029df66480 Description: GNU IPMI - ipmiconsole development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmiconsole. Package: libipmiconsole2 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 317 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 87622 SHA256: 28c55c2d3eb47e723321259f0df988f65390b42fc580b54f3f44b114b88287df SHA1: 631d624e75290b44a5f6cf36b863ebc743b4eda9 MD5sum: 00b15491158816a52593f94370e457d7 Description: GNU IPMI - Serial-over-Lan library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for Serial-over-Lan (SOL). Package: libipmidetect-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 110 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmidetect0 (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 33310 SHA256: 24cea7db4549e899a0c0942677d5ce5aa022c0403b8514423732d7b22710c6ca SHA1: 5802d519f354c0da83269caff7b062ccefbadb92 MD5sum: e3f5f61da5b684441077b4df9297265b Description: GNU IPMI - ipmidetect development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmidetect. Package: libipmidetect0 Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 26976 SHA256: 1302ef2920103d6624889ea6ab8799141e74de9c0730154d4737b42523bed4e2 SHA1: 80600c88a4f52c0ad5be86e3131cd4ab8436bfca MD5sum: 24ff2e3464b5ace6f253f368b4739cdb Description: GNU IPMI - IPMI node detection library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for IPMI node detection. Package: libipmimonitoring-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 297 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1), libipmimonitoring5a (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 63350 SHA256: 6b441527e1f107f0dc7b255ba16cab519989486a4f4d197476e6f0854993cb05 SHA1: 443c2b2cc0e6c80d9aee3f77161ce4d99135d33f MD5sum: df1ff3af53d928b585b0ca9a7cd53397 Description: GNU IPMI - ipmimonitoring development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmimonitoring. Package: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1+nd15.10+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd15.04+1+nd15.10+1_i386.deb Size: 45378 SHA256: ff33ba44eed55089b8b2baded6b04e70a126f564a22eb0e3ed3aee76dd4d3831 SHA1: e027d9e00b482d9a65d036ecdda6a2ad9519c6ee MD5sum: dd35b7a8c9e1db3aed21924fda1f5400 Description: GNU IPMI - Sensor monitoring library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for sensor monitoring. Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd15.10+1_i386.deb Size: 13796 SHA256: fff7b3c5892723e20ccb1836eaff3535b41273a858732ddbf214529be826d9f6 SHA1: da284bb70a5928a31a351f811beced24fb480b49 MD5sum: 777d5524e0be6e99165aa7e098c17baf Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1987 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd15.10+1_all.deb Size: 158280 SHA256: e2638885c6f67fa4fe3805ce145d47836afe4837cb23cfe9160feab83b270744 SHA1: b7d385208ffa71c26321c7b8c6d5b0d47c9df36b MD5sum: 3d81a093867c814aba2efe0714148ee7 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 349 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libhdf5-10, libpugixml1v5, libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd15.10+1_i386.deb Size: 84760 SHA256: 38cff1d9b5232a48c64a51880d5f61e681019449d78f180162169b6322fb0da2 SHA1: f53e533cbda2d6bcb9f14128f26df8d56cc22953 MD5sum: 9626c0c966f3756cfaccfb9f93957fca Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd15.04+1+nd15.10+1_i386.deb Size: 73610 SHA256: ad6448a718be80be0184563ca2f0b8dba7b5819863ec08929e682ed49143a87f SHA1: 966856ff809e2ea214cd50d322f8136584c2711b MD5sum: 6e9fe1818c19e1d032cbc86d0d3f6b4e Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1450 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.4, libstdc++6 (>= 5.2), libvtk5.10, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd15.04+1+nd15.10+1_i386.deb Size: 434042 SHA256: 08243dd91fce8a2c380c427e782f1e37db6e8d4852522b6ffc97140701cafc1d SHA1: ca4f758f23041c13bf72c9565c6cd5428da738e0 MD5sum: f70d9797d08e746cbc3037894d65bcbb Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 565 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd15.04+1+nd15.10+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd15.04+1+nd15.10+1_i386.deb Size: 80842 SHA256: 28c06815bad594661b326a96ae3fa120d82aa7e15b68de93c8678b2ec5437aae SHA1: 6507b903f8b7fcc27f5074d29e83cc75e3e6f9b2 MD5sum: 9b91b22e2b6775c96bbf5b38773f1600 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.0.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 107 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.0.3-1~nd15.10+1_i386.deb Size: 37922 SHA256: df1bf4f83434b67f5401e4cbdbaecace920c93e8b6880fcba0a3948a4478ec2c SHA1: 450a3d25fc1d8fee01bbba379a82526e9fb15d72 MD5sum: 72cabae6093992c11e50485569738467 Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: matlab-support-dev Source: matlab-support Version: 0.0.21~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 17 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.21~nd15.04+1+nd15.10+1_all.deb Size: 7574 SHA256: c4ba8aa092fdd78ee931578a1ef13d097c0f11b0c0a26d1bd721c8bc26fc0b0b SHA1: 408915ff3fdbdc3379b8b317e606bb3902b1b167 MD5sum: 7afdad825ab8ac1b1baf462865536314 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mriconvert Version: 1:2.0.8-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5323 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.2+dfsg), libwxgtk3.0-0v5 (>= 3.0.2+dfsg) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.8-1~nd15.04+1+nd15.10+1_i386.deb Size: 826056 SHA256: 2e592861d495785f5952dc9e9e72fa60c668e7610a4c1b738540953a18cc8c46 SHA1: 27060ebb5ea78e000711f6347aa41da0995bbd47 MD5sum: 5b61b8392d6afaa36412ee9ff1c6b185 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: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 12753 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Recommends: pigz Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 2108170 SHA256: b5497bd299d760b6180d7420be1b849df585aa685569250c931ca0961ef19e58 SHA1: 421aee912182cad14d1f46875104d4b1a2b0c869 MD5sum: b68378404c78134da66e040cecf3a532 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: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1694 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 1658508 SHA256: 8135e0e979a53f598e15999779129c5891566fca7691dc51878804e594eb6309 SHA1: 4c8d7ec1a93894e61be7c6723235c31bf027e187 MD5sum: 1a2dfd5641a5429fcdda4af3ff4fcfac 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: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1022 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 577428 SHA256: 4d9c8d3ec4d9446b555e7f2949108061bdc1827a1c77928cc1c3d260e53e35bd SHA1: 60ec2b395eb76953884e28d6fb1c4b0d43ae5183 MD5sum: 570e54c34d0bc3a576c4fb8117711d70 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: mridefacer Version: 0.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: neurodebian-popularity-contest, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.1-1~nd15.04+1+nd15.10+1_all.deb Size: 637094 SHA256: 85c3220393ef2dc9eeb6d7777bc4e63f769e6833080cdb6b91f2a964ab1cdd5d SHA1: c56285b2c25d28a511bbf07c3afe08a0b9e0ff34 MD5sum: f31372a79b07849a37ab4489d5152b46 Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: netselect Version: 0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 62 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~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 30936 SHA256: d41285938985ba643ea4da2d2749ea9480fef3f04a1715487ca537ac53b6e9ac SHA1: 1daf7de93404dabb09ff51d6a7d02c4d9a814b3c MD5sum: 109c0acf1202fb7d8b33a9edd47272d1 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~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 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~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 16878 SHA256: 17eaf7e30e8d133bfc96ce4836eaa927a14b1d52f9e245f20c56d9243260a1cb SHA1: 7ad6cc055aa912d0eb77b5084d8369855d5523cb MD5sum: 2cdbfd381825e0b50128b3f0a06f36b0 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: 0.37.2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 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_0.37.2~nd15.04+1+nd15.10+1_all.deb Size: 31440 SHA256: 366bf925bf7665dbd51ac5d5da8d0e2816a8496f1648b84bdb73ebbe83946337 SHA1: d5fcf278de28a9f225f1602babdc3850f998e05d MD5sum: 60617093af2b542688377f7a3e1f64a4 Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 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_0.37.2~nd15.04+1+nd15.10+1_all.deb Size: 10048 SHA256: 10f9574e7c5598a91e2a61dd16ea284a67113843b826c9cb3d471ccbc42b4a7d SHA1: 572aa509e98107e69b7f8ba662198dca296894de MD5sum: 5497fdb02f4146d791a6703e7e592cf3 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 188 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.2~nd15.04+1+nd15.10+1_all.deb Size: 115820 SHA256: 1ee995999404a04946f0e559c492be65bcc1cec8fb1381b5e8d6cf0401e15416 SHA1: 5e8b092c083e7eda85c6b26522326fe0271acff7 MD5sum: bb24d5d863f79aa46a7bcb6a8a806587 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.2~nd15.04+1+nd15.10+1_all.deb Size: 32288 SHA256: 0f137d16b41f8a5964d4cd06808ab20ccfb690b362e19b0029bd2d7f9af55dc4 SHA1: e227d9794c3938132b7635cfdf4a0ea4474fcee8 MD5sum: 333a7fd85f5626169ecdc5d306e630ca Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.2~nd15.04+1+nd15.10+1_all.deb Size: 12062 SHA256: 12e0d443b42570b12a3a8a213eb80e3d3fc3987d101b1a460d291e524b19f632 SHA1: f9ea3401af5b71b84aae9a7eb2cbc306b9da540c MD5sum: b7e8eaea234b948b4f5318a0c60e3e5b Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . 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 (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.5.17+ds-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2823 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:any (>= 2.6.6-7~) 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_0.5.17+ds-1~nd15.10+1_all.deb Size: 597464 SHA256: 7e7d23ba05e8ac28aec65fff34ebb11c0a5543f002ac64cd4d2718e147751f59 SHA1: 5d6eff5e3e6c4ffa243c9ff98df07adf6b888719 MD5sum: 1495075352652cbaef38cd635475a45c 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: octave-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 81 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liboctave3 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 20442 SHA256: 4feba21e4dc6ee020d9007774be06730934efa95e60d4bada459cd1cc5c2326d SHA1: 41233bc97cfe9f21250241d9e5182e0a75d35b79 MD5sum: b06a547a241e0a724ed1e25a184e22fd 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: psychopy Version: 1.82.02.dfsg-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14917 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.82.02.dfsg-1~nd15.04+1+nd15.10+1_all.deb Size: 5997786 SHA256: 175bb4f71899c0f2590c5b4655da2f205a8aa4417f33cbb4a81561d675ff3756 SHA1: d8da90c091f0b183d6fd90f47b25b8230a642c57 MD5sum: 879b2dcd751fdda21d5a079cf6e511b6 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: python-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 228 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.4), libcholmod2.1.2, 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_1.4.1-2~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 44478 SHA256: 4fb44cd5802b5ec13a6cd84fd5a7f708741f742a90fe2133007ed1e8abb52407 SHA1: 966f5028beda79ce49980e94a18293140d87e86f MD5sum: 87ce5c4abeb6d7d3f18e4cbe9da333da 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-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 769 Depends: neurodebian-popularity-contest, python-lxml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python-citeproc_0.3.0-1~nd15.04+1+nd15.10+1_all.deb Size: 80446 SHA256: 53b97c0bcbd0e47ec9774a2a9c7948e7f7e6bdd0df9b4cfde61a69f0bee41293 SHA1: 2b9b89bfacadfab9db387c56b59d0a812495fa76 MD5sum: b04a87a0a44d909fbb49ed03106c9c22 Description: Citation Style Language (CSL) processor for Python Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python modules. Package: python-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python-contextlib2_0.4.0-3~nd15.10+1_all.deb Size: 8670 SHA256: c074f20a0bd51ed6eff89cbf6eecdd6517945fb4a709028e576a5e3a147db14a SHA1: 9124d93433c0907b1bd8082bc389f201a30bf631 MD5sum: b498d2525417efaa8d645bdaede4590d Description: Backport and enhancements for the contextlib module - Python 2.7 contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 2.7 module. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 502 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd15.04+1+nd15.10+1_all.deb Size: 78672 SHA256: 3dd0a721cb37499d77ea79aa6e90f76f25f033c06f52ce14e1e17202869af2b7 SHA1: b09765500ff57e38cd3624b02fe6cd9b7d25c441 MD5sum: 7cdebfec320f98b77e6d00bc110e9efd Description: DICOM to Nifti conversion DICOM to Nifti conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a Nifti header extension or written out as a JSON formatted text file. . This package provides the Python package, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dicom Source: pydicom Version: 0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1577 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://pydicom.org/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 359402 SHA256: a903e4b3b558d463a4807396a61dd2e71a4a9f204e9bfd56ebd21976ef56ae1d SHA1: f2eee4b06269a67d248f2bec75022de23ba9d608 MD5sum: 37c3a5938f94239a63f9d775ddac2247 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: 0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4763 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-dipy-lib (>= 0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+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_0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 2338700 SHA256: 00f63502e566d8075ecdef4263fc8da0a3aa119a7e6f751495dc197163b1620f SHA1: 31332e7b928994d2b85409770a97e664785bdecd MD5sum: 26f8731e84174a130ca771157aaad1f6 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: 0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12612 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_0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 10234876 SHA256: 01a1dcdc5a72978b81c1e5de3d7bd1a244e9fcea418d2080e250bfc7dd374297 SHA1: 89adf18c6d9659f650961d43ed34f0bdf24b6796 MD5sum: efeefb286453166b21e38b869243ca93 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: 0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5568 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.9.2-1~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 898068 SHA256: 1305e0ee9ea2b097d755602b08d3b95631555671e04634b3b219dfbd2a05d593 SHA1: ef4ea838c38595be4704ee31ef66534a62ce0e5f MD5sum: f1287b6d6c86f7b22ac1c4488c81e393 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-duecredit Source: duecredit Version: 0.4.5.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 223 Depends: neurodebian-popularity-contest, python-citeproc, python-requests, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python-duecredit_0.4.5.3-1~nd15.10+1_all.deb Size: 46558 SHA256: d02b5be07179e77f1bb295412b5434c9e68aa83a7302dc9d4c9ab59db3e4f0d4 SHA1: aff413361b1eec83654fec21af746457bcc3b4e6 MD5sum: 2cb062ab12a75f64b64f7a4812fb0631 Description: Publications (and donations) tracer - Python 2.X duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2571 Depends: neurodebian-popularity-contest, python (>= 2.7), 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 698814 SHA256: 6652ba241c1aa160d58862a8b30b7c463e89b24ecc86de70e2069606aae1292a SHA1: a0369e3800708c5369ec11a0cf8612d68c3a02cd MD5sum: 7fbb095c97ab3ed7df202c7ef2a552e2 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-freenect Source: libfreenect Version: 1:0.5.3-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.3-1~nd15.10+1) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.3-1~nd15.10+1_i386.deb Size: 44760 SHA256: 5d9cdca3186e3bc7d252740f81557ec24dad0f108a65e1c489c115c3ccfdaeae SHA1: 62a975f98fefc70fbbdc54186510bc59e4d7b358 MD5sum: 15d8653484a8185ae8b978cb2c1827a7 Description: library for accessing Kinect device -- Python bindings libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-git Version: 1.0.1+git137-gc8b8379-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1584 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-gitdb (>= 0.6.4), git (>= 1:1.7) | git-core (>= 1:1.5.3.7), libjs-jquery Suggests: python-smmap Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_1.0.1+git137-gc8b8379-1~nd15.04+1+nd15.10+1_all.deb Size: 306612 SHA256: 79f2bd9131ea2b5ebb97644e6685663327f6b00082c314bddefc804c76f8c10b SHA1: 5debd6faa3b6e7ee1bc90d0bc40fc26805b34238 MD5sum: f5ab597981c5e95b9fdb7d9d19610081 Description: Python library to interact with Git repositories python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. Python-Version: 2.7 Package: python-gitdb Version: 0.6.4-1~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 230 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_0.6.4-1~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 55032 SHA256: e4601fa4b91a6e68f25a9bbedb196ab30d4ebc2880a4ac191531ac4077b9a407 SHA1: 41e68e8772b462c4290ccb7721e4f14d9d7a6d45 MD5sum: cf0ce33ac9a6826d541443094b2df13a Description: pure-Python git object database The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. Package: python-humanize Version: 0.5.1-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 77 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python-humanize_0.5.1-2~nd15.10+1_all.deb Size: 12946 SHA256: 3d7c717bb267130a36d6808ac4bdbe8833f1f74d8bc53d3b0be052b166d46606 SHA1: 9ad504d41c2b45ba4fedaf3fd00b04bef659b55a MD5sum: 6dd73938eea0d270b0f932b91bf0d7e8 Description: Python Humanize library (Python 2) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 2 version of the package. Package: python-joblib Source: joblib Version: 0.9.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 346 Depends: neurodebian-popularity-contest, python (>= 2.7), 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_0.9.3-1~nd15.10+1_all.deb Size: 77868 SHA256: af2356d29165b2ef2ae4f22b241b3eeb98cd30555000d53583a2f013cf7341f0 SHA1: 2999c307d98bfee18f2a4086d9c2afbe9dd269d9 MD5sum: 745a0a6e818c5a26a60ef35dc822c27f 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-lda Source: lda Version: 1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1320 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 239152 SHA256: 4e6466766cea76e8f0d4a1b7eb00289fafca51b6e204b009769218b04a9b49ef SHA1: f1a2f8fb690558c74c7e6d47494dc71b519d63a5 MD5sum: f910f423b3d2a63049a037864e6f4656 Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-mne Version: 0.11+dfsg-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9055 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui 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_0.11+dfsg-1~nd15.10+1_all.deb Size: 4360590 SHA256: 85cc03601dc54db8d177bc33da6391c705ef789c2bb2e0e57bedbf4f8889bb5d SHA1: fbc337208bcad1022d3456a8e38f47ab0356e62f MD5sum: 6b69950039f58d849f5722f60e7dbb0a 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-mvpa2 Source: pymvpa2 Version: 2.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8322 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.4.1-1~nd15.10+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, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib 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_2.4.1-1~nd15.10+1_all.deb Size: 5052862 SHA256: 45c1cdfd4cb15eddd133574350881a6d9feb7985b5b248d09a37d3df5a1666e6 SHA1: 0524a73346ea04e552f865a848d14a96fc991444 MD5sum: f44205751bd52c4375074f4cbb81271d 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: 2.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32037 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_2.4.1-1~nd15.10+1_all.deb Size: 4751888 SHA256: 2224b9973756f2d4e767bdf153f81e46e334113e8da676d7b7d0955f69e16abc SHA1: 4c6ead76b54bffd8be3452a585472eb79f0b40a2 MD5sum: d19f0028ebda653ccb4a27d21f8ae287 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: 2.4.1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 130 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 (>= 1:1.8.0), 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_2.4.1-1~nd15.10+1_i386.deb Size: 48028 SHA256: 658e9a2f562b929ea7d43bc006007256262ea34b0067aa22c0569b2402133bc8 SHA1: 14b870bdf14ca09c244a0e21d2c841fdcf5ebdb3 MD5sum: c7126ad90e4b6e548a068a9dec4d0787 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-nibabel Source: nibabel Version: 2.0.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63342 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.0.2-1~nd15.10+1_all.deb Size: 1962818 SHA256: b8a2e973124b9d0084fd556b591744e2e2373c8d8dc115282b06796021fff1b5 SHA1: ca253caee5abab17e2c2bfb4d956dcf530d05743 MD5sum: 241da9cbb3fc4f477f1db434d17d64da 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 Package: python-nibabel-doc Source: nibabel Version: 2.0.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5617 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_2.0.2-1~nd15.10+1_all.deb Size: 2683940 SHA256: 2249de86f2931b631545f7fbaabe666ca15e23369e04343cd99b29a53bd33e92 SHA1: 70eaeaccf2b4b3eb09795fe51da7b6b9d72faabd MD5sum: f9dbdd8937cf114f4d00c3ba4e112dd7 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-nilearn Source: nilearn Version: 0.1.4+git3-g60d2a1b~dfsg.1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1841 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6), python-nibabel (>= 1.1.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-scipy (>= 0.9), python-sklearn (>= 0.12.1) Recommends: python-matplotlib Provides: python2.7-nilearn Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python-nilearn_0.1.4+git3-g60d2a1b~dfsg.1-1~nd15.04+1+nd15.10+1_all.deb Size: 635570 SHA256: 2f0993d7d926bfa7fed57df08d21000fc7ff3bed35bc618840e14b04a04f4f8c SHA1: a2f3f69e08f74506f31fed6816c0d74f353e410b MD5sum: c0c6ccd950ea92fceb8fbb5a37964708 Description: fast and easy statistical learning on neuroimaging data This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3184 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 723658 SHA256: 92df239b9abd7bb290b28bb5c63f529239e31a8b8db2b2a2d1bd4d882b45aa03 SHA1: 4531747ba8ee381e0d3e1c6b6e0b4afff84e5e85 MD5sum: 9b7b13232caf055b73914495c5fac0aa Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10888 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 3117598 SHA256: e4a164f8c749f224a3229e5099c725c2e882283d2bcea26dda45303ffdb313c3 SHA1: b9261918d254fd68b050178b83d639da2309ca42 MD5sum: 0b4a548ffc499db63c77f0883b400579 Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2728 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 572738 SHA256: dba9480bb35a3c4281a67720af6d318aa1d06aa315b5788333b33391759f0cc8 SHA1: b668ebc674de12a5a080f6d44f59c94f24a780a3 MD5sum: 4e9146282feb895ec01ab01de06420ed Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3172 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 451446 SHA256: acb566e970b82daf4f79b6727074e8dd15f916c1f69fd3a1e6b167ec230ac296 SHA1: e89a0ca60f6456b0ed9c5e68627a6f113adcb535 MD5sum: 76161face4688bf6acfb2e05b43cac6c Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipype Source: nipype Version: 0.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8454 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), 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, python-xvfbwrapper, mayavi2 Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 1420158 SHA256: 0fd545b3427945dc7839ec01306a5ae9e3b70c82eb6cc4f37a75000c4aea46f1 SHA1: 782bcf359a296737d6f9be924ae3175012530d13 MD5sum: c0507e321514629faf892f85d10c03f8 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: 0.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23460 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 8916428 SHA256: 3489524c3e0479ec4f912e3ce85e85d781a858454c95a5f4d8c33ecef1893741 SHA1: a5c883b21262b7657c78ca5478787e48304505a6 MD5sum: a10f5e7314b95618b0a4c85382a614de 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-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 455 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 124018 SHA256: f3fcdc4dcba561bddd95cefc05975084cb0cfc3d8a5785eb859b0530fb97c529 SHA1: 5a8996de257a438c3db07d675d0a5c9ff31b2a57 MD5sum: 3d484be97b6e7944ba3eaf2091820e9f Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numexpr (= 2.4.3-1~nd15.04+1+nd15.10+1), python-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 94232 SHA256: d1f838f2350cb5a0f64889c0d682fb680cbe23de1144d1c40b035d817bdc4b76 SHA1: 7bd10c62997795205b70de88ea485a64ff70bb8d MD5sum: e928442db4ff92dc380e95c20ad2559e Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-pandas Source: pandas Version: 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 19860 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1), python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1_all.deb Size: 2346206 SHA256: e7c25f4f65878c01a3ba24850dcf8d7e6f662714a0987f3e373b08c9316d94c1 SHA1: fb8722db3a6dca2b433204ce634406f9f7679fe3 MD5sum: aac4f5a725c7a0e648a5139b64a16996 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-doc Source: pandas Version: 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 51103 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1_all.deb Size: 10947220 SHA256: 43f2178aafb7ef6d0508eac8a4d50e228c6a0f757da3660f59ab753a97ac5be6 SHA1: 922a505f9a8649575349d549ade1d85a9190274d MD5sum: 0087f4f3a5c93ca1b4a8efc3905682f7 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.17.1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6446 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), 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_0.17.1-1~nd15.10+1_i386.deb Size: 1534168 SHA256: 11df5576309a4347ab941f1c300931e15cfef0c29ea97a7e9142a9fed0ce6ff5 SHA1: 692fbc0a8ec63b80f52d7959341f7a681a7230dc MD5sum: 49015b3c549c539cc44d12c0edc96b9d 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 783 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-six, 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_0.4.1-1~nd15.10+1_all.deb Size: 171530 SHA256: a138d37607bd61b94c05562c2d744774ffa999352c95691b8ce62b2cf634b8a2 SHA1: 73f22404099531ad93c877a47f2aa300e084408c MD5sum: 5b604eb576a5aa546771d5c12481cd8b 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1374 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_0.4.1-1~nd15.10+1_all.deb Size: 358758 SHA256: f36a39459d9124d8b720d8cfef0d823df23253669f24e419b44a04764be872b5 SHA1: 4c359188f6cbd2bde22fa7500ffd05627559f6ec MD5sum: b2913de0d784a00801ac9f4a8695f524 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 758 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~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 82530 SHA256: d92ec2025469219732229d52024021a91ed1be44b4d3a0c968ee39adb4506714 SHA1: cf2cf43bae1aa11ba91b4558b50a3e046aafe00c MD5sum: 7339ae7d62fb0b93e77bfd92362e30a3 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-py Version: 1.4.30-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.30-1~nd15.04+1+nd15.10+1_all.deb Size: 66700 SHA256: 8ca1f393f248519edd0f52de3694de8e511238d2032c6dc0fe1242261908ebf9 SHA1: 7cb7aea10bd5fb3db2aec1ac0d89804294b53809 MD5sum: cfdcd004d5ef98a38394886c5236de3b Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1416 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 5.2) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 277152 SHA256: 05119be8089703a2a7280cdc5063a511bb5a15f22af7835bba9168e9b378f48d SHA1: bb4c84b972591f4f8fcadfecc09dc533b5c846d3 MD5sum: a7710e8a405ff3138656d1ed8545da9b Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 822 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 819464 SHA256: 8c17d1434c8e1da5e583f98d1a6cd3f9861767295c63a8f97dd1c7cb9ef33efa SHA1: 19d1be20a9ac8c71cb8ff3383a695e9f56f75db4 MD5sum: 45bc27c8ee6f2a8e368cce8ed3fb6f8b 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-pymc Source: pymc Version: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2668 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.11), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, python-scipy, python-matplotlib, python-nose Recommends: python-tables Suggests: python-pydot, ipython Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: python Filename: pool/main/p/pymc/python-pymc_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 527858 SHA256: eb622e1174beb55874203fce2ef81473fa31256edf7d7f80b698c1c30915f8c1 SHA1: 3c0afd5be786eefda36c121e7c1d5c2d43927303 MD5sum: e23a044de37f188e79aa28cf68d90fc6 Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. Package: python-pymc-doc Source: pymc Version: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1894 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: doc Filename: pool/main/p/pymc/python-pymc-doc_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 839798 SHA256: d3aaaba642f681a3628813694c80f363c2d5227e847276d89b5b73aa6523ce59 SHA1: ce8e7a60b397a3afb6fa64bd4a348944415c646e MD5sum: 36d84dc5b94e1bce656a0a626657afa2 Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. . This package provides the documentation in HTML format. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 818 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 122702 SHA256: 907de30bc8e14386b8c39219e5b930c49fc5085c48ba1de63defc033de919dd0 SHA1: 2349a0f46e32d4b1fa4700085e6ed4860d1dd2ad MD5sum: b84b793301926a44fe0ad806f70a95e8 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-pytest Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 464 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-mock (>= 1.0.1) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python-pytest_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 102354 SHA256: 2cbc118fdf6a5b9ab7322c2b80519598fff9f8fcb0db2e36193067fa0c133ac2 SHA1: 2cc0c7470f6d1bc7274e365c8630ee7fe46fe644 MD5sum: 56aa0c33033979d21e014df680763597 Description: Simple, powerful testing in Python This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. Package: python-pytest-doc Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2973 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-pytest | python3-pytest Homepage: http://pytest.org/ Priority: optional Section: doc Filename: pool/main/p/pytest/python-pytest-doc_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 403654 SHA256: 6dfdf797382968cc3e3b30e7b20d0ec16e207433a315afb8038cd6772bdd333a SHA1: 9acaa57e48d5edc8d703fdec146d409ebb3cbd75 MD5sum: b5e67852cc706f273cbd4f3446a24658 Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 61 Depends: neurodebian-popularity-contest, python-pytest, python-werkzeug (>= 0.10), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python-pytest-localserver_0.3.4-2~nd15.04+1+nd15.10+1_all.deb Size: 19272 SHA256: 6fb68ebb08da4df6b381bb489a6a9cfd8014d46ae4026b34f4e84df9c819d4ca SHA1: 812f04249c0e18ed99efe15908d30b12f3774220 MD5sum: ab59e0d9c1c17c190d6046db0b63fe4c Description: py.test plugin to test server connections locally (Python 2) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 2. Package: python-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python-pytest, python-tornado, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python-pytest-tornado_0.4.4-1~nd15.04+1+nd15.10+1_all.deb Size: 5776 SHA256: dccd6e64154c95e64e7d74b12739a27460adbac7bc69a586c1936d002fb0f1d6 SHA1: 7fb37482492de05163754654ea174c32badc6900 MD5sum: 1e34a857279804ffc8ea8e9377cd5104 Description: py.test plugin to test Tornado applications pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 2 code. Package: python-scikits-learn Source: scikit-learn Version: 0.17.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65 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_0.17.0-3~nd15.10+1_all.deb Size: 55498 SHA256: 2877c7ee139290fd2dd3814237317078337061f1343376487c3d17aa24d954c6 SHA1: 57511c88f8dcbbb8cd7e09a153503fb253b6b880 MD5sum: 3138699b079400b09d793d2ba01d1c41 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-scrapy Version: 1.0.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 978 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python (>= 2.7), python (<< 2.8) Recommends: ipython, python-django, python-guppy, python-imaging, python-lxml, python-mysqldb, python-pygments Suggests: python-openssl Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.0-1~nd15.04+1+nd15.10+1_all.deb Size: 174766 SHA256: 6844760b2055b26919dd97a3603fe34a1df21bddfca37f17022da480a06a7b0f SHA1: bdd1f1bc3e52eaa797d6239c4e4389ad8b29c5d2 MD5sum: 0effc5a007e87c9c014a8a849a2e44fd Description: Python web scraping and crawling framework Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy script and modules. Package: python-scrapy-doc Source: python-scrapy Version: 1.0.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7111 Depends: neurodebian-popularity-contest Recommends: libjs-jquery, libjs-underscore Homepage: http://scrapy.org/ Priority: optional Section: doc Filename: pool/main/p/python-scrapy/python-scrapy-doc_1.0.0-1~nd15.04+1+nd15.10+1_all.deb Size: 1544070 SHA256: 449c81f478404a04e1fcd4998436a9b24f4a4332a1a608de6c88f61d65959339 SHA1: 56fbd87ac9732c395b8d74f1059795094708d4d7 MD5sum: 2bc9ef9a4399fea4be8c6747c857011b Description: Python web scraping and crawling framework documentation Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy documentation in HTML format. Package: python-seaborn Source: seaborn Version: 0.6.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 698 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-pandas, python-matplotlib Recommends: python-statsmodels, python-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python-seaborn_0.6.0-1~nd15.04+1+nd15.10+1_all.deb Size: 118144 SHA256: 8839b376a37e6339e17aaa2310c0b3e48df3483dd9901bf8341db52d28bd418e SHA1: 46d3946712ac9203c6a251546e0745fc9190864f MD5sum: 7b115de829b27f5e2f5741735a9f4477 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 2 version of the package. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1_all.deb Size: 11100 SHA256: ed8ef878a5acf90ddaca8ef5a9a823e37c018b6cdbaa188d317525382d85a317 SHA1: 7e1d6d6c8f09db6bb829bc8c1626a4cca0f927e6 MD5sum: 234ce848817dcb32bea848057a866628 Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 45 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1_all.deb Size: 11348 SHA256: 1710f5fa454425b0aa703d0ade438483d0bf57eeb1afe7d8997a70efe8cc5508 SHA1: b8f2871cb9c636494a38de1ef65cdeddb8531a47 MD5sum: 93f40a89beabde7e2ae3bda5db966f4c Description: Python 2 and 3 compatibility library (universal wheel) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six as a universal wheel. Package: python-sklearn Source: scikit-learn Version: 0.17.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5278 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.0-3~nd15.10+1), python-joblib (>= 0.9.2) 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_0.17.0-3~nd15.10+1_all.deb Size: 1221930 SHA256: 740f48ead99b2d4f1a87bf1c221c3adc2dca55b92ca7ad0b95f2b9aa87832f93 SHA1: c077d31d9f2b493bef59668424c485a69c4f0988 MD5sum: 957afd089f4144816888d9b1bf80de10 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: 0.17.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24664 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore 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_0.17.0-3~nd15.10+1_all.deb Size: 4061888 SHA256: 25746a617ce40d27b6e3b4522ee509fd04f7a321f41f912c66b1b7000c35ddac SHA1: 48b97ceb835641f1a5c41740b23ec596f32be502 MD5sum: 85830c872937adab980b39229e1dc5ac 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: 0.17.0-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5113 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) 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_0.17.0-3~nd15.10+1_i386.deb Size: 1086128 SHA256: a95d10b3adbec5d0f2f5511f0a2cd8917c293b79391e4289877cd486ed553b72 SHA1: 38f092227634dd191434706200d4e6cba6a57608 MD5sum: 7eee2b2ab4c6004c6d4de25932a7a566 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-smmap Version: 0.9.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 91 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-1~nd15.04+1+nd15.10+1_all.deb Size: 20024 SHA256: 8d44dd3de331e4c9d4c27749000ebe65a0ba5cb3f760896dcc8f52245400b1fd SHA1: 6397e9faff69002e65da42b1ae35b62a8ab636c5 MD5sum: 4a3bc19512ddd05c4c767f7b18474081 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 360 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python-sphinx-rtd-theme_0.1.8-1~nd15.04+1+nd15.10+1_all.deb Size: 117260 SHA256: b070fc77ec214ebeaa7f4fd98275a75bf81ae7d52efd8ea18df62e9aee4df17f SHA1: 613816e175a7cf7868edf04b76f55b92684316d9 MD5sum: c83aed789938169848a09c179ddfdd54 Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-spykeutils Source: spykeutils Version: 0.4.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2075 Depends: neurodebian-popularity-contest, python (>= 2.7), 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_0.4.2-1~nd15.10+1_all.deb Size: 309368 SHA256: 6b690d31eeae3c4a867d58ed574755e6a660c34a9d23ac65bbabd591cdd9b75a SHA1: 296cdb8e4f5791ebc495d023941a780095237738 MD5sum: f76f51f383a606e03e8836f100734217 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-stfio Source: stimfit Version: 0.14.11-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 902 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.4), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), 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_0.14.11-1~nd15.10+1_i386.deb Size: 313262 SHA256: 9aa324458a0b3ae0898779df67946b1636e9a42e4f666e2a81def06a01b22617 SHA1: 76ae0cea44db2f48bbb69d6051e2b949741411bc MD5sum: 294de07db5f92e7273c1523915a3c540 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: 0.6-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 192 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nibabel, python-numpy, python-scipy, python-pil | python-imaging, mayavi2, python-argparse Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.6-1~nd15.10+1_all.deb Size: 41648 SHA256: d9e0e9f82b01d42aaec80b8ce6fa375488d157dfc09ad2708664e15b70bd6b44 SHA1: 140d45cd9ae676ca9a844dec817c69634a3d5de9 MD5sum: 2773633610a43552825d0e747ad9c8cd 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-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 489 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd15.04+1+nd15.10+1_i386.deb Size: 86994 SHA256: 28d983057e0d3fa7ec7ae2a04816286ef3b960546dc015278207dd7bb3834cdb SHA1: f5b529940ee9d89b12c21a68ebe0afb0bcf16382 MD5sum: bd4c30a948c7f6d733252f0384a56aae Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python-w3lib Version: 1.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, python-six (>= 1.6.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python-w3lib_1.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 14178 SHA256: b56e06fe8a1e6fee6777e4018bc7d636d11c63da12365bffd36a17748229316a SHA1: fa42311dce6460190b0f53e9732332f27c700ce3 MD5sum: e1e6355c15ee506303fbb9f8bf538e8a Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-jquery Recommends: python-simplejson | python (>= 2.6), python-openssl, python-pyinotify Suggests: ipython, python-genshi, python-pkg-resources, python-lxml, python-greenlet, python-redis, python-pylibmc | python-memcache, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python-werkzeug_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 163506 SHA256: 36413e807ef6c8a35a35370ee02139b6481335228d5ee8309984b97dc5c2eeb5 SHA1: 2de31195fc04e0452fa9d41b72d9d1a21778dd6f MD5sum: 6d06077dd2e41bdaaf0e3472b80df99c Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python-werkzeug-doc Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2697 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Conflicts: python-werkzeug (<< 0.9.3+dfsg-2) Replaces: python-werkzeug (<< 0.9.3+dfsg-2) Homepage: http://werkzeug.pocoo.org/ Priority: extra Section: doc Filename: pool/main/p/python-werkzeug/python-werkzeug-doc_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 880818 SHA256: 057a3dc0b856ac6387131a0f8d8693f4143a32e93ad22189f9729f10fda2d9f2 SHA1: 751bb017a92beebba4ce4863fbb52f88311dc916 MD5sum: 8a23035e9376f2d33827b4e4c8da721e Description: documentation for the werkzeug Python library Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python3-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 777 Depends: neurodebian-popularity-contest, python3, python3-lxml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd15.04+1+nd15.10+1_all.deb Size: 81936 SHA256: 0044b925f2a4b2936b99fa8d876ef80b47a556182f1a12f302983846a4b1f90f SHA1: ae77286eb819a6f599f442b8ec79fecaceaf4678 MD5sum: de0adeb3c0b211c74f5274dd3ae94e69 Description: Citation Style Language (CSL) processor for Python3 Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python 3 modules and the CLI tool csl_unsorted. Package: python3-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python3-contextlib2_0.4.0-3~nd15.10+1_all.deb Size: 8736 SHA256: e113a4bcb9b97cc6847f1b6e3ede3a211f1c15b2fbf0300f79211de43f32f0cf SHA1: 709296fa01004b17282e9539f49bfd307a81e9d1 MD5sum: 8f47d6b47f71a7dc0979953dd42e7478 Description: Backport and enhancements for the contextlib module - Python 3.x contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 3.x module. Package: python3-duecredit Source: duecredit Version: 0.4.5.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 225 Depends: neurodebian-popularity-contest, python3-citeproc, python3-requests, python3.5, python3:any (>= 3.3.2-2~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python3-duecredit_0.4.5.3-1~nd15.10+1_all.deb Size: 46790 SHA256: e6329a1d6a996fe9e2d34b0e258ae8d63d7a337da94f9cd1aaad88a74315b32a SHA1: 08486f7b49a8ff062fc8797a5f91b09034d5c48a MD5sum: c088969aff39d1c95a9ef6f7056d6519 Description: Publications (and donations) tracer duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python3 -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python3-humanize Source: python-humanize Version: 0.5.1-2~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python3-humanize_0.5.1-2~nd15.10+1_all.deb Size: 12680 SHA256: e9e699f17f354de3e4d7baced43b41a7d582fccd6cc1ad892c9e137486c6773f SHA1: 3f1ce33104fe52071cb463e036474e8e1e671c66 MD5sum: ae611130a59c7598a5c3beb5abb33e62 Description: Python Humanize library (Python 3) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 3 version of the package. Package: python3-joblib Source: joblib Version: 0.9.3-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 339 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.9.3-1~nd15.10+1_all.deb Size: 74744 SHA256: 905b12cc35735100bd9ea8f0bd3fcb178b306a1c68d5537f22540dfe03ba4c18 SHA1: 6a36efc5c8cec62d5556dd5a2ee8873a9d372b9f MD5sum: fd7a692284ae5c38c52ecf94cbe99082 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-lda Source: lda Version: 1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1448 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), python3-numpy, python3-pbr, libc6 (>= 2.4) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd14.10+1+nd15.04+1+nd15.10+1_i386.deb Size: 250312 SHA256: 6338c7a368c8d23d9ba86c75f9b30c0426a1888ee13c1c3ced448021752a5468 SHA1: 622a41b0ed72b283b7623af6eeda65652c4aade4 MD5sum: fee8f1bcb10d6b5e1969b7491d507b44 Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-nibabel Source: nibabel Version: 2.0.2-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63305 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy Suggests: python-nibabel-doc, python3-dicom, python3-fuse Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.0.2-1~nd15.10+1_all.deb Size: 1953122 SHA256: e961c0212b6dd980cbf7cad38e976534e3ab2dc5a9bf763b3975ec72aee3aa75 SHA1: 44bdbcd498382c24ecebe842d848219546e78cb2 MD5sum: 78500bcbc5973a8b920266167a5f0b52 Description: Python3 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. Package: python3-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 745 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 118474 SHA256: 89479d014453d12d60b8d49858032fc1d95ebfca9276419f648c021d481221ca SHA1: 1171a5ecfb14a53cc349267b73a8444535f325b2 MD5sum: 83058748730eb8c974be44756a2f04e0 Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 631 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.4.3-1~nd15.04+1+nd15.10+1), python3-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.4.3-1~nd15.04+1+nd15.10+1_i386.deb Size: 94602 SHA256: 63153a71c8d70e8e7ce9dd07132bde42472e81ff60e7024591d2d0fc77d8028a SHA1: 0915e9ad837c7c3fd342f5de2d6d369ee0a7c460 MD5sum: 8bf8e16436f0bd47f55188986a797ce5 Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-pandas Source: pandas Version: 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 19838 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1) Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-six, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1_all.deb Size: 2342452 SHA256: 7ab4075a7c59ba30edac6ccd924af81469fa814d4d9f2efcb4f39de9f0019ffc SHA1: f95fa32a4b7c1b76b9db9bd7f350ac020b9f654f MD5sum: 95e595910f659c75854d326a3bfb42c8 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: 0.17.1-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12639 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.17.1-1~nd15.10+1_i386.deb Size: 2170546 SHA256: f9bfa08078cc2833b50b0838736683c47db49857de7aa0da18262532eec2718b SHA1: 576794aa8c0b2f81685d6623705a9db92f153486 MD5sum: 6e08384d708a6a694a28c9726b663e24 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: 0.4.1-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 780 Depends: neurodebian-popularity-contest, python3-numpy, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1-1~nd15.10+1_all.deb Size: 171132 SHA256: 374bd7eb78069fdf1b1ef6175fb3886bbde3a55699f80d7c4861065f4f137660 SHA1: 0e6fba8b23f0b29d7f38b11bc2f2665e9ca05874 MD5sum: b42c7c14930ed791f1a1cc02c5e43f0b 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-py Source: python-py Version: 1.4.30-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.30-1~nd15.04+1+nd15.10+1_all.deb Size: 66784 SHA256: 44c24c7e7d14ae7ebbc777d138a0255b99c2033e47da0535c186df618af32d68 SHA1: 152c58c9c5f05613b29b29d17ac6479e3c5c8c6e MD5sum: 07f66b4226d0cc61a272c82e8bdbddd1 Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pytest Source: pytest Version: 2.7.2-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 465 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3, python3:any (>= 3.3.2-2~) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_2.7.2-2~nd15.04+1+nd15.10+1_all.deb Size: 102460 SHA256: 424de9f1c79e3e22df9e310ed6b7e4b526f15964fa9e281c9f32eee34788de84 SHA1: 91180a99a3dce1a700c7ee432de886252e59404c MD5sum: 08dda5d2bc3625ffa1d13b9a5dbfc23f Description: Simple, powerful testing in Python3 This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 3 module and the py3.test script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 61 Depends: neurodebian-popularity-contest, python3-pytest, python3-werkzeug (>= 0.10), python3:any (>= 3.3.2-2~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python3-pytest-localserver_0.3.4-2~nd15.04+1+nd15.10+1_all.deb Size: 19344 SHA256: 8fd2067e092f0556686cd15f9ce8feee1eec3fd1ea4751ae32af05ee3c18843b SHA1: 1f420dc2c6c5b2d515c152a36a51820d6cf3c49b MD5sum: 6b6ba11341c3a7feae080e053f21600b Description: py.test plugin to test server connections locally (Python 3) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 3. Package: python3-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, python3-pytest, python3-tornado, python3:any (>= 3.3.2-2~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python3-pytest-tornado_0.4.4-1~nd15.04+1+nd15.10+1_all.deb Size: 5856 SHA256: c1a5806687563e8096815a04fcbcd1c7679d9b656371bb71687d52948d63a7ae SHA1: 0cae286527ca4e4545f1dd84ea72ed3009e126df MD5sum: 79cf2d318bb1d9be926c8594e6fec5d7 Description: py.test plugin to test Tornado applications (Python 3) pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 3 code. Package: python3-seaborn Source: seaborn Version: 0.6.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 702 Depends: neurodebian-popularity-contest, python3-pandas, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.6.0-1~nd15.04+1+nd15.10+1_all.deb Size: 118332 SHA256: ceb7f817229ddb5f41e56b005f2d1e447cb26420d0fca64961f3e2cf790668fe SHA1: 7e4ed92f564069d0f5e21ebbfb46b55d06d3fecc MD5sum: 0a150c7096e4a22826076661013e57bb Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 3 version of the package. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd15.04+1+nd15.10+1_all.deb Size: 11166 SHA256: 1a35d61217a447155375d01b44b37352135bf032b57e8339a8bd18698ad7bee5 SHA1: f1da621e5d147710e807cf664696af5e55f7b08a MD5sum: e5b2847694d0a8355dee4125351645b3 Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-sklearn Source: scikit-learn Version: 0.17.0-3~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5277 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.0-3~nd15.10+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.17.0-3~nd15.10+1_all.deb Size: 1221660 SHA256: 8b3e51b17bb61e19b90f1be7aaa9df8ec3f9370a6152974a39bb32dadd93e9b7 SHA1: c7e2a444ed01af9f1946bcd624c6f58e679361ed MD5sum: 95fb81979d2f48f0a030ba8c402a7695 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) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.17.0-3~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9210 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.17.0-3~nd15.10+1_i386.deb Size: 1385552 SHA256: 83b048545d94a3c6a78547d568ad3f5583e5539ccbc90c9919213f886cdb80f0 SHA1: 36d2ff5503944e2ba9e55dde7a9c866aa4291a3f MD5sum: 0b64382073d4ecdbe089195f1d44a506 Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 360 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3:any (>= 3.3.2-2~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd15.04+1+nd15.10+1_all.deb Size: 117324 SHA256: 2087eafa13d5d935b75bf36177ccfb79fcd4a4d725a019a9405e6c0fd01a7946 SHA1: abbee96514412f64d6290c13eb64b0e76301b72d MD5sum: 1be1eb10f30f9c390b16d84730cd7621 Description: sphinx theme from readthedocs.org (Python 3) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 3 version of the package. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, python3-six (>= 1.6.1), python3:any (>= 3.3.2-2~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python3-w3lib_1.11.0-1~nd15.04+1+nd15.10+1_all.deb Size: 14272 SHA256: 533da9885ad69c4c60651a590db9fe179c98ca1299ebdad29088b6a9442ec0e2 SHA1: 2a0727511a0a354a099d604f19678016d837da35 MD5sum: b430b30d2b88af7a47b2cd4f7858d04e Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: python3-werkzeug Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libjs-jquery Recommends: python3-simplejson | python3, python3-openssl, python3-pyinotify Suggests: ipython3, python3-pkg-resources, python3-lxml, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python3-werkzeug_0.10.4+dfsg1-1~nd15.04+1+nd15.10+1_all.deb Size: 163474 SHA256: 8a96e417144a08c9a879cc1f5a75631c281bb44e3365214ac99d47d7de3f3158 SHA1: 20740ca85a429f29943d1d914db42fcdbb144741 MD5sum: 89cbd15be9a80bb4de07236524ee85f1 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19187 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 9766876 SHA256: 7d9bdb3a82e3a43a02259ce2031e99063bca119ddff1e3d6bf7ce6a143b9bd37 SHA1: f83778e94a46401b881ced3fbc687dc547f5f6a7 MD5sum: 1c82284fd53d2f35105ec08dc391695f Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73020 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 45519214 SHA256: c60d1744dbf2040909c0f26a32cbe986fe1036f3e5e54c09e8725b841202e253 SHA1: 0f1de9650eb97178e6519f5f010cc73a97144a63 MD5sum: 124be2462bf6d731e2fe1cec360c6551 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9252 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 8934882 SHA256: 6480ec9d767bca325e0a22048cae1ffa576957b7571173989de5b2aa34e6274d SHA1: 37ab9dddd62047263547e3f9c9d870145ca75495 MD5sum: 6341a23c432a49ecc5ee9c3acf4f1f67 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: stimfit Version: 0.14.11-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2546 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.4), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.2+dfsg), libwxgtk3.0-0v5 (>= 3.0.2+dfsg), python-numpy (>= 1:1.8.0), python-numpy-abi9, python2.7, python:any (>= 2.6.6-7~), libbiosig-dev, libsuitesparse-dev, python-wxgtk3.0 | 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_0.14.11-1~nd15.10+1_i386.deb Size: 749160 SHA256: cff0e7c1fdf3b64da39df1b2e0b3c88b6066406be7da226dde0857b53e671652 SHA1: 8cff25f996de4554982d067877b9793728fe268c MD5sum: d244300c9212c59450fff9ba4f3ff545 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: 0.14.11-1~nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 22304 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_0.14.11-1~nd15.10+1_i386.deb Size: 4428908 SHA256: 035b1eb5949e1a3cdc9f281a28b7e5c72b5568c5fb542716ba16d9bde7df8cf7 SHA1: 956a64cdf440851fe1b4d4041227e84f12338494 MD5sum: 9b47504221f89ffe151b5df027c712a7 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+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 400 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1+nd15.10+1_all.deb Size: 85928 SHA256: 936b9b3bf81d8968c2480748adff4cb602f064eeb3fd484923b10f2f376063ef SHA1: 027a77a63a9a04e4f169e0c0f041a9620e4b31b5 MD5sum: fc628c660d2d143f5dd33145ae1cc28c 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: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd15.04+1+nd15.10+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 5.2), libvtk-dicom0.5, libvtk5.10 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd15.04+1+nd15.10+1_i386.deb Size: 74284 SHA256: 778cc167ae10be4d14a9993f4b1e7a209a164212a9ab6b593f71c193f74e2d34 SHA1: d3ba2f4426ee04179a9f8ab82b251eb381e8bcc0 MD5sum: 80413e7c7d77a201365fb25c1c29037d Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools