Package: aghermann Version: 1.0.6-1~nd15.04+1+nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 520980 SHA256: 765131d4c208c334da87132d777ef0673d7c4cca62f96d87e60f1d3e05336642 SHA1: 5c4e5d222771b3d1119b848040c7dc37a2cc45e4 MD5sum: 04440351bcea08181f7ddfe69b8b2f7e 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 680 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 244400 SHA256: 8df16469e4c7a140d6567b8276e3d13c5daf017b9ec30030bb6737b4e357cb21 SHA1: b08084786b7913f1d73259a14918da8754e61461 MD5sum: e9c8cf542cbce70a98c70a655c64a6c9 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: 0.22.0-1~nd15.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 195 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_0.22.0-1~nd15.10+1_all.deb Size: 52250 SHA256: e46794d4d11f4d4e4ed0582b9d9f2f6addb4f117e4da38f25490373821fad455 SHA1: 148d42542d9ede0c04e8281f5ce5b741e15a5974 MD5sum: 949a538976b7c093c1eb7748e5e3bd29 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3460 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_amd64.deb Size: 495208 SHA256: e318bb52e69cd0dd411e98827ad3006927db02f517321f148e28b3cc541b7011 SHA1: c5d333fec963e854443b6ee71288ae12299f0060 MD5sum: e3c1ec53c579f7e560bbdfd87d008237 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5629 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_amd64.deb Size: 4574962 SHA256: fc303281204f6ed3d1689190dabd19fbea5945eb997abcca74a86b19a25a613f SHA1: 0a3b75ee8ad85bb77c019fc30364192f15169cfc MD5sum: 1ea984a7ae58d226e7ac5f44134dbfcc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1043 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) 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_amd64.deb Size: 146984 SHA256: f9f12474523142192a4f42baaad449e6ec3e195071134fe3ce7008587136ba78 SHA1: 553861cf0ab343184494a9fde6cf595b0942f7fd MD5sum: b08b1faf665fec94df753e6254e9617d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 17664 SHA256: 0772d8ae57a2b7e0c9df039d91aecb0f0ff3dd8a7bfc406f644cb4be625cff3e SHA1: b07c8c47e9005c9320d8ec31200dc3de32293c72 MD5sum: bc6dcdf7b119d2eb273379450f1811f0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 39228 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 19436726 SHA256: fdf7676b9e40adbe6cae810f38915d9b2a2b334a63ef1e7081eeb2e1639e9a76 SHA1: 1bce2c91c5efde5ff4aa26475a377a07243024e9 MD5sum: d5595fe1b3bfd5ca9038053384a39502 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 109325 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_amd64.deb Size: 107082064 SHA256: 62cbdc46047ff2513ea8045c7b13a2bfc365827efbd3261b0791bcc6e3e91175 SHA1: 52f33582c2cc9596d81c12bfed8c2fcb1b3d61f0 MD5sum: bcf86b36e849fc4903c38d4ee46f2ca7 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 200 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) 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_amd64.deb Size: 87742 SHA256: d4664cab022961db5affc0bb4c32e9d98d878b08b11a5f590fb7211e52e23abb SHA1: 3f2c038ba1e08f8afb37caf293d0f77cbe6da46c MD5sum: 4042fbf38468278650e45f2ceead6197 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 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_amd64.deb Size: 38584 SHA256: a39a50a9fd9917205684db778dfccaf76bbec9a9ce591054078252ff1def5407 SHA1: b9332b060e1221f534f10b134dbd8fda82606a5b MD5sum: f44eb5e2fdf7eb604d82bd56cfc0e5f6 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 44718 SHA256: 129f21a7c7c0247b2c190820b61c9fae2159a2fe6db3634fe002c088c34821cc SHA1: 13413f64ffae680161fbd4217c529335a97b8928 MD5sum: de8bbf50eafde5b3dd8a896bd412b7e2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 130 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 37506 SHA256: f90191fbcfc34f1f97d68638cb080f39195e6d139f8195d7e52c90ac57e745ba SHA1: bed50d974512a7bcf4b733ff657f2bbdfae8af18 MD5sum: 42cc5a260ccf70b5485984d69680e957 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 78720 SHA256: 85aebe0cb3f7225391dfbdf8f6b5688ec6ce61fb897d5f4613335b2851d3f449 SHA1: 4278b31fda4a5970911e911a8c5581137af45912 MD5sum: b93535fa14064d57d26c3b24f89cd786 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2870 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_amd64.deb Size: 598732 SHA256: 76e56382cb3aaa04e7d66e8054cde5463a80336b86ca0be2cf6fec93b41b9039 SHA1: 27e29d49ce60b629cde162cc30c68d9e4a98c030 MD5sum: 71c38fb89ad80892b315e189a6e4b054 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: amd64 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_amd64.deb Size: 8636 SHA256: c73151235babcb5b74a0b9f043f2b92bd1a42b83f21de0d12596d13753896148 SHA1: 020a287415e25e93e1e8c77d1ec13a5ee789c1bc MD5sum: 3b1ede1602a8d9f64618bd9fd5db52af 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: 6.20160119+gitgb2a2f5d-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 398346 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_6.20160119+gitgb2a2f5d-1~ndall+1_amd64.deb Size: 28589356 SHA256: f8ae173e0e402bcf43a28dd94b38a0e7b60772813050fae17e34b1582c06e22f SHA1: ef2bb48edb2ffee9a41e51820ec28c4c9789b139 MD5sum: 6bd9ecb53ce876f1badeb2be5e1abb39 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: 6.20160119+gitgb2a2f5d-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 45 Depends: git-annex-standalone (= 6.20160119+gitgb2a2f5d-1~ndall+1) Homepage: http://git-annex.branchable.com/ Priority: extra Section: debug Filename: pool/main/g/git-annex/git-annex-standalone-dbgsym_6.20160119+gitgb2a2f5d-1~ndall+1_amd64.deb Size: 9076 SHA256: 86e9f6d9b10333c47247e7e95f653c8611a68202d7ae9ab86ca911cdee061be3 SHA1: 2dbae765e593ab6ca76b188b75a309d6955af7d1 MD5sum: 98889afd979a02d108a33808562575a5 Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 75d11a3ee55319e6cebcf33286de8df9a39bcaea 75d11a3ee55319e6cebcf33286de8df9a39bcaea 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 12741 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_amd64.deb Size: 3626776 SHA256: 765d2d75d86c0c6338f3d22881175f3977c67d87b8ede914e2db8fe44342a720 SHA1: 6fb0f6893533440cf97f0aca8bda5d0bdac535a4 MD5sum: 56bb82e77f1824c583a713920a3d3055 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 36785 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_amd64.deb Size: 34737824 SHA256: d3479be43e499ed721bd6e00c83f660d86b161dea0c282ac55f49fdc86caf487 SHA1: 93c06e1a4dfc988049d97b360fb34c2f3a8f7292 MD5sum: 54c4176aa344cad93b92307b656e8cf2 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 1655 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_amd64.deb Size: 303200 SHA256: 3477c8345e575a16831cff0a950e924fa2286f031eeb918c9e785b4f58996648 SHA1: 96bf8271252c93eacdf06113f5c6c6fc49bdaddf MD5sum: 34c13f93bcc9fbe7962be4b8ede5e18d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 423 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.10+1), libboost-program-options1.58.0, libc6 (>= 2.14), 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_amd64.deb Size: 122378 SHA256: 0f296e655d2529f43f92ae0fc6be8bac034ced74c9208080f19f3903b606573b SHA1: 932185a3af030744be0d5e8a3932415f5d637767 MD5sum: 8aa6b37d1a4162584743a10ebfb03fc2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1741 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_amd64.deb Size: 304894 SHA256: 7f509117c6b79e6dbe7c97d0e885251424a16429e8e5655d92ad22e47fc01321 SHA1: ae654d86568b835a854e72c41863ac9b54ce37c9 MD5sum: c8d412d06b55a32979a2b8bfcd959efc 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 923 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 281544 SHA256: b331ef9f5f9d3b0e82cf8be9d825fc3eb7b855438ce35557263540e83b0e946b SHA1: ab39fe56782a6f2ca813406c60de261bd0ba28f7 MD5sum: 539e7cc42fe0462b54df00259b3f87af 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 395 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_amd64.deb Size: 71984 SHA256: a37a61296e0b36cb75246f4448ad7f5b06d667b4de5f9de1eb916645fea6b9a3 SHA1: afc47cd73fddebaa6e5d52e885fcb6a9bb6884b3 MD5sum: ca1c839801bf8f8f33a81b8c47369284 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 1423 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_amd64.deb Size: 238094 SHA256: 8f501e3174f8c7fb3363f2c9f254aef3d42110d746d62b76426427d388e2b86c SHA1: 497bea526340982ab23034527e665a0258564c98 MD5sum: 3de2e621fc8a706a390143f7a8d3ff84 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 589 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 189380 SHA256: 280bc4c730642c7683d630116ce6f1250613a285ceb9ee5c0c919caf1b991e7b SHA1: f0d9c3a2fea4ef60b4778efdc1830f372ebc1513 MD5sum: 319930ce56df4e1667ad757035d9627a 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 280 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 77712 SHA256: 93c4e8cf9ead6e475db25896a91f0d3632bd1dbb2d881c87f0d9b65143a952b0 SHA1: 46f94dba10c9b45d73e068f211bd04d410b73471 MD5sum: d72c2226aa683b67fed10193207adbb2 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: amd64 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_amd64.deb Size: 21252 SHA256: a586fc2c7138b7ac2ffa99290c9b674e102a65440ef159b389bdbf037fa1ee4d SHA1: 7544cfe4e0bf990238f8b6ddb832a54a1fa42b7b MD5sum: 9fe43288ccdfaaf1cf8e374df2ed71a2 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7746 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_amd64.deb Size: 915088 SHA256: 6d3f07725f0d7377037adbbb103a9493fef249ea59869a8109886736b80d2411 SHA1: 81b53327779bd4253fd8151abb1ff5d32bd3decb MD5sum: a181f254a80c7c12fdb03aa613d428e1 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5054 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_amd64.deb Size: 818722 SHA256: d3ccc3fb25db51bd2f30b07956bfb3a469454d3c4195458c771936de54981a1b SHA1: b2878b3822e01afb1baffc1614fc7cc830aa5c36 MD5sum: ef32707d94a9f3859ef4c4e092f76ceb 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.14), 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_amd64.deb Size: 54902 SHA256: d42b2b2ea9dde425755c119c74a243405d36c699733d1bc257fc2ae0fb068bfc SHA1: e42b83a24c933e53f535481272e2f2f41c36d73a MD5sum: 0ec60e40cd7422e03c22fc6765591c77 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: amd64 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_amd64.deb Size: 8662 SHA256: 1c7e3c73e880663f31a5aa63d5bb25153c6a03e17253041b4a9b46bb107519e7 SHA1: a7e0079c4ace49d760304a8857750e74d8f45243 MD5sum: 246b7a348f6717856988f8d94359466e 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: amd64 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_amd64.deb Size: 19438 SHA256: 3db0c5d26ae21010349d67854323ddeb36e8189b6cfd755f806837b94f6b6550 SHA1: 17df03b3d3a704f586f34113f3fc698af4f6f2f0 MD5sum: cd04d6b95b239d97cbaf54b3c9b764db 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 133 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 42448 SHA256: 67eaa104ed0ab0484a8d756fa8fe1dac07be8a4b5eed39c7b36c3206cdf6b5f8 SHA1: 008f0fadb6a3f001fc8db22184e03b9f0cdcba25 MD5sum: 0263955da891fd014da2bc9e753621da 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 515 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_amd64.deb Size: 101408 SHA256: 18132c8728ac0b26463933ed438f32e0b0a678d9137880240ac1b2afeb78c97d SHA1: b623f0fb0c01bfe0fbe2e914c90f73f99c6ab779 MD5sum: cb60acda025249c32db452645edecd2d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 266 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_amd64.deb Size: 85388 SHA256: 79b8b760a3a2ed9a0c95838ce1330365ba936c6fc1417113d708491abeb39074 SHA1: 899c348c1ff75a9f6c133a51abb89dabfd9a2f1b MD5sum: 7def016111b6a1a71f02e5488c2c5cad 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 117 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_amd64.deb Size: 31336 SHA256: 43644426a1cb014a192d688660979941b829e08140dc65d03155cc1c3b2ea3f7 SHA1: eaf0ee119408a2f964c19e83af4615917551552a MD5sum: a8d1b8cfa054bb4172d570eb2574b4bf 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 71 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_amd64.deb Size: 25452 SHA256: fa9a162a7fa77ff1b6d112f2201774f012615e8405cffe31d0abc8ac08854eee SHA1: f7262d2dcb13d09b4454270dd774e2716f1487f6 MD5sum: 03d75da45fb45097172a7f5c07e18a81 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 320 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_amd64.deb Size: 61352 SHA256: f9549e825c6534f5a605e8c76e2dd6d957f2af855270c5b2d5be9158b3136b71 SHA1: 2098c3673053ac44a22e71dd24b514e8925de072 MD5sum: a8ccdc5ac2532d6777143ad8ebbca6ac 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 43282 SHA256: f37a4759014205dc17ecc62ccddc767b85a74687252c93b98f7fd9e87791150b SHA1: d0e70f36121970770fc7064518f5728826f1f9a1 MD5sum: e6a8b48de32efebefc3d1adc802b8cef 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: amd64 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_amd64.deb Size: 13788 SHA256: 1e0802315327a838123f9a56c10b9325856f40b6e9302654fce2acaec241a8d3 SHA1: 2e7e9699aeabcf5ceeaa2b0db7490ac83f618b76 MD5sum: af70db860ac3751874d52f74ab629576 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 341 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 77814 SHA256: 80dffd7b4c80895929ee1ce943c0d2ec817a7b1a1107225e2f0aa68679bc9e04 SHA1: 02b02928e3cff07e5ac39db9ae2b8a9a8307fa6d MD5sum: b033287aafdbc2fa97bdbeaea268e28d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 277 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_amd64.deb Size: 74308 SHA256: 699f9626d49739684904c27913b17dcaf11a187359faed129351906680874a10 SHA1: d2e7bc3379146b0912627062c308627fd7d2aa2b MD5sum: efad2fe07c019fd08a786388dd3c0f62 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1787 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 445524 SHA256: 26aafaa7bc30ed4adab49223f2eb4ead2e891cfc43b82ae7dfb0c43e1331bfe5 SHA1: b5db8412249d025a104c3cd46438419aefd03ead MD5sum: 14633cbaa41df73ce076c784e30d9d19 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: amd64 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_amd64.deb Size: 80894 SHA256: b463293241dcc981bd741f38427e42a5d375f983f7ae433f685b727e2faab953 SHA1: 786c40c771f5782f07bef602e8e0357799fefc47 MD5sum: 6eee7fb021c2d2b68146746be6cf26be 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 120 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_amd64.deb Size: 37758 SHA256: 3d816cda59b140f328ed0e2a34fdd7a6597f98e29dbf38be06ff7447484d1ba0 SHA1: fd16596acf73e75a438d2a07cf4efe8ddd37deae MD5sum: 0d7e7021a481b5736152f028c4b99f63 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5560 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 829604 SHA256: 40d246cfc8d993bc7fe232b00af6f8a03686a86406f2e85be8d634c81d8b9f0a SHA1: 88c5d594ff045dd390e6da246ac9779b0fb38411 MD5sum: 1c296e0d8623ea72c7c6b033fba8baae 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: amd64 Maintainer: NeuroDebian Team Installed-Size: 16779 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), 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_amd64.deb Size: 2312386 SHA256: e31d9422a4f2e6f77a43c86434b1b613399e060fd3735b471d2755cf67ee7a05 SHA1: de0954f9719d9ef5a32b35f6a81e58cbb29b4579 MD5sum: d123e8bf062ed7b37ddb38a856a1da9d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 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_amd64.deb Size: 31110 SHA256: f7be3cc7aa2045129754099c254322ae1310a194d61f94ccd0b23cd3e346dbd4 SHA1: a9ead25abda0dfe22b9b51fae65222c07f8fc84a MD5sum: c66ee98da8a9ce48c8474bdabc2d04e8 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), 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_amd64.deb Size: 19710 SHA256: 7d0c56ac2433430b9ab571db02531d979e89d824fe02a5707688fd8a4a5352d6 SHA1: 28810f033c7dbca0ab6dae15fa0e1ae0fae9de0a MD5sum: ad8c745e1c73a087286c20e07b6e421d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 231 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 (>= 2.14), 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_amd64.deb Size: 43404 SHA256: ac540e937d52e30d083d976f2464022ccf4128bd20a7d16c93b00e4d3474ba12 SHA1: cb1a55f4edd52b572a93cbc7c1d486696f0e9889 MD5sum: 979ddedc663b74cec8704d660d250901 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5338 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14), 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_amd64.deb Size: 932958 SHA256: 9c01cdc70088cf83fca2183d67ace62f8c628f6ea24f838f3507f95077fd1fd9 SHA1: 16e51fe0dd110d994cfb75b9010149adaf1b9af0 MD5sum: 401103ef49840b3b8ac6cb2ebfca15cd 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 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_amd64.deb Size: 45308 SHA256: b73b41ddfc083ba6b64d9143a307e24c110bb58369ac9781c758b481bb28d1b5 SHA1: f3c265a1d0ea1c2df0195c35a818b0f8b4994357 MD5sum: 1143cbcb697c048538eb515f46a82af0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 231 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) 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_amd64.deb Size: 53980 SHA256: e2d2418c5ecadae051d8ff1e669bfccdd661f8b30b9f3c49cbf19b4581806715 SHA1: e435f5fb621b779d5d59cb27bcd716dc238b678a MD5sum: 14f18eb2598e5bc8e59441a82154b58f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1320 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 237580 SHA256: a65707d17f93a01b2dfdf5f505353d5ea329b85c7341978d878a49d5235f6692 SHA1: 1b81773815ad71fdb36e681404daad5d4e5ef379 MD5sum: a3a756a535d4e96d3e69224db6882795 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 135 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 47594 SHA256: a88ed9e381112b58c9bfe4ce20ef8c9c4e4dd7d5b4865c6e7ff0ec49f7ac1cbe SHA1: dc6494af5153dc366283c392ab1485c84e81b730 MD5sum: 68eec460deadfaa1e79a359d4d85c511 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2616 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 620276 SHA256: effa86809b7cc37d8386d90023c80ba60d69091645c3f471196c8b5558f8098f SHA1: 1925894dae9f167d84eb1d13d941646128775bd3 MD5sum: 23acadae93e0547302df99557d7ed76f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3761 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 631578 SHA256: 3bbfec9506c910b84de20e22f732a0b40e4abc331700eaa3dd940f57705b2c55 SHA1: 5a8b28f51fd324afbc636f5740376e9a3edd231d MD5sum: 466654674624f68a1d561f76f7913605 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 401 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 (>= 2.14), 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_amd64.deb Size: 136156 SHA256: f5b87d36c04471feee4b4a7e094b1e4da101236399470e37efd386b75aefa243 SHA1: c613b83e6f774b781024f3ac3210541372e1757d MD5sum: b358fc9eee2f2690a4ce1b4d9b97d5fa 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 274 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.14), 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_amd64.deb Size: 106548 SHA256: 944efdf874423f66f0704ec8c3b3c7b63a60ac58ed1c2393c0abcc363878ef13 SHA1: 128f72de8720d4b6bb9fd4ecee62bf74a4d756be MD5sum: 8ace0108dde7dfbd74fdf9221d46a0e4 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: 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5882 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1_amd64.deb Size: 1527250 SHA256: bd3793a28d5a0fedfa0151e695ed32ff1007919c615af84f39ceb69d57988d8d SHA1: fc8b0c1b672906970aa75d0891b223ddde894c22 MD5sum: 51be02d8933037c56db7133ddf1e3860 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1434 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 (>= 2.14), 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_amd64.deb Size: 284186 SHA256: 178273665af4cc4d367595b8cc232dc6c089efb17d0ad3a234369277a8af8251 SHA1: 6269db9e94394423ba8aead3f942ef58380e8ba6 MD5sum: 17d8fa14e2a754a0f7d11e50f2207404 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2805 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 591630 SHA256: 4e76fe2ad5eacd88bd6920fbe740c41d3bdca0fa0c6bbb6d1801512e0079d11f SHA1: 717a4b15a58fbbbc6752c06709d8dcf215a62a12 MD5sum: 5066a2886871aeebe8930cc760e23b12 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5017 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 1110460 SHA256: e8e8cf0dde52682258ecce85fbc89efb3c3bb940924bd2459e9f251f13f4b2fd SHA1: 3f4805cb98e16f97150edc57a13a3b2699defd1e MD5sum: 031b80bae456cff1a9de821d2b24341f 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 899 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 (>= 2.14), 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_amd64.deb Size: 302690 SHA256: d0be2055836b34f9d1f3722b868048ed212a156a3fbde32c835bb8669a176850 SHA1: 5150640cd9d4ad7420341432f305dc96357a451f MD5sum: 315b72811aa0e20b44ee79fbf69a5093 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 494 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_amd64.deb Size: 90778 SHA256: 0b561af538424d933738303cad4cc68bf90f2047a26769ad0322e5a9c6e42aba SHA1: 16c030b30ec3697298f6a2f3c6b98f3ee499b7eb MD5sum: 121d86860e7c68de809fd87ef49c0d7c 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1444 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.4~), python3-numpy, python3-pbr, libc6 (>= 2.14) 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_amd64.deb Size: 252858 SHA256: 9ba571288f3a8baac8b36fb5cb809f4be8087cadcfa5e31d10fc5c3b7327a94c SHA1: 746a1c2a6b3cccfb5e1842b78b40f0f6755d6eaa MD5sum: 5e699fcdd7a6a4b7b823bca07a9fc7fa 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 637 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.4~), libc6 (>= 2.14), 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_amd64.deb Size: 131116 SHA256: b3f6142a152f090716c576550e64c0ba06439ae6b456f11c591e17d1a872a594 SHA1: 1364087847e96c0501a79ebe262b32a0ea62afa4 MD5sum: 1f5b3b0fcba73592b3d0f049a6c53719 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.4~), libc6 (>= 2.14), 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_amd64.deb Size: 107166 SHA256: fbd5504b5dccb878a9882f646fbab98532928ffa3a9d56509aa9b7aa08919338 SHA1: 4d3f2142bf6529d7ebf32a4a27923e24803a522c MD5sum: 72c49d9bd6644c3e0f528d5e16156c97 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: 0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11441 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_0.17.0+git8-gcac4ad2-2~nd15.04+1+nd15.10+1_amd64.deb Size: 2234198 SHA256: ae9869d170d91d62c05ebbc64e178adf3d47620181b0a79bbcae1e0c716e2ed8 SHA1: 82b50308668b9cad2f9f56fc38e1866cb8d3f043 MD5sum: bdee9c58e580cd8ace62bbf8f8b3930d 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9126 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 1480876 SHA256: ab6571d483093810009ae448e71c6b3064298dc7750450f2eeda37705ce1912d SHA1: 5b5dd71bc48668ab3fbb723e2b54037f12e74687 MD5sum: 05642dac864950b560bc742ab9ddeec0 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2759 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.14), 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_amd64.deb Size: 739130 SHA256: 08a782212543eb92fd0527ae015b750f5f2e625fd385d6ff306302188ee7ed1a SHA1: 0735a62ff9c6a34a2b32481ce06a9090f9b767e5 MD5sum: e006d311b0419d86589a1af2e1198e64 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 28648 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_amd64.deb Size: 6057370 SHA256: 63ddfa4878eccbe333065a63e5b3d76a58a14bcf30d3fb026174a9091c15a339 SHA1: cc9aef385dc3cfa2fca459363c18fe4178d5c2bb MD5sum: 69ae624bfc477962058d1c90ce276859 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: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 291 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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_amd64.deb Size: 74230 SHA256: 545cb5a8e696f2500c952d19b13e42a17e5551dbdde9cf0a577f8393def02a61 SHA1: 4b148ae9417e8dfda0bb6ccc96910d460bc70f5e MD5sum: bd5616da3c446973381a985fb9508a92 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