Package: aghermann Version: 1.1.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1630 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.14), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:3.0), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.31.18), libgnutls30 (>= 3.5.0), libgomp1 (>= 4.9), libgsl2, libgtk-3-0 (>= 3.21.5), libitpp8v5, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libpangocairo-1.0-0 (>= 1.14.0), libpcre2-8-0, libsamplerate0 (>= 0.1.7), libstdc++6 (>= 5.2), libvte-2.91-0, zlib1g (>= 1:1.1.4) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.1.2-1~nd+1_amd64.deb Size: 541528 SHA256: 52ba5dbe35d8dc541d5f5f69321132cfffab213a9f39ff9cd698c62397599f38 SHA1: 9321bceb74c2f4c2ad8dc457adb9e5cfff1135a6 MD5sum: 22c77f4d291bb1538198b5d4e6a870b6 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: aghermann-dbgsym Source: aghermann Version: 1.1.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11807 Depends: aghermann (= 1.1.2-1~nd+1) Homepage: http://johnhommer.com/academic/code/aghermann Priority: extra Section: debug Filename: pool/main/a/aghermann/aghermann-dbgsym_1.1.2-1~nd+1_amd64.deb Size: 11781814 SHA256: da0e83888dab39f8a0a8a20103bb26192ba7ddaea6358e626465cc07d44bd6f8 SHA1: 7726bd71fe6032f7e46d3b25395d77161fe29611 MD5sum: 4456b246af070cee4d9886b8234c5568 Description: Debug symbols for aghermann Auto-Built-Package: debug-symbols Build-Ids: 085cb3623ca2b65d2b2033c07fae435497ff0127 1142adafd8a9ae678f2de4174a4874421ee8c0e3 3574dcd5a1ce43966a76e4e22cb3dd1edbb4e37b 4ed58c90dd39dd1b5a20ad72b8e1f6d1d81fa60f 52ea19d7f2cc254d156b1c3b46b57e92c22f9f3e 68cd9729d779979ebe9e60a6a656989b65765e53 a03eeb72fa0409ee451e242249b5368aabebbbc2 a6ecc43d9014e52df4465cc43810348d3d5c488b Package: ants Version: 2.1.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 173809 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libinsighttoolkit4.8, libstdc++6 (>= 5.2) Recommends: environment-modules Suggests: fsl, gridengine-client, r-base-core Conflicts: gpe-conf Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_2.1.0-2~nd+1_amd64.deb Size: 24611780 SHA256: 54a066f48c29c963fdb553582c85c0bb8088b2f9160512ef041bc586d874cbf7 SHA1: 75b892a8e1c204f228441f3f202c7bc6fadde0ea MD5sum: 025c1c46e8a20d7249f6ad535bcc0976 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. Many of the ANTS registration tools are diffeomorphic, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). . This package provides environment-modules configuration. Use 'module load ants' to make all cmdline tools available in your shell. Package: arno-iptables-firewall Version: 1.9.2.k-3~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~sid.nd1_all.deb Size: 132466 SHA256: f27127b8c1dc917c0286a9387f8fa457376ded10b07a5908485636c27a2a14ff SHA1: 696de58c79bec6fd3efa3cf7dbbeecaa18d1ea8e MD5sum: da7a5641d17921fad83cbb534f2ebb22 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: bats Version: 0.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest Homepage: https://github.com/sstephenson/bats Priority: optional Section: shells Filename: pool/main/b/bats/bats_0.4.0-1~nd+1_all.deb Size: 14428 SHA256: 0f03a145105517af6b77b17a29c29136a50d1addd60bd676402ce7c9dab1ec2c SHA1: c946bfca85b5ec6ecc6be6c1ddcb960908fcbaea MD5sum: e14bddbd95bc1a10d6fd2f8fd5cfab64 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 664 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~nd+1_amd64.deb Size: 241148 SHA256: 33bcc37190d57787b0b1037992c123496665405d8d0bf98b422a9d752809d6ba SHA1: 5fba533ccbb060104fe06459f913bfc0a922b82f MD5sum: 58d6258527ac48e06bf837a9a07ae96e 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: 0.23.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 255 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv Homepage: http://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.23.3-1~nd+1_all.deb Size: 70860 SHA256: 15f6f58a62684e0694a396838b578d66ae974c3dd90fd553adad9b1599f5c984 SHA1: b0ae9db4e9b362a88f182cb901f642f58b80f1d4 MD5sum: 2ae3664d3654f56b0b640c710f2c826d Description: backup tool for btrfs subvolumes Backup tool for btrfs subvolumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations, with ssh and flexible retention policy support (hourly, daily, weekly, monthly). Package: btrfs-tools Version: 4.1.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3408 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~nd+1_amd64.deb Size: 486882 SHA256: 2ab34a74ac11405e0df3f8dcda3abe86278e7150b24049dbf5e5747cd1c5a9cd SHA1: 6b06ac0186a0139b4b60ed91e9f5b7b4596c232f MD5sum: db6c0b9d56acbbb19bc880f6e9d1993b 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5334 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd+1_amd64.deb Size: 4324746 SHA256: 0fa4afc8227c26e507ec3c57a64797094d9fa5d6d066887c6767eb3517423f03 SHA1: d258b6849962b26cec766e24bba032b6ffa7cdb1 MD5sum: 400719702f722029a52dc9c1eee6d50e 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. Build-Ids: 10ae215f5393407b1b4c4527ac8aca927195dfa3 19afe875459d6c5761c7f248f5623645953bf371 1c9e1b1a3c29c62de5c4e962a1b25b58ceb05630 3ec84a10f450216970019a4e2dd4fbbc2c7a560a 47a77c2d5d0c12d5adb7088cb08cda3ae72ee490 496604cf46f34b8e1ddf4cbbd8fac66071057431 59f686c021c3e24b014fe5e18ddffce3fdf5a85f 59f933da8c57ccea8b95fe23a9ea5e8756ac96b4 777c9cad588e48a53af17184ea5f1e060877e388 affb922cb566aff4802604a5b80e209a74ac8f49 b7dc34dd0718ad909df709d9a9cccc359d543fcb d80b273bcbff103e3416226e1072e3bc85acf813 ed69ea90cf3b002d00e4fba1bf14cd6831b8e20e Package: caret Version: 5.6.4~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18488 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libminc2-1, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, zlib1g (>= 1:1.2.3.3) Recommends: qt-assistant-compat Suggests: caret-data (>= 5.6.2~dfsg.1~) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.4~dfsg.1-2~nd+1_amd64.deb Size: 7376006 SHA256: bd0a9647dcad847aed6cf289146ee08c1c25746f7c94489a90f55d018eeeea21 SHA1: 23e7ffc52a15f9a88e364b8d11863926383e000c MD5sum: 6f19a5e8f11a02cfd5e58411abc191ae Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes: . - Map volumes to surface via PALS atlas - Multi-resolution morphing - Projection of foci via PALS atlas - Surface-based registration - Surface flattening . Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more information. Package: cde Version: 0.1+git9-g551e54d-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1015 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~nd+1_amd64.deb Size: 144634 SHA256: 1cf7c774c64fb1056d31b51ef40a2756c40c80e54938ca373d026b296897d0fb SHA1: 6b1285ce56dc1d49842b1ce0b3433303d3af1f98 MD5sum: 824ea887a1a7020923ffc738dc340eef 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: cgroup-bin Source: libcgroup Version: 0.37.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 162 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcgroup1 Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/cgroup-bin_0.37.1-1~nd+1_amd64.deb Size: 66080 SHA256: c2bf1309139d9c0002ef411c1e02edcc9e944babddcbb54babe84178be12c84d SHA1: 2e40ba785e3fd24c20a7a7f7260168b7fc49c4b0 MD5sum: fc6a514ef97967b2231a5a98249054f8 Description: Tools to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . These tools help manipulate, control, administrate and monitor control groups and the associated controllers. Package: cmtk Version: 3.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 26444 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk8, libfftw3-double3, libgcc1 (>= 1:3.0), libgomp1 (>= 4.9), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_3.3.1-1~nd+1_amd64.deb Size: 3695838 SHA256: 19f843e1d405b53955f7a7ea893aeab814d7936a7d55402b8a480e802d2901d5 SHA1: 00cb4ecc383f0519002fd23781615906375a0f89 MD5sum: 45bf8ee440af8431b28cae4e8f8eef10 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cmtk-dbgsym Source: cmtk Version: 3.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11754 Depends: cmtk (= 3.3.1-1~nd+1) Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: debug Filename: pool/main/c/cmtk/cmtk-dbgsym_3.3.1-1~nd+1_amd64.deb Size: 1019064 SHA256: 0b73ae23edd368fc425abd9c2d7fad8fc064ce6856db6b52458624e575b50ad8 SHA1: 92199aaddd0cb68fefee21b34c42b001f138ab9e MD5sum: c3e39469db3f129837f9f55e9ae2ac3c Description: Debug symbols for cmtk Auto-Built-Package: debug-symbols Build-Ids: 01a58b939aba6f8137acf04eb33b0deb220351fc 036e2ed9ab8f4081e7d443d246c2a22ea71aa6ca 0a4f07f76aa85789b943e764f7aec1e55bd9fc1d 0c1f184ee192798514a27135f4d04f22493065ce 0e5ac6957359e1d1e30e226fb9224bea7a485a03 122a873bd52ebd7103b365183230af33391c781f 12fb49d354b2158774c52083089a0031522c1fd6 15393c05efabfcf0ab01c8e50c34cb519ff52cc7 17e30a44a81dd51fd99463b02f0231be95a6fb63 1aa380cf702d6340f9317f55adf143427926e4eb 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pool/main/c/cnrun/cnrun_1.1.14-1~nd+1_amd64.deb Size: 102168 SHA256: e073524ad4c9c8ec08b2521f0ba4fd80f2c06c78a229e8790a1b6d565f53de39 SHA1: 52da6b8dcf8d3abde03808462bb9a37ef7d22479 MD5sum: 5fd58d63cd6780097732244f36b41b3d Description: NeuroML-capable neuronal network simulator CNrun is a neuronal network model simulator, similar in purpose to NEURON except that individual neurons are not compartmentalised. It can read NeuroML files (e.g., as generated by neuroConstruct); provides a Hodgkin-Huxley neuron (plus some varieties), a Rall and Alpha-Beta synapses, Poisson, Van der Pol, Colpitts oscillators and regular pulse generator; external inputs and logging state variables. Uses a 6-5 Runge-Kutta integration method. Basic scripting and (if run interactively) context-aware autocompletion. Package: cnrun-tools Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:3.0), libgomp1 (>= 4.2.1), libgsl2, libstdc++6 (>= 5.2), libxml2 (>= 2.6.27) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.1.0-1~nd+1_amd64.deb Size: 21818 SHA256: a82f55e4f22f7d4725838d6844de802c2c08ff1482501ffc276097f4ad9019ff SHA1: 6f2be0b59901f7a761af13db8ed52de16f82baf6 MD5sum: d021a95fe9df0d4b3a8bcebf617270c4 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: cnrun-tools-dbgsym Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 132 Depends: cnrun-tools (= 2.1.0-1~nd+1) Homepage: http://johnhommer.com/academic/code/cnrun Priority: extra Section: debug Filename: pool/main/c/cnrun/cnrun-tools-dbgsym_2.1.0-1~nd+1_amd64.deb Size: 104530 SHA256: 4976e8925cf02c2bf6d8f483e40efb3f524e2c562699ed04cae87050f6326dc0 SHA1: f731d869a0e227bd2591fbb0c25feb484a913186 MD5sum: 6d8439a19ac79bda6c5adc23bc746eac Description: Debug symbols for cnrun-tools Auto-Built-Package: debug-symbols Build-Ids: 5b2c33b964e20bd1a0ea59f24ad9665021c61368 ad3ab12a13734d07d7a6480367d97b09105e83b5 Package: condor Version: 8.4.9~dfsg.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.9~dfsg.1-2~nd+1_all.deb Size: 16196 SHA256: 0df170fb5cfeab10ad871bc3238b09a8d519b8f6d1cbcde8c62cf10f2b2b67ef SHA1: 1894f7b63cde9fcbdbecccde5d330c73d67e6dcb MD5sum: a83f38ecd6537a2e586cef6b133d5ea6 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". 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Package: condor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.9~dfsg.1-2~nd+1_all.deb Size: 16212 SHA256: 605c57b870e82b5345cffdb05d4a61ebc3abc4442b6b9b7450ebe3afbd9f83f1 SHA1: 60b965d995a858ceecc889b81ad4536d715151c4 MD5sum: c0f780575f44d50a6a79a557fedd89c8 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: 1.2.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51176 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:3.0), 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), 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_1.2.3-1~nd+1_amd64.deb Size: 24916474 SHA256: f8622413eb2c27bc63640be092eb64224377ad3631857db57a77e965646c2c0f SHA1: def450632a53f79d32536a332ee5b6b4c9bcc186 MD5sum: d602e7b0a94ee250113fd1f728afb8c0 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: 1.2.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 131693 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.2.3-1~nd+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.2.3-1~nd+1_amd64.deb Size: 129279634 SHA256: 27c090a0a242704c720c2f17d75feeb003d29ab9346d3d8782e3f9b557fd6576 SHA1: 40dc45ddcbe7c06ac86eb40400da1cf5f189e53a MD5sum: bf492e143058c76ca1d7344fa15f376d 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. Build-Ids: 2ee7d2dfaedfebb5e84f9ef100645cbb015c1075 ec824d6fc19466ea265ff6e2656815169955ae90 Package: connectomeviewer Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1578 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-cfflib (>= 2.0.5), python-networkx (>= 1.4), python-nibabel, python-numpy (>= 1.3.0), python-scipy, python-chaco, mayavi2 (>= 4.0.0), ipython Recommends: python-nipype, python-dipy, python-matplotlib, python-qscintilla2 Suggests: nipy-suite Homepage: http://www.connectomeviewer.org Priority: extra Section: python Filename: pool/main/c/connectomeviewer/connectomeviewer_2.1.0-1~nd+1_all.deb Size: 1356156 SHA256: 434aff9b028c4333df4aff71cc45e6b82a98574f6297ddab70d0ebc260ff5e6a SHA1: 5dc49f902c6d89fd0fea7758ce53c9462ec73db4 MD5sum: a9b946a201ad29742748d1c152b6fd57 Description: Interactive Analysis and Visualization for MR Connectomics The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics. . Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit. Package: coop-computing-tools Source: cctools Version: 3.4.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4143 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfuse2 (>= 2.8.1), libglobus-common0 (>= 14), libglobus-gss-assist3 (>= 8), libglobus-gssapi-gsi4 (>= 10), libkrb5-3 (>= 1.6.dfsg.2), libmysqlclient16 (>= 5.1.50-1), libncurses5 (>= 5.5-5~), libopenmpi1.3, libreadline6 (>= 6.0), libstdc++6 (>= 4.1.1), libtinfo5, python Suggests: coop-computing-tools-doc, condor, gridengine-client Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: utils Filename: pool/main/c/cctools/coop-computing-tools_3.4.2-1~nd+1_amd64.deb Size: 1385772 SHA256: 01f1bf972ab54cef91733140dbde1b1115284f528cc8d7c6d0395dfc8c7f38f8 SHA1: 268f3a1192eb9f4143a47f0ff495a78144d1fbf6 MD5sum: cbcf55a31fde50b2daa211aa5248dd3a Description: cooperative computing tools This is a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. This includes: . * Chirp: A personal filesystem and I/O protocol that allows unprivileged users to share space securely, efficiently, and conveniently. When combined with Parrot, Chirp allows users to create custom wide-area distributed filesystems. * Parrot: A transparent user-level virtual filesystem that allows any ordinary program to be attached to a remote storage device such as an FTP server or a Chirp server. * Makeflow: A workflow system for parallel and distributed computing that uses a language very similar to Make. * Work Queue: A system and API for building master-worker style programs that scale up to thousands of processors. * All Pairs: A computational abstraction for running very large Cartesian products. * Wavefront: A computational asbtraction for running very large dynamic programming problems. * The Fault Tolerant Shell: A high-level programming language that allows users to combine the ease of shell scripting, the power of distributed programming, and the precision of compiled languages. Basically, parallel programming and exception handling for scripts. Package: coop-computing-tools-dev Source: cctools Version: 3.4.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 956 Depends: neurodebian-popularity-contest Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: libs Filename: pool/main/c/cctools/coop-computing-tools-dev_3.4.2-1~nd+1_amd64.deb Size: 223104 SHA256: 9c70ef3ecc9c22a751cdef3771c3eb3f8f4125cdaaf5ea4e1368b25ce948179d SHA1: 02996c496e3c0071229bb75f999dc697060526bb MD5sum: af272ab8dd94941a181640eca10e31c5 Description: libraries and header files for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides static libraries and header files for development. Package: coop-computing-tools-doc Source: cctools Version: 3.4.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2319 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: doc Filename: pool/main/c/cctools/coop-computing-tools-doc_3.4.2-1~nd+1_all.deb Size: 310822 SHA256: 0642839d664eb82995250674899981ef923b580886bfee044c3d7fb0423d5c59 SHA1: ac36fb2e56a520976ccafeb3149cbb74e53a5783 MD5sum: 24357820bf176e53a7aafe81b73d5de2 Description: documentation for coop-computing-tools These tools are a collection of software that help users to share resources in a complex, heterogeneous, and unreliable computing environment. . This package provides the documentation (manual and API reference) in HTML format. Package: cython Version: 0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4924 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd+1_amd64.deb Size: 1331846 SHA256: 340cb1e470f0ab638c1749452199ae2f2516fac9a8152e5c5c8c15124e2fd662 SHA1: a348afb03c532dea466aab9a642a95188e3e222d MD5sum: 8dfc10b6cf44d65866b45a1880d617e1 Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10552 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3), cython (= 0.13-1~nd+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd+1_amd64.deb Size: 3422252 SHA256: 3a8617e19420cda0a3d5f6c4d52e5d4503fa1d1606355ddb7f9f8b2140fc2548 SHA1: 995dcdf86f109c46c013af8da69b15a78b6a7faf MD5sum: 6ddc22d8e8982d79f4c6d9df3fde309a Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.5, 2.6 Package: datalad Version: 0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.4-1~nd+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.4-1~nd+1_all.deb Size: 44616 SHA256: 82a9d97576b8d35a134333ebbbc53b439de829a179e9f4c26ae7331815c59121 SHA1: f7b1d3168c1048fa18a5ff867333596c33c3b41a MD5sum: c1c040c559b0ebdfc94c59965de89d72 Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package provides the command line tool. Install without Recommends if you need only core functionality. Package: dcm2niix Version: 20161101+git66-g672f4d2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 272 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_20161101+git66-g672f4d2-1~nd+1_amd64.deb Size: 115816 SHA256: ac3beb10bd9c4d2ef53fe6f668d9e1606e3d76305cb497a693d490cf80c243fa SHA1: 57f127ae0385910ed391c54bf643ab0f6c8f4a2e MD5sum: e950af6498eb3f5572b8c9a9e2b06d3a 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: dcm2niix-dbgsym Source: dcm2niix Version: 20161101+git66-g672f4d2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 278 Depends: dcm2niix (= 20161101+git66-g672f4d2-1~nd+1) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: extra Section: debug Filename: pool/main/d/dcm2niix/dcm2niix-dbgsym_20161101+git66-g672f4d2-1~nd+1_amd64.deb Size: 257042 SHA256: bf92fe4ff7e8aad7648980474194180a26adcb5defd651c972418596556704aa SHA1: e9c1ae14172031277640522c30980718e34a115b MD5sum: 33457127e6d33a26a182a2599ac12977 Description: Debug symbols for dcm2niix Auto-Built-Package: debug-symbols Build-Ids: fa0e52daf33b0f454895c8aa4c841c23af41e307 Package: debian-handbook Version: 6.0+20120509~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23215 Depends: neurodebian-popularity-contest Homepage: http://debian-handbook.info Priority: optional Section: doc Filename: pool/main/d/debian-handbook/debian-handbook_6.0+20120509~nd+1_all.deb Size: 21998670 SHA256: b33f038d8363175473cc056a5f98fc7af52386a466b45d4b2e42d2f25233a3ed SHA1: 7a0b369b4548a3f4fb61aa1ef9efa2ddf2b319e2 MD5sum: 3e3d2cf990fcc5ed1ed6bdbfb5c1c3dd Description: reference book for Debian users and system administrators Accessible to all, the Debian Administrator's Handbook teaches the essentials to anyone who wants to become an effective and independent Debian GNU/Linux administrator. . It covers all the topics that a competent Linux administrator should master, from the installation and the update of the system, up to the creation of packages and the compilation of the kernel, but also monitoring, backup and migration, without forgetting advanced topics like SELinux setup to secure services, automated installations, or virtualization with Xen, KVM or LXC. . The Debian Administrator's Handbook has been written by two Debian developers — Raphaël Hertzog and Roland Mas. . This package contains the English book covering Debian 6.0 “Squeeze”. Package: debruijn Version: 1.6-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfftw3-3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd+1_amd64.deb Size: 47848 SHA256: 71a8b562764b4bd8af95fd48462f1a57ada1c6205bde6b229ae57cb95580f0ce SHA1: 8a8a0b3896e1a50950e2ca2948a14b4a45ae2ff4 MD5sum: e484b2892411baa709b340dea84b5be4 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: dh-systemd Source: init-system-helpers Version: 1.18~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, perl, debhelper Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/dh-systemd_1.18~nd+1_all.deb Size: 13820 SHA256: 5c6c86d4863c6322a9e6512918f65d3621106a79bb50d159df73068dc4f82efb SHA1: 99fb38f6bfb0c38a01dd2e304f1c32ffbe0c0b2b MD5sum: 7a19fa0768f1c1d627df931054cb945b Description: debhelper add-on to handle systemd unit files dh-systemd provides a debhelper sequence addon named 'systemd' and the dh_systemd_enable/dh_systemd_start commands. . The dh_systemd_enable command adds the appropriate code to the postinst, prerm and postrm maint scripts to properly enable/disable systemd service files. The dh_systemd_start command deals with start/stop/restart on upgrades for systemd-only service files. Package: dicomnifti Version: 2.32.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 518 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.9) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.32.1-1~nd+1_amd64.deb Size: 96200 SHA256: 33b35d56de33aafcbd4dbc2f0b01f4afbeced59b2dc6bdee8a7bb24c3da0a002 SHA1: 37494494cf51060d3e9717981a409260f0737cf7 MD5sum: d30d75022bca197d47d678d0f1bab58a Description: converts DICOM files into the NIfTI format The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer. . dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files. Package: dmtcp Version: 2.3.1-6~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2711 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: utils Filename: pool/main/d/dmtcp/dmtcp_2.3.1-6~nd+1_amd64.deb Size: 663398 SHA256: 54a35614b21559a652b0f61ddad0a6c403a420e1680d22b833f562a41b380682 SHA1: 95968a10f6ab8b8d023c66855276d1f4bcff4fe3 MD5sum: 1f4fddbe77f18be8d44095f042f7d969 Description: Checkpoint/Restart functionality for Linux processes DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains DMTCP binaries. Package: dmtcp-dbg Source: dmtcp Version: 2.3.1-6~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 26290 Depends: neurodebian-popularity-contest, dmtcp Homepage: http://dmtcp.sourceforge.net Priority: extra Section: debug Filename: pool/main/d/dmtcp/dmtcp-dbg_2.3.1-6~nd+1_amd64.deb Size: 4430034 SHA256: f65f2d784641940745e2499e7a27c9cfa2041970c8a8b348fdfe794dccc3c07f SHA1: fb12166741d48d46749cd6d201d7d8434f07746f MD5sum: 0ebe94242eb601adc6d011626b1e9d93 Description: Debug package for dmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are Open MPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package contains debugging symbols for DMTCP. Package: docker-compose Version: 1.5.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 278 Depends: neurodebian-popularity-contest, python-docker (>= 1.3.0), python-dockerpty (>= 0.3.4), python-docopt, python-enum34 (>= 1.0.4), python-jsonschema, python-requests (>= 2.6.1), python-six (>= 1.3.0), python-texttable, python-websocket, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: docker.io (>= 1.6.0) Homepage: http://docs.docker.com/compose/ Priority: optional Section: admin Filename: pool/main/d/docker-compose/docker-compose_1.5.2-1~nd+1_all.deb Size: 87420 SHA256: 8e1c046f74ca70d5335a5700e0349e295a7d29c4f9519ecff6f3503bec8ce2d8 SHA1: 60b4209fd79c7a44d8fc80b65b80d6465e9d763f MD5sum: 746a3e0890d396e0a4f5cb21b58c1c2e Description: Punctual, lightweight development environments using Docker docker-compose is a service management software built on top of docker. Define your services and their relationships in a simple YAML file, and let compose handle the rest. Package: edac-utils Version: 0.18-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libedac1, lsb-base (>= 3.0-6) Recommends: dmidecode Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: admin Filename: pool/main/e/edac-utils/edac-utils_0.18-1~nd+1_amd64.deb Size: 29388 SHA256: 35eaab5a6f6e60bc8658584ce1e371bff4ccd5d4c2d187629c921d42fafe52c4 SHA1: 2219157a47614641e0a6df9f4f7be4551a355c24 MD5sum: faf7a1b943b080c0e7ec732e8d08723a Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package provides command lines tools Package: eegdev-plugins-free Source: eegdev Version: 0.2-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 83 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd+1), libc6 (>= 2.3.4), libexpat1 (>= 2.0.1), libusb-1.0-0 (>= 2:1.0.8), libxdffileio0 (>= 0.0) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/eegdev-plugins-free_0.2-3~nd+1_amd64.deb Size: 29120 SHA256: 677b5097f03a868fb8c6e5c8c814ab76de49bfa2b694755437f4e2a8468e8835 SHA1: 7ad475e313c7375173931fee058678da6b2a0da8 MD5sum: 915ec3b1a6c6686bd019ad250623b28f Description: Biosignal acquisition device library (free plugins) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the devices plugins that depends only on free components. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1_all.deb Size: 7224686 SHA256: 54ff518513962d0d5f50f6194edc9210fd1280ccb3dd2d277aee94711522513f SHA1: 0f8e5ec99bfea7724ce386136c4733c175063e78 MD5sum: 489d2beaf9e6e7e581abbfb6cebbef44 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: eegview Version: 0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libeegdev0, libmcpanel0 (>= 0.0), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegview.html Priority: extra Section: science Filename: pool/main/e/eegview/eegview_0.0-1~nd+1_amd64.deb Size: 13088 SHA256: 2858efcd056e22e60a51a184a8e3993ceff5bea3feb9dd6324e1b2a6a7a5f501 SHA1: c579ac3eba1dce8e39171383f17cff3a7f27aab8 MD5sum: 2872a1f589a8380a0270c45fcece6b2b Description: Software to display EEG data in realtime This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment. Package: environment-modules Source: modules Version: 3.2.10-8~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 185 Depends: neurodebian-popularity-contest, debhelper (>= 9), tcl8.6 (>= 8.6.0), libc6 (>= 2.14) Homepage: http://modules.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/m/modules/environment-modules_3.2.10-8~nd+1_amd64.deb Size: 92436 SHA256: f015ede1558ed9791c5ba5173613d808b10cbad79d5a0b5823a20ce25e47fbaa SHA1: b75d1000daabaf8e66ea4eb5ab729ca34b894cb1 MD5sum: 19b7f7a5f6f05ab0403bbce2c3581e6b Description: Modular system for handling environment variables The Modules package provides for the dynamic modification of a user's environment via modulefiles. Each modulefile contains the information needed to configure the shell for an application. Once the Modules package is initialized, the environment can be modified dynamically on a per-module basis using the module command which interprets modulefiles. Typically modulefiles instruct the module command to alter or set shell environment variables such as PATH, MANPATH, etc. modulefiles may be shared by many users on a system and users may have their own collection to supplement or replace the shared modulefiles. The modules environment is common on SGI/Crays and many workstation farms. Package: fail2ban Version: 0.9.6-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1290 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), init-system-helpers (>= 1.18~), lsb-base (>= 2.0-7) Recommends: python, iptables, whois, python3-pyinotify, python3-systemd Suggests: mailx, system-log-daemon, monit Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.6-1~nd+1_all.deb Size: 287494 SHA256: f104e13fbfa3b1d8e49e13621af856348cfee7a4a97bcf997e081730de705035 SHA1: 8847df6ae06253701955925306cb77eaae44f307 MD5sum: bcafc7f5e8f822ad4f242c26d14bc48b Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: freeipmi Version: 1.4.9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd+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~nd+1_all.deb Size: 1166 SHA256: 7dda9d1542d1494e9a7fee60f42db2b304fd486139b040580e1719fcc4f3a72e SHA1: 4992038df8faf051041e20e9509db82a264606c5 MD5sum: 0627a974c392edde19e7e09ff3454195 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), libgcrypt20 (>= 1.6.0), freeipmi-common (= 1.4.9-1~nd+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~nd+1_amd64.deb Size: 44794 SHA256: a0121b484aad031e0aac3197193e7b225c037acc69ecf091e56c874250893178 SHA1: 9a2476207516d1b84da8a73e117c2c8e76d499ae MD5sum: 6aa119cda279dbb79c05c8acea14082f 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 490 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~nd+1_all.deb Size: 339368 SHA256: 630feacdcc5462e2cb14ec9cc1ab0df88ed40258cec8fc465d00ca2b35195650 SHA1: 37a7e8b5ad9ebb187cfa538fde4bc36977682a8b MD5sum: 461e09f72e0e80921f61d0d42aaae393 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 134 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.1.5), libgcrypt20 (>= 1.6.0), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd+1_amd64.deb Size: 37738 SHA256: afbcc385b28ad260fa3b73740f1cad7607e9091bec0565c384d9a7ad06b5a3cb SHA1: 8673ce2a79b181ec9312e0eb4d05a57cd84063a4 MD5sum: ec5f59197a9ee5eac3628528a4119f2f 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 210 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), libgcrypt20 (>= 1.6.0), freeipmi-common (= 1.4.9-1~nd+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~nd+1_amd64.deb Size: 79044 SHA256: ba21f7723190c8e31bcaaed22a266a558287f8c578d661e6edaaa6ca99a585cd SHA1: da8b0efe91037517a4f2133a029b7679c8d45d52 MD5sum: 7c6e5603fa4d7087edfc1cb3eceb85d6 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2887 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.9-1~nd+1), libgcrypt20 (>= 1.6.0), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd+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~nd+1_amd64.deb Size: 600724 SHA256: 129d804116212206358ea756ccedf0897a2f1abf63b7b9ab18fc0fc76683e179 SHA1: 456136e6b26a9d1d4c2fe988dbeea12067167227 MD5sum: 2f45828553534e4c809fbf216c648592 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 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_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 8484 SHA256: 83db9498b018ffe1a8edba6e87d6f2915ddfbf0a10fe668f067f354fd26ef1e2 SHA1: 9e7f6524aabba55760ee4cbfcf3e38907ab1cb27 MD5sum: e57c5a99cb4054440b7dda0d18ed4ac4 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~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 74 Depends: neurodebian-popularity-contest, python, python-matplotlib, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-nibabel, 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~nd+1_all.deb Size: 13894 SHA256: 9756e4fb5df49c082874797043964c50688944e09807b3c2e3ae5f8ef57a29fc SHA1: c8188453f7a785172e154a3ed522bd45758a23b6 MD5sum: 810ba8a6c4ee3c0548200411b906c2a2 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: fslview Version: 4.0.1-6~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6739 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.0), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 5.2), libvtk5.10, libvtk5.10-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-6~nd+1_amd64.deb Size: 1350344 SHA256: c8cf6977278aa2ceb3d4d8a25c4598b76dc82114b6d3e9c9f95a0e7c5cc7a8c5 SHA1: 7f26047d6803b01c0c85b12bd6d8b43e0497d7f3 MD5sum: a72954acd2a6c27085a8119c156bccca Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-dbgsym Source: fslview Version: 4.0.1-6~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7777 Depends: fslview (= 4.0.1-6~nd+1) Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: extra Section: debug Filename: pool/main/f/fslview/fslview-dbgsym_4.0.1-6~nd+1_amd64.deb Size: 6804864 SHA256: 806f19aa8909586bc000386a40629f1f00d204c075ecf188d1a22b15a53d3ed3 SHA1: 27eef7300a7e4f1b1f2b05d3a272f18ca3e21588 MD5sum: 000616f7d0ca514cf538e7d83550b8e9 Description: Debug symbols for fslview Auto-Built-Package: debug-symbols Build-Ids: 08118a0534dcb3bd6d2bb7b4d0ec15ff6b2b12d9 5dbabbaddd1ee386d6afd27847cf4af5c733ac91 Package: fslview-doc Source: fslview Version: 4.0.1-6~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2930 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-6~nd+1_all.deb Size: 2227654 SHA256: 76b56902c93037a6b1047c3e407923921380d785c518c9fb3578b298e9bf571e SHA1: 230f1be25b2d41fb8a1b741677ba1af77a3fcfe2 MD5sum: fdd711020a889d9831643710482d3d31 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1766 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_3.4.0-1~nd+1_all.deb Size: 1669934 SHA256: a942c1135cb5ea2389e82adeeeddd0c6d52dbb92a9d5ec5b6fbd38dc344a85e8 SHA1: 5e465d9f3df150aa6315f64305a6fc8066123b0d MD5sum: f3d53c3e565d66af9033c8eb536f27b0 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: gdf-tools Source: libgdf Version: 0.1.2-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 183 Depends: neurodebian-popularity-contest, libboost-filesystem1.49.0 (>= 1.49.0-1), libboost-program-options1.49.0 (>= 1.49.0-1), libboost-system1.49.0 (>= 1.49.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.2-2~nd+1_amd64.deb Size: 55792 SHA256: 4ec7f41d0f5c7f9554a8907ac6a147eb6206cf18ff54999e65bcf773d52e4a76 SHA1: a6724577836330c0d6cc59ff4780ea3af5fe29e1 MD5sum: a0ad31b0d6f1bf3862dabf1da13b3e39 Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: git-annex Version: 5.20150327+git27-g6af24b6-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 55475 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libffi6 (>= 3.0.4), libgmp10, libgnutls-deb0-28 (>= 3.3.0), libgsasl7 (>= 1.4), libicu52 (>= 52~m1-1~), libidn11 (>= 1.13), libsqlite3-0 (>= 3.5.9), libxml2 (>= 2.7.4), libyaml-0-2, zlib1g (>= 1:1.1.4), git (>= 1:2.0), rsync, wget, curl, openssh-client (>= 1:5.6p1) Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2, bittornado | bittorrent Suggests: graphviz, bup, tahoe-lafs, libnss-mdns Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex_5.20150327+git27-g6af24b6-1~nd+1_amd64.deb Size: 8433438 SHA256: 7b055a8e4ae9f1e6f59b07443e8daedc3ec871f803170dd927a1dc9cfaa19ce6 SHA1: c9af4e8f9d7ad877605441c21a67abbb042652a0 MD5sum: 77bbe55d4b6721054274e3027c293975 Description: manage files with git, without checking their contents into git 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. Package: git-annex-standalone Source: git-annex Version: 6.20170101+gitg93d69b1-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 162339 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, tor, magic-wormhole, 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_6.20170101+gitg93d69b1-1~ndall+1_amd64.deb Size: 34155056 SHA256: 731e8d39316df3165af36db7023e6e8b6c7346c4acfe616450b3afe1e56189af SHA1: a24372a9b71c09fa954704ab295fb1170276c386 MD5sum: a2785f8e037f927fd24b59c1975ba114 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: 6.20160126+gitg65f4442-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 45 Depends: git-annex-standalone (= 6.20160126+gitg65f4442-1~ndall+1) Homepage: http://git-annex.branchable.com/ Priority: extra Section: debug Filename: pool/main/g/git-annex/git-annex-standalone-dbgsym_6.20160126+gitg65f4442-1~ndall+1_amd64.deb Size: 9076 SHA256: df13c8d6accff21cae1128fda8e3626634b54097765c744bda4d814a294a4754 SHA1: bf65febb9152d0ab4b069d9ef9ca4b44fc3ea7fa MD5sum: dc4d8ce99c459c96dd4f4a6d010e02ca Description: Debug symbols for git-annex-standalone Auto-Built-Package: debug-symbols Build-Ids: 75d11a3ee55319e6cebcf33286de8df9a39bcaea 75d11a3ee55319e6cebcf33286de8df9a39bcaea Package: git-hub Version: 0.10.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Depends: neurodebian-popularity-contest, python, git (>= 1:1.7.7) Homepage: https://github.com/sociomantic/git-hub Priority: optional Section: vcs Filename: pool/main/g/git-hub/git-hub_0.10.3-1~nd+1_all.deb Size: 34098 SHA256: 8040a3bcf2b0edb26f64479ad263802c54abaa84c5c634916bac6cc38d0f0b86 SHA1: fa08d17ce7635fb46ae42ae7a828a421253be7b3 MD5sum: a5f8f25a39285cdb58716bbb34332c85 Description: Git command line interface to GitHub git hub is a simple command line interface to GitHub, enabling most useful GitHub tasks (like creating and listing pull request or issues) to be accessed directly through the Git command line. . Although probably the most outstanding feature (and the one that motivated the creation of this tool) is the pull rebase command, which is the rebasing version of the GitHub Merge (TM) button. This enables an easy workflow that doesn't involve thousands of merges which makes the repository history unreadable. . Another unique feature is the ability to transform an issue into a pull request by attaching commits to it (this is something offered by the GitHub API but not by the web interface). Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 426 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd+1), libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 Replaces: libglew1.6 (<< 1.7) Homepage: http://glew.sourceforge.net Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.9.0-3~bnd1~nd+1_amd64.deb Size: 135524 SHA256: d4039f12618a30494fd0b6d7c94d4135faf62f6aa87e208d7e365704c9ece03b SHA1: 29dcba8fcdd979e12823a4a184c3e0beeda19d1c MD5sum: 686e42921049db250110df3f3022c68a Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the utilities which can be used to query the supported OpenGL extensions. Package: gmsl Version: 1.1.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd+1_all.deb Size: 13860 SHA256: d5e113a0261e40edce8fb498d2bb7852c648002247fffdff0452381a4b2ecdef SHA1: 11595f3dcf608a93147968af5da25409ce67f80e MD5sum: 1f3da7118ebb92d891e0eca8f578fe12 Description: extra functions to extend functionality of GNU Makefiles The GNU Make Standard Library (GMSL) is a collection of functions implemented using native GNU Make functionality that provide list and string manipulation, integer arithmetic, associative arrays, stacks, and debugging facilities. . Note that despite the name of this project, this library is NOT standard and is NOT written or distributed by the GNU project. Package: guacamole Source: guacamole-client Version: 0.8.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 476 Depends: neurodebian-popularity-contest, guacd Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole_0.8.3-1~nd+1_all.deb Size: 426802 SHA256: 30425f953711295f9fd13c922f1f6cdfb967eae6d2b35805872681de6cab0984 SHA1: 10dc2e2a857d30f9a48b314928809fa24c950efb MD5sum: 146eaa1ce187ce8df480c722af1b3657 Description: HTML5 web application for accessing remote desktops Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. Package: guacamole-tomcat Source: guacamole-client Version: 0.8.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-client/guacamole-tomcat_0.8.3-1~nd+1_all.deb Size: 6738 SHA256: 35e27bb61847fd126702dfd459303228bb781ce180fa78b663d7263479f5b2a6 SHA1: 97eec3f03694256ce8d38f1ae5db05b2e6de793a MD5sum: abb7483920ef5ea1c5619fd31786a892 Description: Tomcat-based Guacamole install with VNC support Guacamole is an HTML5 web application that provides access to a desktop environment using remote desktop protocols. A centralized server acts as a tunnel and proxy, allowing access to multiple desktops through a web browser. No plugins are needed: the client requires nothing more than a web browser supporting HTML5 and AJAX. . This metapackage depends on Tomcat, Guacamole, and the VNC support plugin for guacamole. Guacamole is automatically installed and configured under Tomcat. Package: guacd Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 34 Depends: neurodebian-popularity-contest, lsb-base (>= 3.0-6), libc6 (>= 2.15), libguac5, libssl1.0.0 (>= 1.0.0) Homepage: http://guac-dev.org/ Priority: extra Section: net Filename: pool/main/g/guacamole-server/guacd_0.8.3-1~nd+1_amd64.deb Size: 13992 SHA256: 87ec2fb0f2321678d85139b4eeaed3c6f10a27822fdf97661fe9a36ca213d4fd SHA1: 3a8c4d7e3670640653a98a75eb15dfb45eb0e6c6 MD5sum: 061310bad42d90c2bff2db649215bbb0 Description: Guacamole proxy daemon The Guacamole proxy daemon, guacd, translates between remote desktop protocols (like VNC) and the Guacamole protocol using protocol plugins. Once a user is authenticated with the Guacamole web application, a tunnel is established through the web application to guacd, allowing the JavaScript client to communicate to an arbitrary remote desktop server through guacd. Package: heudiconv Version: 0.1-1~nd+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~nd+1_all.deb Size: 10206 SHA256: 7f58fdc3a1e6742dd76a6ff2da6fdc6f6afe5203a2fa45544715ecbf8ccb0796 SHA1: a3f880cc7c86f3d90c0ca41428ce8bf7dd55fd24 MD5sum: 866bc0ecbf19c7a266f312fcd9aac8db 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: 8.4.9~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 12950 Depends: neurodebian-popularity-contest, adduser, debconf (>= 0.5) | debconf-2.0, libdate-manip-perl, python, libclassad7 (= 8.4.9~dfsg.1-2~nd+1), perl:any, libc6 (>= 2.15), libcgroup1 (>= 0.37.1), libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:3.0), libglobus-callout0 (>= 3), libglobus-common0 (>= 16), 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 (>= 8), 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), libgsoap10, 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 (>= 2.4.6), libpcre3, libssl1.0.2 (>= 1.0.2d), libstdc++6 (>= 5.2), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), 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_8.4.9~dfsg.1-2~nd+1_amd64.deb Size: 3660648 SHA256: 73a16f024fa645bd9e443710cc9e8b657fe203da78edba38d5f1f52bd5b666f7 SHA1: 527f8da1f23de202c47e1352e27020003cdd015f MD5sum: 7c833a85cacd87aceecc22766a16df95 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: 8.4.9~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 37320 Depends: neurodebian-popularity-contest, htcondor (= 8.4.9~dfsg.1-2~nd+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_8.4.9~dfsg.1-2~nd+1_amd64.deb Size: 35430760 SHA256: 6df47211cf723cb126cb8cd9cf92742169c17552463d4f20f13d0d3810f282e4 SHA1: a4cf70e4811b03bf630c315a4190f2b81114d42c MD5sum: 13014ca75ccd88a9f5da59b2ba35cf54 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. 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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: 8.4.9~dfsg.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 6120 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_8.4.9~dfsg.1-2~nd+1_all.deb Size: 1066620 SHA256: 55dc5961bd5648362a13d2431f210b729c50bf943db110e3101a66321d44fe1f SHA1: 65fabc7bfa4fa14faa3ae8f09d7d26ef01b28b3e MD5sum: a96409da9a66d6f3490983ac7333db74 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~nd+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~nd+1_all.deb Size: 175634 SHA256: aa6b3094a51db5f60c086659775a5dd4f1bdb1b3efc3e6cfb7b2a8a8eaf55505 SHA1: 80326f67f2bf666891aeafd556ee40cbfb5f0d1f MD5sum: 2e373cb2275ad290ace5b30382a3c4bb 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: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd+1_all.deb Size: 9644 SHA256: 0d13ef08a008124bb9da089c6b0ee0b6786334ccc1f455d0fbf23dc513dd40df SHA1: bc8cb6cadf98cc14994f98441238f49353e3a04c MD5sum: 4ea2b3f0bbadd9c29c191cb08ac94709 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: init-system-helpers Version: 1.18~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, perl Breaks: systemd (<< 44-12) Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/init-system-helpers_1.18~nd+1_all.deb Size: 13476 SHA256: d19f7f7a8cc30eebf191c3e5ad052e7bed02fdc1193cd7d909b96fcb70fb0a92 SHA1: 030b394a1bb44ed637be9f28365d434d5b7b76b9 MD5sum: 1082547d50241a858f76eaea6a830965 Description: helper tools for all init systems This package contains helper tools that are necessary for switching between the various init systems that Debian contains (e.g. sysvinit, upstart, systemd). An example is deb-systemd-helper, a script that enables systemd unit files without depending on a running systemd. . While this package is maintained by pkg-systemd-maintainers, it is NOT specific to systemd at all. Maintainers of other init systems are welcome to include their helpers in this package. Package: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.7.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2836 Depends: neurodebian-popularity-contest Suggests: libinsighttoolkit4-dev Conflicts: insighttoolkit-examples Replaces: insighttoolkit-examples Homepage: http://www.itk.org/ Priority: optional Section: devel Filename: pool/main/i/insighttoolkit4/insighttoolkit4-examples_4.7.0-1~nd+1_all.deb Size: 2500548 SHA256: 0531b48d93ec829a52e19ef69ade463eb0d13b9b1d738db0d3b56ba6773293a6 SHA1: 1827fac02b3ef405aff4374a4cb2563a9c0dca06 MD5sum: ed36ba29f41f8508c077ae627f0bcfa9 Description: Image processing toolkit for registration and segmentation - examples ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the source for example programs. Package: insighttoolkit4-python Source: insighttoolkit4 Version: 4.7.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 878785 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfftw3-double3, libfftw3-single3, libgcc1 (>= 1:4.1.1), libgdcm2.4, libinsighttoolkit4.7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.9) Conflicts: insighttoolkit-python Replaces: insighttoolkit-python Homepage: http://www.itk.org/ Priority: optional Section: python Filename: pool/main/i/insighttoolkit4/insighttoolkit4-python_4.7.0-1~nd+1_amd64.deb Size: 74558304 SHA256: 7881b396a118d0c4a03811cc482a38c0be7a38d86b496ce983a638af6142b792 SHA1: 4172f38840f7dc079d0b6ef0ea9c667395f28730 MD5sum: 8bdcea30c24f42c96c629b2c398ca986 Description: Image processing toolkit for registration and segmentation - Python bindings ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the Python bindings. Package: ipython01x Version: 0.13.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4808 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.6.6-7~), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython01x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.13.2-1~nd+1_all.deb Size: 1306542 SHA256: 33fc418d5aa20d8ed5764ba27113cf8b7dfd6e161f925ce1b3bf179bf11fb31c SHA1: 39a91cecc912b7b453902b3746d62849a55e0b52 MD5sum: 9f74e872ca8b460a4350a340d804f98b Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.13.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16672 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.13.2-1~nd+1_all.deb Size: 7241256 SHA256: a0d2235483d3300b6213c473d783db7e62487249a9bed0d418dbad6d44693be8 SHA1: 947c3033758d7974461bd0758e0d765af1750dc6 MD5sum: c52d4bb47c6d7375400b74e24c2f9fd8 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-notebook Source: ipython01x Version: 0.13.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-notebook_0.13.2-1~nd+1_all.deb Size: 900 SHA256: 610ebc3a7bcc05bd450b367852ab26dad5c2f8b668e000fc73880a07cdffda2f SHA1: c722a2a679e2931d56dc828366f160165f16d9d0 MD5sum: 9e7976ee869362eaa11884d2e1ff00c0 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython01x-parallel Source: ipython01x Version: 0.13.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython01x/ipython01x-parallel_0.13.2-1~nd+1_all.deb Size: 828 SHA256: 1f0ce5d07095b2529a2f935f8715d834215d6c4f016179fc33ba6b11dd5855f7 SHA1: e2194703b6e2426cbb732cc34070157910c6c0ca MD5sum: fe3fa702999665bd8751b4daf6afb0d2 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython01x-qtconsole Source: ipython01x Version: 0.13.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.13.2-1~nd+1_all.deb Size: 914 SHA256: ed093f1f0751c34cedd9910b094deecb52e3a7d8865119c5de7d47996acdea7b SHA1: 4aebbc9ff1ce980725e419f8754294d3ea472dc6 MD5sum: 96a49d95cc8ce5bff8422fb5d3f378ba Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11748 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython1x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython1x/ipython1x_1.1.0+git7-gf5891e9-1~nd+1_all.deb Size: 3842882 SHA256: 7c1441bc77ba7c7fd3bdbe815f7c7f7f6463fa9ef0313a9e93609cdfe179dd8c SHA1: 4caf2b8e43102cc073fa5d48befbdea5f0bd2f59 MD5sum: 47491a39015e2f209b730ad0cb5ada5d Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-doc Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10389 Depends: neurodebian-popularity-contest, libjs-jquery, ipython1x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython1x/ipython1x-doc_1.1.0+git7-gf5891e9-1~nd+1_all.deb Size: 3694410 SHA256: 791e5bf6963a169984fc99ea7876edcf8ee4d9d395d324c12dda2aef4f0a602a SHA1: 94c9c4fed79527354a553fd0e0a794eb18c92ae6 MD5sum: 4a3eea4d61a721ca8acfda4d8c57ef61 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-notebook Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-notebook_1.1.0+git7-gf5891e9-1~nd+1_all.deb Size: 962 SHA256: fe4b4c9a3c3c0f4a0a6fea5b8988cfdf1116d52d69e2c1a0fee034193a621b73 SHA1: 7fff71aa3955c95a06d37dc68325299f9d5304ef MD5sum: cd9e1c312a5b0daaa52b9744d53c19d0 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x-parallel Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython1x/ipython1x-parallel_1.1.0+git7-gf5891e9-1~nd+1_all.deb Size: 888 SHA256: b92af7fb89a64885bac32001ff8af087e44e8b5b7d2ff631255d786fe8a80d01 SHA1: aaa3c95e540ffc04b95c335b8059fa1d82c1da4f MD5sum: 8ffb02a51001d8c55e7f68aad8820104 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython1x-qtconsole Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-qtconsole_1.1.0+git7-gf5891e9-1~nd+1_all.deb Size: 972 SHA256: 899ea9da63a3f655e738b2853dc87c805ce75a92303b2f1baf93e31c9aa5d743 SHA1: b8d030862023fbf54da8e753ce0b86d306982254 MD5sum: 6db341ac45a0e710a04f62bd052e45c6 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: ipython2x Version: 2.0.0+git8-gee204ae-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12337 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7), python (<< 2.8) Recommends: python-tornado (>= 3.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib, environment-modules Suggests: ipython2x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython2x/ipython2x_2.0.0+git8-gee204ae-1~nd+1_all.deb Size: 5617136 SHA256: 8bd356916406ac6cd32400a0f84f7c961c575e597f1cb27359d8fc3557311155 SHA1: f8ff90471d165b6b6f5364285f5943c8c56b8112 MD5sum: d3ea479e159c72a987a2fcb370b51985 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython 2.x seres with all fresh goodness from the IPython team. It provides IPython2X module thus not conflicting with system-wide installed IPython Package: ipython2x-doc Source: ipython2x Version: 2.0.0+git8-gee204ae-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12949 Depends: neurodebian-popularity-contest, libjs-jquery, ipython2x (= 2.0.0+git8-gee204ae-1~nd+1) Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython2x/ipython2x-doc_2.0.0+git8-gee204ae-1~nd+1_all.deb Size: 4678124 SHA256: b5c017712653a30fa8a62aaa8601c3b9146f3c63184419ef17121da49c38e864 SHA1: 571824bad0b488d73fdc42eac1a4fe70bb10d9f6 MD5sum: 855a4ce18a4ed06cef96e0796756cdd6 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython 2.x. It provides IPython2X module thus not conflicting with system-wide installed IPython Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd+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~nd+1_all.deb Size: 5014 SHA256: 912f3638ef54d138a31d05609f4e92f791abe30ad5df28d5e39c45c8d55fb258 SHA1: 9868caa57e8404a539336933627057b221713c81 MD5sum: 10f20c9b72aefdbd2b0e54ab0cfd049c 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 419 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+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~nd+1_amd64.deb Size: 120918 SHA256: b73e78bdcd0c7ff4523a178ec2d6f977cd15a7a026fa564b8b345ee699d596d9 SHA1: dd046ffa31813fd2c4656f456ea6fa0eff460ddf MD5sum: 4bc39ca69e2a36404f01a92891b1e556 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: itksnap Version: 3.2.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 14511 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libgdcm2.4, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit4.6, libqt5core5a (>= 5.1.0), libqt5gui5 (>= 5.2.0), libqt5opengl5 (>= 5.0.2), libqt5qml5 (>= 5.0.2), libqt5widgets5 (>= 5.2.0), libstdc++6 (>= 4.9), libvtk6.1, zlib1g (>= 1:1.1.4) Homepage: http://www.itksnap.org Priority: optional Section: science Filename: pool/main/i/itksnap/itksnap_3.2.0-1~nd+1_amd64.deb Size: 3345058 SHA256: 2f77811f2217c056a7ada0fd75d1ff79a1093829a177a55dbbf8a91e2d5340f6 SHA1: de4ef069567bfc7f86073d1669ac229f48680bca MD5sum: 56c1538ab4b91ad4f3c808e95ef7764a Description: semi-automatic segmentation of structures in 3D images SNAP provides semi-automatic segmentation of structures in medical images (e.g. magnetic resonance images of the brain) using active contour methods, as well as manual delineation and image navigation. Noteworthy features are: . * Linked cursor for seamless 3D navigation * Manual segmentation in three orthogonal planes at once * Support for many different 3D image formats, including NIfTI * Support for concurrent, linked viewing and segmentation of multiple images * Limited support for color images (e.g., diffusion tensor maps) * 3D cut-plane tool for fast post-processing of segmentation results Package: jasp Version: 0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 7091 Depends: neurodebian-popularity-contest, libarchive13, libboost-filesystem1.61.0, libboost-system1.61.0, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libqt5core5a (>= 5.6.0~beta), libqt5gui5 (>= 5.2.0), libqt5network5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5svg5 (>= 5.6.0~beta), libqt5webkit5 (>= 5.6.0~rc), libqt5widgets5 (>= 5.6.0~beta), libstdc++6 (>= 5.2), libjs-marked, r-base-core, r-cran-afex, r-cran-bayesfactor, r-cran-car, r-cran-effects, r-cran-hypergeo, r-cran-lme4, r-cran-logspline Recommends: r-cran-ggplot2, r-cran-lsmeans, r-cran-plotrix, r-cran-rcpp, r-cran-rinside, r-cran-rjson, r-cran-vcd, r-cran-vcdextra Homepage: https://jasp-stats.org Priority: optional Section: science Filename: pool/main/j/jasp/jasp_0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd+1_amd64.deb Size: 3578872 SHA256: 52f92b038eaa047910008ab5d394980a45d0edde789726e8210a575fd5419d37 SHA1: 6c8e7755ef89a844e07162eea0e37abd407032be MD5sum: 0a519e1b7b8d7887d2102180561f55a8 Description: Bayesian statistics made accessible This is a statistics package with a graphical user interface. Its authors consider it "a low fat alternative to SPSS, a delicious alternative to R. Bayesian statistics made accessible." Package: jasp-dbgsym Source: jasp Version: 0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 44074 Depends: jasp (= 0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd+1) Homepage: https://jasp-stats.org Priority: extra Section: debug Filename: pool/main/j/jasp/jasp-dbgsym_0.8.0.0~beta2+git154-g375aad9~dfsg.1-1~nd+1_amd64.deb Size: 43915284 SHA256: 8b10d68c23279047507c4a6275d25f81a941e453ed27c5bcb6efc7b4a3349262 SHA1: 4fb720bd1b66924efe3c6d410213f2c7a9b6e627 MD5sum: 45d08bd97eec66f2b4e8ccfd02ced9e7 Description: Debug symbols for jasp Auto-Built-Package: debug-symbols Build-Ids: dccbe6e64884ced4e10c26826827ee9107078a89 ee0d6027068e1813841c19b44eaa200e5370b676 Package: klustakwik Version: 2.0.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://sourceforge.net/projects/klustakwik/ Priority: extra Section: science Filename: pool/main/k/klustakwik/klustakwik_2.0.1-1~nd+1_amd64.deb Size: 22928 SHA256: 63333a8de042aaeacb2ce74aae8157484e53b3ba1e9fbed278205a106e4b6841 SHA1: ea366e27b7a442539ac40d4e78662e92bfc86b42 MD5sum: 73cd3988d2ccaa81b7c213ba565b6194 Description: automatic sorting of the samples (spikes) into clusters KlustaKwik is a program for automatic clustering of continuous data into a mixture of Gaussians. The program was originally developed for sorting of neuronal action potentials, but can be applied to any sort of data. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1732 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd+1_amd64.deb Size: 300368 SHA256: b275e3b0f005183099bca8e46f14e2a2acad9d4e04b1db932d8e64cdbe021004 SHA1: 8fc6552280e51cfebba6d8970fe2fbe94013729b MD5sum: 99c1b9731b35884533020197fda3880b 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 911 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: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-2~nd+1_amd64.deb Size: 277316 SHA256: 9c045491ba576ba6a5ab5b034a9e70deb9d206347ee29b19bc939044bbd60ac8 SHA1: e3af55b9ed816e493a4a278f7f1f969c9804916d MD5sum: c4a8bbeb5a081c38fa12cf8e1dc38cac 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd+1_amd64.deb Size: 65440 SHA256: 0b2eb2f1bf3f0ff2d08aa8b47de024b5f4e7187560752b1091c637988efd9e48 SHA1: b8897578b3f6b6671f1da019fc95b3b7478a2fd8 MD5sum: 3bdf5d77c9ccb1708e3aa9e4c3441fe6 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: libcgroup-dev Source: libcgroup Version: 0.37.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libcgroup1 (= 0.37.1-1~nd+1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libdevel Filename: pool/main/libc/libcgroup/libcgroup-dev_0.37.1-1~nd+1_amd64.deb Size: 17396 SHA256: 52f355fe4c6d1c87d9b53ed25f434bafc9906faa3469e89537da42c406ef9564 SHA1: c99990c7998929defb496312cb3899dd79f97128 MD5sum: b45c34dae327e5a90c118ff1a1285196 Description: Development libraries to develop applications that utilize control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . It provides API to create/delete and modify cgroup nodes. It will also in the future allow creation of persistent configuration for control groups and provide scripts to manage that configuration. Package: libcgroup1 Source: libcgroup Version: 0.37.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, libc6 (>= 2.7) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: libs Filename: pool/main/libc/libcgroup/libcgroup1_0.37.1-1~nd+1_amd64.deb Size: 38574 SHA256: 0834b57e45f2c932c17cf3ff12ab40879cf52bf10a9e38473c73e09a99d2aad1 SHA1: 66f29ae37615f5c40b598f60762f81f0d0c8e401 MD5sum: cb31c3c38d3a9052289d2b139d19c53c Description: Library to control and monitor control groups Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This library allows applications to manipulate, control, administrate and monitor control groups and the associated controllers. Package: libclassad-dev Source: condor Version: 8.4.9~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1365 Depends: neurodebian-popularity-contest, libclassad7 (= 8.4.9~dfsg.1-2~nd+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_8.4.9~dfsg.1-2~nd+1_amd64.deb Size: 237068 SHA256: fc16e26ae09f1d88cd56cdd4c8f56d63183128cb7c8262454fe598e962775d11 SHA1: 5784ac0e4f4aa5d01ed61025c29db400aeb0949a MD5sum: 0ff213419e0ab995eecf63e43ffe1dab 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: libclassad3 Source: condor Version: 7.8.8~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 904 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/libclassad3_7.8.8~dfsg.1-2~nd+1_amd64.deb Size: 274840 SHA256: 530bb0a3cdba278b3a3b2a2177268787ce70641867023b3c0d9a6897ee5de19c SHA1: ff962737f7bedcc65a091d3e070249a618bf3d00 MD5sum: 5834ce476dfd1b6c78d94add43d71ccf Description: Condor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libclassad7 Source: condor Version: 8.4.9~dfsg.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 617 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libpcre3, libstdc++6 (>= 5.2) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: libs Filename: pool/main/c/condor/libclassad7_8.4.9~dfsg.1-2~nd+1_amd64.deb Size: 194248 SHA256: a4bbf362b8f311766cad3d9e28ad1fc52f32e6256068bb9517038f84a713edac SHA1: 34747626c052c52189a810236cdfcfa70ec586ff MD5sum: 121e68f33ea23ed919ab81d90e0ad39f 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: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 296 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgomp1 (>= 4.2.1), libgsl2, 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_2.1.0-1~nd+1_amd64.deb Size: 85696 SHA256: 2d93ab71d2ec27095948061ddfd79ed3fd0b4f7aefd5ff258afdb9d492721f00 SHA1: b76b9f9c2ef8baf635d283390d00b2d97543ed2f MD5sum: 1e9d0a47ee7bed93814feb5cd0dc0741 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-dbgsym Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 985 Depends: libcnrun2 (= 2.1.0-1~nd+1) Homepage: http://johnhommer.com/academic/code/cnrun Priority: extra Section: debug Filename: pool/main/c/cnrun/libcnrun2-dbgsym_2.1.0-1~nd+1_amd64.deb Size: 953324 SHA256: aec400a8baa5630c3eadb11c89ae14764720bb071fd84e4c7d50182a1a802b75 SHA1: 500f76d872113b6a47191980b17c2619e9224273 MD5sum: aad487070a7bf4b7a4148a3965978ec0 Description: Debug symbols for libcnrun2 Auto-Built-Package: debug-symbols Build-Ids: c5e84d0097b9955381d011263f1588ebf8c0f304 Package: libcnrun2-dev Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 141 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.1.0-1~nd+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.1.0-1~nd+1_amd64.deb Size: 25236 SHA256: 9de2fb21856a3d0c8f0a7825d3b6f77d4a0f8b80d3fc838a81698615d002d1f0 SHA1: 58f09a265f4f65f3e3451e92502abe3baba32c99 MD5sum: 485cfbde82267891dbbc58c194e961a1 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: libdmtcpaware-dev Source: dmtcp Version: 1.2.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16 Depends: neurodebian-popularity-contest, libdmtcpaware1 (= 1.2.5-1~nd+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libdmtcpaware-dev_1.2.5-1~nd+1_amd64.deb Size: 7094 SHA256: 2492fc524563812a909d4928dd2f355b9265e467c5169873a7f4610235844fd1 SHA1: c2e9ea52fa37c65ac821ecafac290bd5959301a0 MD5sum: 40c56ae1334e348bdc8aacf9d06efb21 Description: DMTCP programming interface -- developer package DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides libraries for developing applications that need to interact with dmtcp. Package: libdmtcpaware1 Source: dmtcp Version: 1.2.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, dmtcp, libc6 (>= 2.2.5) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libdmtcpaware1_1.2.5-1~nd+1_amd64.deb Size: 7230 SHA256: 1af77d4d08a41e77075c1d44b22051af9f47df51c792776b728e9298f48061fe SHA1: 2e1f1202ae298ef980e5af1ad9c0f4aeb24a31f1 MD5sum: d9f1251c83b35a7d771a2aaf3beb3075 Description: DMTCP programming interface DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides a programming interface to allow checkpointed applications to interact with dmtcp. Package: libdouble-conversion-dbg Source: double-conversion Version: 2.0.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd+1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: debug Filename: pool/main/d/double-conversion/libdouble-conversion-dbg_2.0.1-1~nd+1_amd64.deb Size: 101832 SHA256: 1a6509988d49b2e919e506725b9e6c05f8b7c58b7697c7dfb51ea8fd89f1af89 SHA1: 236c9d51c91e1d3342fe3cf4d47eef04037e37a9 MD5sum: 8f292a4e63b408789e4e897e52255adc Description: routines to convert IEEE floats to and from strings (debugging symbols) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains the detached debugging symbols of the library. Package: libdouble-conversion-dev Source: double-conversion Version: 2.0.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 199 Depends: neurodebian-popularity-contest, libdouble-conversion1 (= 2.0.1-1~nd+1) Homepage: http://double-conversion.googlecode.com Priority: extra Section: libdevel Filename: pool/main/d/double-conversion/libdouble-conversion-dev_2.0.1-1~nd+1_amd64.deb Size: 48874 SHA256: c8d1905c8986a07ae0fd8062a5773d2dce757a570d43a5ad778785ece92bae4b SHA1: 85ab84485d4aa582d23884f65f9eb87cf6946093 MD5sum: 2f718f32b9de43311cd6fe547dc56be8 Description: routines to convert IEEE floats to and from strings (development files) This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a static version of the library and development headers. Package: libdouble-conversion1 Source: double-conversion Version: 2.0.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 75 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://double-conversion.googlecode.com Priority: extra Section: libs Filename: pool/main/d/double-conversion/libdouble-conversion1_2.0.1-1~nd+1_amd64.deb Size: 32816 SHA256: 8d084bf359e2e719baa3bc8a51fcf6bb78d316c98e79afa1b8f3c5704575c418 SHA1: e777c8ef9c4622b6b9152409b809513f7e11930d MD5sum: 55116668824275dde1f5763ff6754ab3 Description: routines to convert IEEE floats to and from strings This library provides routines to convert IEEE single and double floats to and from string representations. It offers at lot of flexibility with respect to the conversion format: shortest, fixed, precision or exponential representation; decimal, octal or hexadecimal basis; control over number of digits, leading/trailing zeros and spaces. . The library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. The code has been refactored and improved so that it can be used more easily in other projects. . This package contains a shared version of the library. Package: libdrawtk-dev Source: drawtk Version: 2.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_2.0-2~nd+1_amd64.deb Size: 43600 SHA256: 114d7a4af1f317efb54c7062252f502ed7a578ae62d33de0f98bc8e289d7a3bd SHA1: de340071bb3464f72afebdea6357d7ebda6ea4b8 MD5sum: 510b3581e95e0f5654910c817ca9a58f Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 2.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 66 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreeimage3, libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.11) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_2.0-2~nd+1_amd64.deb Size: 36386 SHA256: 10ac89b07cdbe58d7cf10013f149cbbbdb3673e9ebedfbd3bfdfd7467773b064 SHA1: f68dde73625f026a2db0d116c70018e5c99d85ce MD5sum: 0254920c2ed10d3cbcf061ef53f39878 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 2.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_2.0-2~nd+1_amd64.deb Size: 79720 SHA256: 8c4f0fdc1ed058c0921906ed665079e08447ed883c754791d5b3b69921f4525b SHA1: af113c056a69f739b7e95caaf5b18a360c38cf26 MD5sum: 802c2440009c0800fc946e960b3ec9f7 Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Package: libedac-dev Source: edac-utils Version: 0.18-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, libedac1 (= 0.18-1~nd+1) Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: libdevel Filename: pool/main/e/edac-utils/libedac-dev_0.18-1~nd+1_amd64.deb Size: 18922 SHA256: 72d81cdd7be0e7555fc705116451bf9151a6afea3a9a41c4f876ec912679c5b9 SHA1: 7128511b9b0fc0524286efc5b688931c838cf37e MD5sum: 79fb263dbc69404ff64497141ef6f93d Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package contains development files for the library Package: libedac1 Source: edac-utils Version: 0.18-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libsysfs2 Provides: libedac Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: libs Filename: pool/main/e/edac-utils/libedac1_0.18-1~nd+1_amd64.deb Size: 14974 SHA256: cbd9324827d1a39bf9e20509de4f9e6aad2f601312eb175ab9ba53db8142753c SHA1: 552751ee230545e2b4aa65f90e6978388a5dc74b MD5sum: 704ff786aa0dc1b22e158705b20db4ef Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package includes shared library Package: libedac1-dbg Source: edac-utils Version: 0.18-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 91 Depends: neurodebian-popularity-contest, libedac1 (= 0.18-1~nd+1) Provides: libedac Homepage: http://sourceforge.net/projects/edac-utils Priority: extra Section: debug Filename: pool/main/e/edac-utils/libedac1-dbg_0.18-1~nd+1_amd64.deb Size: 38424 SHA256: 504a189f7860c080c4c836ea6646c79bb4486a649850f70e544a80c3ea9d39cc SHA1: e16f0a8209a74c5ff4ea040827ec2f8d0949c174 MD5sum: f85459635937b87db80422e15540a4d8 Description: report kernel-detected PCI and ECC RAM errors This package contains the user-space utilities for use with the EDAC kernel subsystem. EDAC (Error Detection and Correction) is a set of Linux kernel modules for handling hardware-related errors. Currently its major focus is ECC memory error handling. However it also detects and reports PCI bus parity errors. . PCI parity errors are supported on all architectures (and are a mandatory part of the PCI specification). . Main memory ECC drivers are memory controller specific. At the time of writing, drivers exist for many x86-specific chipsets and CPUs, and some PowerPC, and MIPS systems. . This package includes shared library with debugging symbols not stripped Package: libeegdev-dev Source: eegdev Version: 0.2-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libdevel Filename: pool/main/e/eegdev/libeegdev-dev_0.2-3~nd+1_amd64.deb Size: 22446 SHA256: 7bd2e373379d12ae035183071af1c48463ce4080c098a054e4cc5f2153b8eab1 SHA1: 2de32029aee3d34ca41ade541fde39241e8da6e0 MD5sum: 003ee78d125b4881b0b5ae190afd2a29 Description: Biosignal acquisition device library (Developement files) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the files needed to compile and link programs which use eegdev. Its provides also the headers neeeded to develop new device plugins. The manpages and examples are shipped in this package. Package: libeegdev0 Source: eegdev Version: 0.2-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 80 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.3.2) Recommends: eegdev-plugins-free Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: libs Filename: pool/main/e/eegdev/libeegdev0_0.2-3~nd+1_amd64.deb Size: 46258 SHA256: 936cd3384dc48c6893e3fbf4d8f5bd4001de40f9f19f2b83a0272e7ba31feff4 SHA1: 54be314608aeeafa756c7c90e15e27f3af8a4646 MD5sum: ba475b721f95c0fceb73482569d7d2b2 Description: Biosignal acquisition device library eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package contains the core library Package: libeegdev0-dbg Source: eegdev Version: 0.2-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 190 Depends: neurodebian-popularity-contest, libeegdev0 (= 0.2-3~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/eegdev.html Priority: extra Section: debug Filename: pool/main/e/eegdev/libeegdev0-dbg_0.2-3~nd+1_amd64.deb Size: 166280 SHA256: 24c02693885dc88a249e91263b11d8e8b58d881ad7a170011e00a5d56b9c4b53 SHA1: 41a6606909a1cb1c38c3b36dbba6f00d3b9349d2 MD5sum: cde8b893ea54e74e3af505cf59395b75 Description: Biosignal acquisition device library (Debugging symbols) eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the mean of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially. . The core library not only provides to users a unified and consistent interfaces to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task. . This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research. . This package provides the debugging symbols for the library. Package: libeigen3-dev Source: eigen3 Version: 3.0.1-1.1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3412 Depends: neurodebian-popularity-contest Suggests: libeigen3-doc Homepage: http://eigen.tuxfamily.org Priority: extra Section: libdevel Filename: pool/main/e/eigen3/libeigen3-dev_3.0.1-1.1~nd+1_amd64.deb Size: 509860 SHA256: 43b2baa64b33e4fbf11a783946fdfe245a8d78b44bd74e940191add8defaaf6c SHA1: 9fc35c3326dd1ba971587496db83a3259211d2b9 MD5sum: 53485f52ab1a0e0491b59fed04f76c8a Description: lightweight C++ template library for linear algebra Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . Unlike most other linear algebra libraries, Eigen 3 focuses on the simple mathematical needs of applications: games and other OpenGL apps, spreadsheets and other office apps, etc. Eigen 3 is dedicated to providing optimal speed with GCC. A lot of improvements since 2-nd version of Eigen. Package: libeigen3-doc Source: eigen3 Version: 3.0.1-1.1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10344 Depends: neurodebian-popularity-contest, ttf-freefont, libjs-jquery Suggests: libeigen3-dev Homepage: http://eigen.tuxfamily.org Priority: extra Section: doc Filename: pool/main/e/eigen3/libeigen3-doc_3.0.1-1.1~nd+1_all.deb Size: 2377404 SHA256: c6e5364649cf5f6b1db3f3ae2ba998964c4fe8f2eb419b325c156d12f699ebba SHA1: 43b49a1ec0f5cb0655454679d1d1655729ff6721 MD5sum: bd7d512332aa9a1e81f26066dcd42be1 Description: eigen3 API docmentation Eigen 3 is a lightweight C++ template library for vector and matrix math, a.k.a. linear algebra. . This package provides the complete eigen3 API documentation in HTML format. Package: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7784 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd+1), libfreeipmi16 (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd+1_amd64.deb Size: 915688 SHA256: 07b6183fa1ef276c35c8321f275b246a33c8c056850d3ddd0fcdef226343f203 SHA1: cf511c9ec409de6fe6470176fd431e604d35675d MD5sum: 7443942fb3b4598c47132b03a02746f9 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: libfreeipmi12 Source: freeipmi Version: 1.1.5-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4625 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcrypt11 (>= 1.4.5), freeipmi-common (= 1.1.5-3~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi12_1.1.5-3~nd+1_amd64.deb Size: 1095562 SHA256: c56dc9aaa6c83b8762fcc51cc474dc6551c306208667ef0c5cb60ad9a15a217f SHA1: b9b9a184ac3aed215d925b5f1cd2ee7c25a930fa MD5sum: 0068dadc37b88d9bba5a9d56250c0d2b 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: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5091 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt20 (>= 1.6.1), freeipmi-common (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd+1_amd64.deb Size: 822604 SHA256: d608367c6764604ca7bf95b6f5d2b776cc43e469ffb2d18913cf3e3d50959299 SHA1: fbbfc7809ef865cb4f6b338229c341fc58fd669a MD5sum: a9bb0d31aac2f2c1ac9871fb9dc13452 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 248 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 (>= 4.4.0) 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_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 55106 SHA256: 33ba17376e2be0bda5287d629e8a24d89ab052b8f962d1928196c608e26d7bdf SHA1: 9b2cd7420aea771c9f518a7f726ff0f87444aeba MD5sum: 61528ebf530d0e14fab7a4efe30185ca 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 8520 SHA256: 9de229affec3e86e00ba8a7a50d730d177db1153eaa17489c98a14eb2b3d860a SHA1: 75ea040843e4d9b18d43663f43c6548b1baf4de2 MD5sum: c5770e0a0352fe359446534b3d7796df 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 62 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.2+git6-g5455843+dfsg-1~nd+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_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 19284 SHA256: b0e95cc3b5b0eb420d4eafe2b94c16c31c0b6799775f4e558a9071d2b35ca1fc SHA1: 203e41b21e1316213db8611e3289cdf0a98c0f90 MD5sum: 735abc5a984610d2e8a2abf28d7a17a3 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 647 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.2+git6-g5455843+dfsg-1~nd+1_all.deb Size: 90086 SHA256: 68f42b33ec077a3faf58c19fe5cf2c27447d8fee3138c77f150b768b7e9f82dc SHA1: 528662d27cbab6b251d1a9ed0ef62a9e4ff297d9 MD5sum: e6f8806207d425ef8660693e40b6c021 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: libfreenect0.1 Source: libfreenect Version: 1:0.1.2+dfsg-6~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.8) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.1_0.1.2+dfsg-6~nd+1_amd64.deb Size: 37404 SHA256: 44d0a6dcf73d04db5430676ac421ae65152f479dd479f87e5e45d26754c576a5 SHA1: 5e6738d64d21246d05ee18a4e62a723ecdc5aa37 MD5sum: 9dd9578548d7edab65be0710546b4dbe 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: libfreenect0.5 Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 107 Pre-Depends: multiarch-support 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_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 42158 SHA256: 62dbb8e9db557618036ed037cdf985a9cd08257a2d6e2fd43fa03907005519c0 SHA1: 534d65a506d3756c9bf839f9cc050bde6113cd83 MD5sum: df698ed432ec74cfae67b3c2bb329516 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: libgdf-dev Source: libgdf Version: 0.1.2-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-2~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.2-2~nd+1_amd64.deb Size: 19768 SHA256: c6a960971c49788f5a01a18e667435fe4db5add6e35083393a9fdf837164fefc SHA1: 7caeae7296cf9543789d2e22b551d35a63d530cb MD5sum: dc2822666076a15dddf2489ac3163df9 Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.2-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 823 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.2-2~nd+1_amd64.deb Size: 220678 SHA256: a7b5ededfa818702bcc8152ecefa293f8ddb7bdd09d4c27e3cf6cf06602d5077 SHA1: a25c86393dd8656d88867f2c0214a6feabb12b23 MD5sum: d598b3b7ccb5365c3513d1e5dfe30650 Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.2-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2721 Depends: neurodebian-popularity-contest, libgdf0 (= 0.1.2-2~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.2-2~nd+1_amd64.deb Size: 611024 SHA256: 9d740d601f221e335e0005a5987697af4c3233c7271ae8c4b09126c6a3a32291 SHA1: 1fc1f05fc60044049fbfb8507ede84a02a68f5cd MD5sum: dbcb477d7c2656cdf428763846b03796 Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libglew1.6 Source: glew Version: 1.6.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 452 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.6_1.6.0-2~nd+1_amd64.deb Size: 123972 SHA256: 537d4f4a7623682c5c33f9c0067ab1eb9dba5673c1c348d3e09f590510c74413 SHA1: d1f845afe92ae5246f71232d4ceff1e1f08c7991 MD5sum: 92c4ecb7bb9fd83394e928b71beb8090 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.6-dev Source: glew Version: 1.6.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1516 Depends: neurodebian-popularity-contest, libglew1.6 (= 1.6.0-2~nd+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.5-dev Provides: libglew-dev, libglew1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.6-dev_1.6.0-2~nd+1_amd64.deb Size: 244768 SHA256: 4bcb0544947f90a633d52e13f60521b12b7b69a5602583400dd342e1a135230e SHA1: 75f240bb9dc1d795751bd7215cc13fafc57504b4 MD5sum: 243e92dca33a3df2f389d625941be885 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development documentation as well as the required header files. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 650 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 Suggests: glew-utils Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.9_1.9.0-3~bnd1~nd+1_amd64.deb Size: 183556 SHA256: ec470c7c0d89504eb7412c7021b11b00cfdd959a767e3fa9799f9954d64d7fd4 SHA1: 39a6194e471b7063ade4268ae86a228c9c64f157 MD5sum: 02ae332f55b9ce7d8099b495c27733bc Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd+1_amd64.deb Size: 41060 SHA256: 3a97756750062d708bb8eb2ed2e825fd6e34429cdddb7f30549c82902b2e97e1 SHA1: 3aa2132d89d88f867c252edee0dd50692225477a MD5sum: 580a49626e6611c1174946bfe64437fb Description: OpenGL Extension Wrangler (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglew1.9. Package: libglew1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd+1), libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.6-dev Provides: libglew1.5-dev, libglew1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.9-dev_1.9.0-3~bnd1~nd+1_amd64.deb Size: 153218 SHA256: 27fbf8145faab168a2ec8d315030d9961ad3c820d3de2958857e8af2e29b9db5 SHA1: 1452a1306fa94ea49d2c366afa8a6e36a0a62dc2 MD5sum: 2702a2385ae44398744921df12a43d8f Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development documentation as well as the required header files. Package: libglewmx1.6 Source: glew Version: 1.6.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 396 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Homepage: http://glew.sourceforge.net/ Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.6_1.6.0-2~nd+1_amd64.deb Size: 109686 SHA256: 6b9e04505849c96ccee2af033fed1635ab732bbca9993c48fb45bf8cd684597c SHA1: 05b2cb7adb027f7147b05edcbd60643110ba0a8c MD5sum: 4c1084a82d81286e09356141198971e5 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.6-dev Source: glew Version: 1.6.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 524 Depends: neurodebian-popularity-contest, libglew-dev, libglewmx1.6 (= 1.6.0-2~nd+1) Conflicts: libglewmx-dev, libglewmx1.5-dev Provides: libglewmx-dev, libglewmx1.5-dev Homepage: http://glew.sourceforge.net/ Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.6-dev_1.6.0-2~nd+1_amd64.deb Size: 101858 SHA256: ed330da36792d703dfda5228af7053a0617640ccc95dabb194914daeb2fd6738 SHA1: 8f40dd745f044bd50d334a0a4c45649612cca4bb MD5sum: 4af9582b1e48afeb460f8342548d3cbf Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry[1]. . This package contains the development libraries compiled with GLEW_MX Package: libglewmx1.9 Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 573 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1, libx11-6, libxext6, libxi6, libxmu6 Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.9_1.9.0-3~bnd1~nd+1_amd64.deb Size: 164568 SHA256: 1de6aeabab350c20b23db0630546449e4db913b54dcd147c48628aa57cb00af8 SHA1: 460640685994e11538cb79726a80771a1c9a5d3c MD5sum: b4fec025620b987fa433d6ac25eb05c9 Description: OpenGL Extension Wrangler (Multiple Rendering Contexts) For more information about GLEW please refer to the description of the libglewmx-dev package. . 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Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglewmx1.9. Package: libglewmx1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd+1) Conflicts: libglewmx-dev, libglewmx1.6-dev Provides: libglewmx1.5-dev, libglewmx1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.9-dev_1.9.0-3~bnd1~nd+1_amd64.deb Size: 8814 SHA256: 60cbe85972f17f40c55bd8f22da41ec6e22ff9aa884808dd9dc72ab7535ef63e SHA1: 9c8459075282450492c82e7cfcc5360ff4ea1144 MD5sum: ceb70933d667dfeec4d1158a6f6e8dab Description: OpenGL Extension Wrangler MX - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development libraries compiled with GLEW_MX. Package: libguac-client-rdp0 Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 109 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libcairo2 (>= 1.6.0), libfreerdp1 (>= 1.0.1), libguac5, libogg0 (>= 1.0rc3), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2), ghostscript Recommends: libfreerdp-plugins-standard Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-rdp0_0.8.3-1~nd+1_amd64.deb Size: 28104 SHA256: 9c5eeb77468263f3eb888cce9f06fa7c575d5e995e27184048f0771ff55ba9d9 SHA1: 4a9613ebfb3b7a0cb8a6efad9ae47596ec3dc307 MD5sum: 0491e9b6e74c2fcf921ccc3b94f9f6a5 Description: RDP support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the RDP protocol (Windows Remote Desktop). Package: libguac-client-ssh0 Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libguac5, libpango-1.0-0 (>= 1.22.0), libpangocairo-1.0-0 (>= 1.14.0), libssh-4 (>= 0.3.91) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-ssh0_0.8.3-1~nd+1_amd64.deb Size: 22382 SHA256: 5f8bed44a3302086392488ea71c2d0a90678d3f8b5375e355864c40229194032 SHA1: 8bfeb6937b95ed2259429e4740fd4f44cfa3fe78 MD5sum: 1b398c4599a9408ae9e3336702184676 Description: SSH support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the SSH protocol. Package: libguac-client-vnc0 Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 27 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcairo2 (>= 1.6.0), libguac5, libpulse0 (>= 0.99.1), libvncserver0 Recommends: vnc4server Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac-client-vnc0_0.8.3-1~nd+1_amd64.deb Size: 10802 SHA256: 123c88507dce5f8155416944a9d98af6f380e056f99759609301a3bda64df516 SHA1: 4c4ab450edf7179e1ba54507eb0fd9b5ba4f3ce6 MD5sum: bb4ad23a11b2a854c01997e80023d4a3 Description: VNC support plugin for Guacamole A plugin for the Guacamole proxy daemon (guacd) that provides support for the VNC protocol. Package: libguac-dev Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 214 Depends: neurodebian-popularity-contest, libguac5 (= 0.8.3-1~nd+1) Replaces: libguac1-dev Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libdevel Filename: pool/main/g/guacamole-server/libguac-dev_0.8.3-1~nd+1_amd64.deb Size: 35834 SHA256: aa3a262e0590b39303bee15833f0ba72365439a5877ad245379538b3b43a4e23 SHA1: 97d3b1cad6d0ecb137b0c84be5f4719ef9fe9581 MD5sum: 05010cdf0bc63ca1e318e9a0bd406e05 Description: Development headers for the core Guacamole library The development headers for the core Guacamole library used by guacd and all client plugins. This package is required for development of new client plugins, or for building existing plugins and guacd. Package: libguac3 Source: libguac Version: 0.6.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libpng12-0 (>= 1.2.13-4) Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: libs Filename: pool/main/libg/libguac/libguac3_0.6.0-2~nd+1_amd64.deb Size: 18986 SHA256: 71c9d799fc32b796309d5b17209a865d3acb8f2af3c6dabbc3e31514280c0593 SHA1: 7ae6e19fc62c88079406be65d77baf3533e3cca0 MD5sum: 9217c23780f8ba502c003a06f6fe3cfe Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libguac5 Source: guacamole-server Version: 0.8.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.17), libcairo2 (>= 1.2.4), libogg0 (>= 1.0rc3), libpng12-0 (>= 1.2.13-4), libvorbis0a (>= 1.1.2), libvorbisenc2 (>= 1.1.2) Multi-Arch: same Homepage: http://guac-dev.org/ Priority: extra Section: libs Filename: pool/main/g/guacamole-server/libguac5_0.8.3-1~nd+1_amd64.deb Size: 21550 SHA256: 8de79f47b2f45af3ba04808717fc0d4dab9a3dc61adc49ea33738c9b7368a87e SHA1: 86b1c0dce3f509d73393fbd7449b4c9930fd86ab MD5sum: 41ea311850ad7b6fd973fdc1544c3bbf Description: Core Guacamole library used by guacd and client plugins The core Guacamole library which both guacd and client plugins depend on to provide low-level I/O and protocol support. Package: libinsighttoolkit4-dbg Source: insighttoolkit4 Version: 4.7.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 41926 Depends: neurodebian-popularity-contest, libinsighttoolkit4.7 (= 4.7.0-1~nd+1) Homepage: http://www.itk.org/ Priority: extra Section: debug Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4-dbg_4.7.0-1~nd+1_amd64.deb Size: 37242576 SHA256: 9b9754854404dde5cc9a7e388e3f61a60e07010b4bc6a4c32c8615a31a05b515 SHA1: 3d6f4a95c086d364243aeccf082082e65734ea06 MD5sum: f803a7ea2c8d9b8bade0df20a7e723ac Description: Debugging information for the Insight Toolkit ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the debug files of the libraries. Package: libinsighttoolkit4-dev Source: insighttoolkit4 Version: 4.7.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 25377 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libinsighttoolkit4.7 (= 4.7.0-1~nd+1), libstdc++6 (>= 4.9), libgdcm2-dev, libdcmtk2-dev, libhdf5-dev Recommends: libfftw3-dev, uuid-dev Suggests: insighttoolkit4-examples Conflicts: libinsighttoolkit-dev, libinsighttoolkit3-dev Replaces: libinsighttoolkit-dev Homepage: http://www.itk.org/ Priority: optional Section: libdevel Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4-dev_4.7.0-1~nd+1_amd64.deb Size: 2958570 SHA256: 0dc1580b784ba8c44a5c1ae862877b0717f9f0066a9a0f4bd11ad0d3cd89bfcc SHA1: 1b68be6000e8843c33ef3aacf7a74c0368a48b70 MD5sum: 1effc39d7e0dfe454de76ad90008e545 Description: Image processing toolkit for registration and segmentation - development ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the development files needed to build your own ITK applications. Package: libinsighttoolkit4.2 Source: insighttoolkit4 Version: 4.2.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 22235 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgdcm2.2, libhdf5-7, libjpeg8 (>= 8c), libminc2-1, libnetcdfc7, libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), zlib1g (>= 1:1.2.3.3) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.2_4.2.1-2~nd+1_amd64.deb Size: 7285284 SHA256: 0bf5f59261cf3e0c70a589ff388f8eb80f89d89d6bc4b1d74b9c9fd486fa4657 SHA1: d9db3fff12782f106b08f196a7cead6c06bbdc45 MD5sum: 1c29f1e2334323ba146837de79d73820 Description: Image processing toolkit for registration and segmentation - runtime ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the libraries needed to run ITK applications. Package: libinsighttoolkit4.7 Source: insighttoolkit4 Version: 4.7.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 23825 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfftw3-double3, libfftw3-single3, libgcc1 (>= 1:4.1.1), libgdcm2.4, libhdf5-8, libhdf5-cpp-8 (>= 1.8.13), libjpeg62-turbo (>= 1.3.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.9), libtiff5 (>= 4.0.3), zlib1g (>= 1:1.2.3.4) Homepage: http://www.itk.org/ Priority: optional Section: libs Filename: pool/main/i/insighttoolkit4/libinsighttoolkit4.7_4.7.0-1~nd+1_amd64.deb Size: 4698324 SHA256: 0fb11641c3f61971649eb183ff91950d099598a8023da5aed9ed0201503f8f7f SHA1: aa8bf028e4094a1b2dafac06bb42f4ed227e8c89 MD5sum: 81b5054013143215bafc30a29568d359 Description: Image processing toolkit for registration and segmentation - runtime ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the libraries needed to run ITK applications. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.9-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 518 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd+1), libipmiconsole2 (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd+1_amd64.deb Size: 101806 SHA256: 38b0677816c0cce6e6e02fafeea2fc976f5453bf6fa14d2a9246aff4846b7645 SHA1: 5f0ac0525c6b5772d8cf7cd6c878a1e4924d88bd MD5sum: 2dcb84a5a7bf18d1bc57aba3ff214ebb 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 266 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), libgcrypt20 (>= 1.6.0), freeipmi-common (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd+1_amd64.deb Size: 86286 SHA256: 50bd5833cbd87c53c70eb110c9ef35a2e9fbd72eba57093540c5ef15e479d525 SHA1: f1cea9da7ee8e35c62717f25114afa17e7102361 MD5sum: 4125fb74c47fda75a76a109e487b5d3f 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd+1), libipmidetect0 (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd+1_amd64.deb Size: 31594 SHA256: 0b26654635fff479bd9f51b31bcb9e381d6235f56b254f408c836a64e4fe872d SHA1: f312df507f3c34a7e05b4f5b171ae499e0314954 MD5sum: dcba8c63eb8af8b1e1b90141ffc2adbf 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 75 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd+1_amd64.deb Size: 25640 SHA256: a1654358f64c021250ade5218e68adaac13434c7d7249ebf7f80f43bf30a6008 SHA1: ee99a89e3163bfd0cbdb57523d3687b768cac88f MD5sum: e4a814c1a24c4c495b4381564ad4fc80 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd+1), libipmimonitoring5a (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd+1_amd64.deb Size: 61580 SHA256: 632d2bc424a11e28152a5e212bf986dc326ae5fa8436a2fe1e5558215e47cd85 SHA1: dec0341813469c73b5c05658043f5df250397937 MD5sum: 169738719b0fcdc86ca4cd205020cc63 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: libipmimonitoring5 Source: freeipmi Version: 1.1.5-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 255 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi12 (>= 1.1.5), libgcrypt11 (>= 1.4.5) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5_1.1.5-3~nd+1_amd64.deb Size: 190374 SHA256: 2f58fd78b6d373e46376c2263d84babcf3f3f6695ad550d110ec1880803a9f97 SHA1: 8eeb56eec313330a216e1003f7ce151643023a6b MD5sum: 6db74317d0ee66d7090aad8e518b0b2e 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: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libfreeipmi16 (>= 1.4.4), libgcrypt20 (>= 1.6.0), freeipmi-common (= 1.4.9-1~nd+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd+1_amd64.deb Size: 43450 SHA256: fa73621cb5fa81beb55a47f42ae39b54f0ab568f6f54399b050361974419d89a SHA1: 1d007cb826cc372d7412628b887d1b9decc20d8e MD5sum: 9cbcbe3abae53043d2b3cb9bacd3a694 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd+1_amd64.deb Size: 13794 SHA256: 5cd7a2f154850bc416839678496aac8cdb8cdc7d4edbfa752109cafeda052afa SHA1: 99bcb68e7b6f0340eefbcf1cc7ae0779927e05b6 MD5sum: 448cb3230e24537149c84706f1326854 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~nd+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~nd+1_all.deb Size: 158244 SHA256: 731a984503486f267ec68521dd5d3465dce1ba96a6808b77fc7e2345b729de6c SHA1: e3aa32efb2aaec1cdf7169e6a9afcc00afe36e95 MD5sum: 7a48add23e72992c4367c723dd4642f9 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 348 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libhdf5-10, libpugixml1v5 (>= 1.4), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd+1_amd64.deb Size: 77770 SHA256: f379c9aaafcf205f889ee613926acbe7a28b89f57079f5d96ff69b3e457a0482 SHA1: 20850f64601b774bb1944c0db3e078e6058ec2ff MD5sum: ad0dba8ff810c7b7b18d0bfce4422e9a 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: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libdevel Filename: pool/main/m/mcpanel/libmcpanel-dev_0.0-1~nd+1_amd64.deb Size: 2400 SHA256: a4612428a1f388a69ba3eea0f0603e83eff41909d6e033ce32ceebc0df5b4842 SHA1: e58ee9c82c1adcdc4878bf89d49d534a443fd108 MD5sum: ad0a76058eb30f7d0ea7e78e6afd51d5 Description: Library to display multichannel data in realtime (Developement files) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the files needed to compile and link programs which use mcpanel Package: libmcpanel0 Source: mcpanel Version: 0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.14.0), libgtk2.0-0 (>= 2.14.0), libpango1.0-0 (>= 1.14.0), librtfilter1 (>= 1.0) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libs Filename: pool/main/m/mcpanel/libmcpanel0_0.0-1~nd+1_amd64.deb Size: 54376 SHA256: 0035c4aed5a6c0e34dd464c28cb2f1c18b9dfad4f1fc6a26fde7b5325418a2dc SHA1: 511dbe17ba3f96d3a187f012776683f21c248aad MD5sum: a232d613589b15d2a132dc7f3ed9730b Description: Library to display multichannel data in realtime This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. Package: libmcpanel0-dbg Source: mcpanel Version: 0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 333 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: debug Filename: pool/main/m/mcpanel/libmcpanel0-dbg_0.0-1~nd+1_amd64.deb Size: 122698 SHA256: fa5126364e2697614b6b6f9b8ab926dff122ba5c81774b0b1691a56159349c3f SHA1: 6aed06ef0c7b81b6cb17512f886a517a345df166 MD5sum: fb644b2c8df228c2fbd7669a4670832c Description: Library to display multichannel data in realtime (Debugging symbols) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the debugging information of the library. Package: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 25189 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-single3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp8, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd+1_amd64.deb Size: 3775132 SHA256: a8ef5f80f762a766692f633a1e427b5db4d9b7dc042b5b771ebeba520bbb3037 SHA1: d3431a36a6d89d0ed4a31f92871f2d61dfce80ce MD5sum: 137af8cea7dc298a12d282d6b2d40016 Description: library for 2D and 3D gray scale image processing libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. Package: libmia-2.0-8-dbg Source: mia Version: 2.0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67823 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd+1_amd64.deb Size: 61623850 SHA256: d671870de0d5be969e2ff4ec1c8cf15355dab1dd2a99fd5f1c57b45e4cebbaba SHA1: 21866bb1f623b30654109fcacd8b7be7489ee54d MD5sum: 8ebf2051cbab211629c3d8db42cf8734 Description: Debug information for the MIA library libmia comprises a set of libraries and plug.ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. libmia is library for general purpouse 2D and 3D gray scale image processing. This package provides the debug information of the library. Package: libmia-2.0-dev Source: mia Version: 2.0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1093 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd+1), libxml++2.6-dev (>= 2.34.1), libitpp-dev (>= 4.2), libtbb-dev, libgsl0-dev, libboost-all-dev (>= 1.46.1), libfftw3-dev, libblas-dev Recommends: libmia-2.0-doc Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/m/mia/libmia-2.0-dev_2.0.13-1~nd+1_amd64.deb Size: 178112 SHA256: 6fbf362d7b4d2cf9558c0ac3e239782e98d3a859ade235de682877fc638aa1b8 SHA1: 4de0012e58dff3fab36f8ffe5eb4c5eaf643bb5c MD5sum: 626b192d264e70006b468fd64aabf9dc Description: library for 2D and 3D gray scale image processing, development files libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the development files for the library. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14011 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd+1_all.deb Size: 837904 SHA256: 6efc28d4222b4fb91ba00745e720dcd6ae7588b802cf7b12051065e2f784bcd0 SHA1: e36b5e877dfe57819cadb4ca52228fa321a74390 MD5sum: de045c0e2212f343fde74be4c895c334 Description: library for 2D and 3D gray scale image processing, documentation libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the Doxygen generated API reference. Package: libmialm-dev Source: libmialm Version: 1.0.7-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 421 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libm/libmialm/libmialm-dev_1.0.7-2~nd+1_amd64.deb Size: 77948 SHA256: e856c869f583f0a3bc7a0953d81e94ddcccf21d96f70d2d67e916d68b2c0f2b3 SHA1: be866e93a2f6a75cdab67824baafed8a87f50971 MD5sum: 79ad1f569718761aa460156f1495dc3a Description: Development files for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the development files - headers, shared libraries, and pkg-config files. Package: libmialm-doc Source: libmialm Version: 1.0.7-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: neurodebian-popularity-contest Suggests: devhelp Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/libm/libmialm/libmialm-doc_1.0.7-2~nd+1_all.deb Size: 21290 SHA256: b0dd34278ad9a52597e66191c62a74baff467c13c2c870179302634477b9c8fa SHA1: 838394dd07ce9586d20f35968c02f61bac4c766f MD5sum: 7eefb55e9ae26db08d0750f3da3ec2a7 Description: Documentation for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package contains the library documentation. Package: libmialm3 Source: libmialm Version: 1.0.7-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 57 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libglib2.0-0 (>= 2.16.0), libxml2 (>= 2.7.4) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libm/libmialm/libmialm3_1.0.7-2~nd+1_amd64.deb Size: 18514 SHA256: 2b184476f5f14e1076694bddcb84a476ca7449c0edcbf6d9e89226929d95ab8e SHA1: f5fe36ca6527bc8fdc837f20d8435dfbb518172e MD5sum: 11a328479ca5881ec8c30b83eb8e3135 Description: Landmark handling for the MIA tool chain This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. Package: libmialm3-dbg Source: libmialm Version: 1.0.7-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, libmialm3 (= 1.0.7-2~nd+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libm/libmialm/libmialm3-dbg_1.0.7-2~nd+1_amd64.deb Size: 59194 SHA256: 6d057b468f3d042d59ff5a0b5585e9c78bb4dd6d50700c35021d1284ba96a369 SHA1: 49a72ee0224d61c7779c6dd02ac8d18a85ccfb00 MD5sum: dcec2d53f4f25b72fe6e8f0cf747aac1 Description: Debug information for the MIA landmark library This library implements handling for landmarks and 3D view positioning for optimal landmark visibility, and in-and output of these landmarks. This library is part of the MIA tool chain for medical image analysis. This package provides the debug information of the library. Package: libmtcp-dev Source: dmtcp Version: 1.2.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libmtcp1 (= 1.2.5-1~nd+1) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/d/dmtcp/libmtcp-dev_1.2.5-1~nd+1_amd64.deb Size: 5554 SHA256: 90752d16e9711895b4ae2627609ffb671548d5b7c50f768ac46ed42604b1b3a6 SHA1: 114daea12c7ac8d6292c18049805cf69153895ec MD5sum: 8e9cdb43c4278421fff5aeefac197824 Description: Developer package for libmtcp DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides header files needed for building programs with libmtcp. Package: libmtcp1 Source: dmtcp Version: 1.2.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 106 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://dmtcp.sourceforge.net Priority: optional Section: libs Filename: pool/main/d/dmtcp/libmtcp1_1.2.5-1~nd+1_amd64.deb Size: 45072 SHA256: 9e23e0114a6a8bf234d5be36ff5eb11c59c7591b7267a74af262e04e07a852d6 SHA1: e76e954c331daeed0f0e5c3908361b680e5926d6 MD5sum: 1d6ad2ceb74551671d0c1a10ee39df32 Description: DMTCP library needed for checkpointing a standalone process DMTCP (Distributed MultiThreaded Checkpointing) is a tool to transparently checkpointing the state of an arbitrary group of programs including multi-threaded and distributed computations. It operates directly on the user binary executable, with no Linux kernel modules or other kernel mods. . Among the applications supported by DMTCP are OpenMPI, MATLAB, Python, Perl, and many programming languages and shell scripting languages. DMTCP also supports GNU screen sessions, including vim/cscope and emacs. With the use of TightVNC, it can also checkpoint and restart X-Window applications, as long as they do not use extensions (e.g.: no OpenGL, no video). . This package provides libmtcp which is needed by DMTCP to checkpoint a single standalone process. Package: libnifti-dev Source: nifticlib Version: 2.0.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 592 Depends: neurodebian-popularity-contest, libnifti2 (= 2.0.0-2~nd+1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-2~nd+1_amd64.deb Size: 138178 SHA256: 9e94d8b96305aeabafe7ae5247a18001ec20c4dba727faf131fc579a0f00b1d3 SHA1: 47b6d447df056ed81127f6be7032218be2e34a11 MD5sum: 635819c71bc979886e3ccb1ea50fd991 Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-2~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1692 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-2~nd+1_all.deb Size: 140120 SHA256: 686d57e91867e23c55f747d863502416f84742afb987fd4ebb04c9c92d37d998 SHA1: 082412016af6c5d134f591ec409101525ab5916d MD5sum: 2e3ad2d99bfd2cebade7b1bcf6aaff07 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 307 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-2~nd+1_amd64.deb Size: 107430 SHA256: 6074f2f86ea79adac869fda824e3895ff7d2e738bc0dface064a514d7348cb61 SHA1: 3e654df8fdbeb7f09c0517cf785b332bbc2e9a19 MD5sum: 0a9a9249cf95e8acd0260187e36da1cf Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libnlopt-dev Source: nlopt Version: 2.4.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 595 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd+1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libdevel Filename: pool/main/n/nlopt/libnlopt-dev_2.4.1+dfsg-1~nd+1_amd64.deb Size: 170298 SHA256: 3b949a08fab4cb287da92640c977d79385493b316c98a9719dd2cc27db2ca6ad SHA1: b5c3a47c7e0c95cc5dd2a98475ce2397a016129d MD5sum: a143d64188c5c23b9d267a0f964f4199 Description: nonlinear optimization library -- development package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the header files, static libraries and symbolic links that developers using NLopt library will need. Package: libnlopt-guile0 Source: nlopt Version: 2.4.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 130 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd+1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), guile-1.8 Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt-guile0_2.4.1+dfsg-1~nd+1_amd64.deb Size: 37014 SHA256: 474d98291828330b3457be9ae050536f67ea33d552921e677320998042072725 SHA1: d8f98d6d878565f85e173067ff6d015091f3d3d4 MD5sum: 1e014553c905a60f4dc98e0dea8af3b4 Description: nonlinear optimization library -- Guile bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the bindings for GNU Guile. Package: libnlopt0 Source: nlopt Version: 2.4.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 427 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Multi-Arch: same Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: libs Filename: pool/main/n/nlopt/libnlopt0_2.4.1+dfsg-1~nd+1_amd64.deb Size: 162260 SHA256: fa7798b7295e93e64b25e42d0cc87fa4e9955b84d1e8cbf4e288cf223607d835 SHA1: 094d3649da78a3d1af89e37f80959d01142cf497 MD5sum: 9022fdb216398afbd3d6fffa44241345 Description: nonlinear optimization library NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package provides the shared libraries required to run programs compiled with NLopt. To compile your own programs you also need to install libnlopt-dev. Package: libodin-dev Source: odin Version: 1.8.8-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 25639 Depends: neurodebian-popularity-contest Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.8-1~nd+1_amd64.deb Size: 2633994 SHA256: fd3e61605835564e8304a60b2f8f600ae039f0db677d01dfc4145f6399b73ca6 SHA1: 37fe70572ce6686b17f036c5feb93d6f21f51a3a MD5sum: 19e5035b293ba9169a116d4e14de29f4 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 197 Depends: neurodebian-popularity-contest Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-4~nd+1_amd64.deb Size: 42560 SHA256: 172d3c71cdd962e7ea7e7d7aba4913659aac254125a7f4af5cd88b3158552543 SHA1: 8dd28b974f00c17271f0a33a8bf4f06853d9b54f MD5sum: 9873bf212c5e47ec8cac580d73b21bcf Description: openmeeg library -- development files OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1791 Depends: neurodebian-popularity-contest, libatlas3-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.6) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-4~nd+1_amd64.deb Size: 271318 SHA256: 8a714c2b5f0ce62224ea82b71f5316928b68432252c4fff953a73812bf5c677e SHA1: e5391cadae65eb8bf2fb263735133b0ab573b7b6 MD5sum: 2c26b8bf96571574e8a4bdc5d8f37f92 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides dynamic libraries. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6519 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.54.0, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph99, libstdc++6 (>= 4.6) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.4.0~rc1+hg3a3147463ee2-1~nd+1_amd64.deb Size: 1236670 SHA256: c556c0ae79475adbcbb1d59e0bd45f1bfce29322c59278a9a7c3560b43201d42 SHA1: 7b2b786b9a9e697ea6c780ed2808e65e84c578c0 MD5sum: d63e8012474b24f8c93265ac9f042679 Description: Framework for multi-modal medical and brain data visualization OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 3.0.0), libopenthreads-dev (>= 3.0.0), libboost-dev (>= 1.46.0), libboost-program-options-dev (>= 1.46.0), libboost-thread-dev (>= 1.46.0), libboost-filesystem-dev (>= 1.46.0), libboost-date-time-dev (>= 1.46.0), libboost-system-dev (>= 1.46.0), libboost-signals-dev (>= 1.46.0), libboost-regex-dev (>= 1.46.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.4.0~rc1+hg3a3147463ee2-1~nd+1_amd64.deb Size: 249446 SHA256: 164eec8aba84103665ac7e568185cf7956e7976b76f0b7b1c03cc9c542637d1c SHA1: 4b69737d7074c5b6e2d5274056c8b89e7c91feaf MD5sum: 00456cf1fec973b45febbad68314cd80 Description: Development files for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48075 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd+1_all.deb Size: 2681636 SHA256: d042340fe7dcca76e8158aa438e6b3e15ff18b784521652317a66f70e98c397e SHA1: 3b9b8845f6836b1497663e58556a9c2ed9497b4c MD5sum: d3f9e8e06482d3b6b8bca3c09e3737cd Description: Developer documentation for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libpam-cgroup Source: libcgroup Version: 0.37.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libcgroup1, libpam0g (>= 0.99.7.1) Homepage: http://sourceforge.net/projects/libcg/ Priority: extra Section: admin Filename: pool/main/libc/libcgroup/libpam-cgroup_0.37.1-1~nd+1_amd64.deb Size: 7824 SHA256: 5e8926012a5a9d48bb5d27257fb4d47803f353e060e4826e9cdce508e18766d8 SHA1: 753427d86004338370afc2545cec32651d14c5d1 MD5sum: 2b0fb6d9ba849c0db32094d055c2ed6f Description: PAM module to move a user session into a cgroup Control Groups provide a mechanism for aggregating/partitioning sets of tasks, and all their future children, into hierarchical groups with specialized behaviour. . This PAM module will move a user session into an existing cgroup by attempting to match uid and gid against the defined cgroup rules configuration. Package: librtfilter-dev Source: rtfilter Version: 1.1-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-4~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libdevel Filename: pool/main/r/rtfilter/librtfilter-dev_1.1-4~nd+1_amd64.deb Size: 12602 SHA256: 27b1531bb92def0976a579ea9f7ea7ebbc9a2c736fd66a1d5b407c5feb9110be SHA1: 9c430feb5bd104a84b0e8a9c9920ade5bc06aeb6 MD5sum: cda1de3f2c0a77596d0a99813fb87b05 Description: realtime digital filtering library (development files) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package contains the files needed to compile and link programs which use rtfilter. Package: librtfilter1 Source: rtfilter Version: 1.1-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: libs Filename: pool/main/r/rtfilter/librtfilter1_1.1-4~nd+1_amd64.deb Size: 32284 SHA256: 2ecd286d122cfd8081909454e2a7ba4414491ffc29e10d60af74b42d08968a24 SHA1: 6ee6ead80e1fbdadb144af70d1a46d602640cec9 MD5sum: 54eeea89770d108dba89f334ca1056fe Description: realtime digital filtering library rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). Package: librtfilter1-dbg Source: rtfilter Version: 1.1-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, librtfilter1 (= 1.1-4~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/rtfilter.html Priority: extra Section: debug Filename: pool/main/r/rtfilter/librtfilter1-dbg_1.1-4~nd+1_amd64.deb Size: 43178 SHA256: c51e4dcab91efdf27bd5475bd8844586fd8c5e1830a57195333b3f3a5e7284a2 SHA1: adfe52c8600987927e3dec249b947e110e3f7cd8 MD5sum: c2aeed10977cac0a2d89f5c2f9eb6649 Description: realtime digital filtering library (debugging symbols) rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter... . One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred). . This package provides the debugging symbols of the library. Package: libsvm-dev Source: libsvm Version: 3.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libdevel Filename: pool/main/libs/libsvm/libsvm-dev_3.0-1~nd+1_amd64.deb Size: 39858 SHA256: e60901ef45ad48ddab8e9ad01e145ec1b9376d6d851a4a75597e42690037ba2b SHA1: b3c9da08c1ea22891ae3e92fe026aa53783df252 MD5sum: f22e3b3a170b76749aac93569c5365ea Description: The LIBSVM header files These are the header files for LIBSVM, a machine-learning library. Package: libsvm-java Source: libsvm Version: 3.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libsvm3-java Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm-java_3.0-1~nd+1_all.deb Size: 13482 SHA256: 1492b2687984b9a78136924b2b39e6e61aa7cce3db838336fee65922035b3ee0 SHA1: 13a26757ee98ac492d11734e3a474b294266c9f2 MD5sum: 98d98d2c95a2b57a1d0f0fd2ccbf5e27 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. . This package solely provides a symbolic link from svm.jar svm3.jar. Package: libsvm-tools Source: libsvm Version: 3.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python, gnuplot Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: devel Filename: pool/main/libs/libsvm/libsvm-tools_3.0-1~nd+1_amd64.deb Size: 120618 SHA256: e1d145faa6c9fa5b18db06bb0be9804232915e72b0128f10a9cbd82a5c7cac52 SHA1: 47d6d9085d066923fe71a3b03439679572b21444 MD5sum: 7d92190fb1e31c0bb11798024b5bf098 Description: The LIBSVM binary tools LIBSVM is an easy-to-use package for support vector classification, regression and one-class SVM. It supports multi-class classification, probability outputs, and parameter selection. LIBSVM homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm Package: libsvm3 Source: libsvm Version: 3.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: libs Filename: pool/main/libs/libsvm/libsvm3_3.0-1~nd+1_amd64.deb Size: 46474 SHA256: 0c65840f15685c1bfc5e764f04d51f8a3963b6054164f9a562c29598db84e97c SHA1: 010513765f68d322979ed1c2230cdbac05464646 MD5sum: be36569a5174603abfb6c0381dcde4c0 Description: library implementing support vector machines The LIBSVM library is used to calculate Support Vector Machine optimizations with a great variety of powerful options. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. It is primarily of interest to machine-learning researchers and artificial intelligence application developers. Package: libsvm3-java Source: libsvm Version: 3.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, gij | java-gcj-compat | java1-runtime | java2-runtime Suggests: java-virtual-machine Conflicts: libsvm2-java (<= 2.91-2) Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: java Filename: pool/main/libs/libsvm/libsvm3-java_3.0-1~nd+1_all.deb Size: 60478 SHA256: 801debe37d8eb71cf96cc8acb1f192c1ff8b0a237ff08c17575a3294f5f65b68 SHA1: e237f6806ac39e2fccaca7e875b4a02449cb425a MD5sum: 5f50baac283e77ea67d18c68132f91b8 Description: Java API to support vector machine library The functionality of the libsvm are offered in a single jar file. It includes one-class, two-class, multiclass, regression-mode, and probablistic output functionality. Package: libvia-dev Source: via Version: 2.0.4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 969 Depends: neurodebian-popularity-contest, libvia2 (= 2.0.4-2~nd+1), x11proto-core-dev Conflicts: via-dev Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_2.0.4-2~nd+1_amd64.deb Size: 212222 SHA256: b2a55d94cb9a3e9a5ba63d9a0f9641887438e1bd29e61ba5c5bd83ee03aa24f3 SHA1: 0b57892b138d578f57ef792ecc43618e520ac444 MD5sum: a9b3e03e247341deeba5d3d9ffe7813d Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 2.0.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 903 Depends: neurodebian-popularity-contest Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_2.0.4-2~nd+1_all.deb Size: 118466 SHA256: b016bb696ef74d79bfb463aa989ab3d6b853f6dde7786e5fca7158c2cdc241bc SHA1: a75f6603432044f4e7a27b88453e558b9d97dd8d MD5sum: d816c6e69ff20beb455556cf9a20fcd0 Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia2 Source: via Version: 2.0.4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 568 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia2_2.0.4-2~nd+1_amd64.deb Size: 172346 SHA256: 8deadc3da8379a440e98e2ab0dfaf1df0b059ed955fd2d639ba752cb09b86801 SHA1: c4a9bd3eae156821096d99829cd79c367ec666dd MD5sum: 68536c339368c38a0fc654e5988a98f7 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: libvistaio-dev Source: libvistaio Version: 1.2.16-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 173 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd+1) Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/libv/libvistaio/libvistaio-dev_1.2.16-1~nd+1_amd64.deb Size: 108384 SHA256: 6da616ca33739b5cfbe82ee7d68cdb8e2a26195c9d8928b38d323f179b3a937d SHA1: e707934a4ff8c6a4245422e76c3b0d68a42a145b MD5sum: 05e9c987fdcb35aa71d757bad23f84bf Description: Development files for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is the development package containing the header files, and pkg-config script, and man pages. Package: libvistaio14 Source: libvistaio Version: 1.2.16-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 99 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/libv/libvistaio/libvistaio14_1.2.16-1~nd+1_amd64.deb Size: 37338 SHA256: 2b6d09436029c824ed0cde8c9912a1552873d8d955ef5cb91fd4ee4b9cbcc140 SHA1: 3065ffe1f951740789ba667bba29fbb4894002be MD5sum: 3378d5e7aac43df4849d35bb9938e50d Description: Library for loading and storing various types of binary data Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. Package: libvistaio14-dbg Source: libvistaio Version: 1.2.16-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, libvistaio14 (= 1.2.16-1~nd+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/libv/libvistaio/libvistaio14-dbg_1.2.16-1~nd+1_amd64.deb Size: 80754 SHA256: b4492a420b602fc0d70b7a39acb532fe612f9e3b62d01444b4b2bc3f5f2d6730 SHA1: 24bce5cd3ca2cc6fab6bbc172d48dfbad1b9f325 MD5sum: 5aa62add34bf3b88993a329fe11880a4 Description: Debug information for the libvistaio library Vistaio is a library that handles loading and storing of data in a cross-platform manner. Its virtue is that the otherwise binary files provide an ascii header that makes it easy to get information about the contens of a file. It supports a variety of data types like images, vector fields and graphs. This is package containing the debug information. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 702 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd+1_amd64.deb Size: 218312 SHA256: f56d5647573b51f7f78dc9a5bb4039cc3ebfc76bedf61b134e7fc836cf712c8e SHA1: 833c046b4196a973ac9bd91cbc7d00767d9022b6 MD5sum: 360601b54f1f54abc9d558749673dc0e Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 585 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd+1_amd64.deb Size: 232320 SHA256: 2b22b9e2e09ec73f6d0ce94e43bacd08ff99d39a77ff6acc6b55bcd2df904bb0 SHA1: a61d194c5089b76ca3a69d8ab9e6727e0a4b26e1 MD5sum: ab65d3914c00ad62427bf2d6620ab1cc Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1422 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd+1_amd64.deb Size: 492410 SHA256: 0765b32b1168830803a0c5158b24162d607aad9b773dab9afc64fecbfdd7a5d7 SHA1: dc1378b8a520d079d525ec053bb59e4f3e851cb1 MD5sum: bf7e348da50602826005ecb4289386c2 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 276 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.8 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~nd+1_amd64.deb Size: 73988 SHA256: 18c2ccbc016c5a04ddd56bc4e430fbd888ba36f40f3cde80dedcac34483d7e4d SHA1: 57fab3c9fa4f193b8931d4fa87a07d6d5491bb86 MD5sum: 59ffa85ca7e314c93654536013de7fab 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1876 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.4, libstdc++6 (>= 4.9), libvtk5.8, 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~nd+1_amd64.deb Size: 454106 SHA256: e7c80c2967c884f72bff9422716672026c089ad34bc80a9b5381ca104d890fe7 SHA1: e7093dc367909e8118813f819c46d7eb52dae5a2 MD5sum: 468a6e0432c4383353eebc2c5f0e9a59 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 564 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd+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~nd+1_amd64.deb Size: 80848 SHA256: bdac70c9493d17e67fc1a5a91a76f0463975dfdc2b8146f6f05ab7ddc1f52f70 SHA1: 3d65030e6e7761dfce650ccdf37580fad13c780b MD5sum: 8abd562c7cea573017c02f6ded01e5f9 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: libvtk-java Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10911 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libvtk5.8, zlib1g (>= 1:1.1.4) Suggests: libvtk5-dev (= 5.8.0-7+b0~nd+1), vtk-examples, vtk-doc, java-virtual-machine Homepage: http://www.vtk.org/ Priority: optional Section: java Filename: pool/main/v/vtk/libvtk-java_5.8.0-7+b0~nd+1_amd64.deb Size: 4911688 SHA256: 7dff14fd98779ece455045a424edbf7cf66cfc0b3e84fe7a7fb990f5747c066d SHA1: 1806f843614cfbea51d21e350da23469ffe9415a MD5sum: 582f3cccf93bc46635a35919787e6eb2 Description: Visualization Toolkit - A high level 3D visualization library - java The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK Java language support. Package: libvtk5-dev Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12852 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd+1), libgl1-mesa-dev | libgl-dev, libglu1-mesa-dev | libglu-dev, libx11-dev, libxt-dev, x11proto-core-dev, libc6-dev, libxss-dev, libxft-dev, libexpat-dev, libjpeg-dev, libpng-dev, libtiff-dev, zlib1g-dev, tcl8.5-dev, tk8.5-dev, libavformat-dev, libavutil-dev, libavcodec-dev, libswscale-dev, libgl2ps-dev, libfreetype6-dev, libxml2-dev, libpq-dev, libnetcdf-dev, libmysqlclient-dev, mpi-default-dev, libqt4-dev Suggests: vtk-examples, vtk-doc Conflicts: libvtk-dev, libvtk32-dev, libvtk4-dev Replaces: libvtk-dev, libvtk32-dev, libvtk4-dev Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-dev_5.8.0-7+b0~nd+1_amd64.deb Size: 2565186 SHA256: fc8dac41ae2e77932dedf520aa02697ad651edb91a2f1ca1e3d07bcd2081d5e4 SHA1: 6ea90e464abffbd8246f1ba87a9adb9de4d8204a MD5sum: 155e9a5ca5cf79975be0ae008641c6d8 Description: VTK header files for building C++ code The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK to do 3D visualisation. Package: libvtk5-qt4-dev Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 549 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libvtk5.8-qt4 (= 5.8.0-7+b0~nd+1), libvtk5-dev (= 5.8.0-7+b0~nd+1) Conflicts: libvtk5-qt3-dev Breaks: libvtk5-qt4 (<< 5.4.2-8) Replaces: libvtk5-qt4 (<< 5.4.2-8) Homepage: http://www.vtk.org/ Priority: optional Section: libdevel Filename: pool/main/v/vtk/libvtk5-qt4-dev_5.8.0-7+b0~nd+1_amd64.deb Size: 109432 SHA256: 067d2cb87fdae75da20c7965209c6cf6569646bdd4e3c5c500198510ff5e4de9 SHA1: 1fe30ebba984d528292d05cfd14bdb6664e19027 MD5sum: f01892997b07a13fd4017c4b84b10aea Description: Visualization Toolkit - A high level 3D visualization library - Qt devel The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK header files required to compile C++ programs that use VTK GUI support for Qt4. Package: libvtk5.8 Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 47808 Depends: neurodebian-popularity-contest, libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libgl2ps0, libjpeg8 (>= 8c), libmysqlclient16 (>= 5.1.50-1), libnetcdfc++4, libnetcdfc7, libopenmpi1.3, libpng12-0 (>= 1.2.13-4), libpq5, libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libtiff4 (>= 3.9.5-2), libx11-6, libxml2 (>= 2.7.4), libxt6, zlib1g (>= 1:1.2.3.3) Suggests: openmpi-bin | lam-runtime, libvtk5-dev, vtk-examples, vtk-doc Conflicts: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5, python-vtk (<< 4.4) Replaces: libvtk, libvtk32, libvtk4, libvtk4c2, libvtk4c2a, libvtk5 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8_5.8.0-7+b0~nd+1_amd64.deb Size: 15257918 SHA256: 12722282f82ca3a68c785de23dada2d96bdab6ba2f6a9ac9f66e85b6738df07a SHA1: e3bf98567f525433b9b75bc9c3c7cd235dec4370 MD5sum: d7739ec7f85a30b93245caa28158f760 Description: Visualization Toolkit - A high level 3D visualization library - runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . VTK enables users to concentrate on their work by providing a large number of excellent and feature packed high level functions that do visualization. The library needs OpenGL to render the graphics and for Linux machines Mesa is necessary. The terms/copyright can be read in /usr/share/doc/vtk/README and README.html. VTK-Linux-HOWTO has information about using vtk, getting documentataion or help and instructions on building VTK. . This package provides the shared libraries needed to run C++ programs that use VTK. . To compile C++ code that uses VTK you have to install libvtk5-dev. Package: libvtk5.8-qt4 Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1360 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqt4-network (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.8 Homepage: http://www.vtk.org/ Priority: optional Section: libs Filename: pool/main/v/vtk/libvtk5.8-qt4_5.8.0-7+b0~nd+1_amd64.deb Size: 484068 SHA256: 300d18c727a092d43ed423f862924d3ddee46d3ac1cb96956ea8e17068772e00 SHA1: d1d71eddd3c64edf901c7ddcf94f2b46d0b69b6e MD5sum: da32b0491774da5c508e7c1c7d8af53a Description: Visualization Toolkit - A high level 3D visualization library - Qt runtime The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package provides the VTK GUI support for Qt4. Package: libvw-dev Source: vowpal-wabbit Version: 7.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2616 Depends: neurodebian-popularity-contest, libvw0 (= 7.3-1~nd+1) Homepage: http://hunch.net/~vw/ Priority: optional Section: libdevel Filename: pool/main/v/vowpal-wabbit/libvw-dev_7.3-1~nd+1_amd64.deb Size: 326420 SHA256: a6f8f7017f2ed57b83d37ec8d52b747f201953432c05a52b1045d5dacad9ea7f SHA1: a322eae2d935b15e0b21b4fa9881a31cd0782804 MD5sum: f745aecb3c564f46ab8d671bdc3fada0 Description: fast and scalable online machine learning algorithm - development files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains development files needed to compile and link programs which use vowpal-wabbit's libraries. Package: libvw0 Source: vowpal-wabbit Version: 7.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 746 Depends: neurodebian-popularity-contest, libboost-program-options1.49.0 (>= 1.49.0-1), libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.2.3.4) Homepage: http://hunch.net/~vw/ Priority: optional Section: libs Filename: pool/main/v/vowpal-wabbit/libvw0_7.3-1~nd+1_amd64.deb Size: 244798 SHA256: e5609d18adfa65a25048028cfbbe0a200f51f68bbf09599729308f7825b028bc SHA1: 758918d8157198fdd5fc8affd7b2278f6b47578a MD5sum: 6e82531527b49b85e69e39f738e14bb6 Description: fast and scalable online machine learning algorithm - dynamic library Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains vowpal-wabbit's dynamic libraries. Package: libxdffileio-dev Source: xdffileio Version: 0.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 32 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.3-1~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libdevel Filename: pool/main/x/xdffileio/libxdffileio-dev_0.3-1~nd+1_amd64.deb Size: 27780 SHA256: eb3ae122becd833cd1b915fb213373d230110da5caf1f2dcbd22e4d13ad0ca56 SHA1: b9576e4644f307f88752e22f4d701fb39ccbbb97 MD5sum: 6b4dfbd1f3020fd15ded30e01a014640 Description: Library to read/write EEG data file formats (development files) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package contains the files needed to compile and link programs which use xdffileio. Package: libxdffileio0 Source: xdffileio Version: 0.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 83 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: libs Filename: pool/main/x/xdffileio/libxdffileio0_0.3-1~nd+1_amd64.deb Size: 43672 SHA256: 304e1ab3203f7dc04b122030f8bbeca772086fbbff286dd34f18898d572c9e32 SHA1: 7a09e94b11b300b2ceffacfd10b5032e01433a78 MD5sum: ab34b0bd2694f3037e21f1c0195cfcf4 Description: Library to read/write EEG data file formats xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead of the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. Package: libxdffileio0-dbg Source: xdffileio Version: 0.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, libxdffileio0 (= 0.3-1~nd+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/xdffileio.html Priority: extra Section: debug Filename: pool/main/x/xdffileio/libxdffileio0-dbg_0.3-1~nd+1_amd64.deb Size: 76368 SHA256: f1286f7b0c518e38e3fdad5b56e80e3b819889603022ce46270d13deda223380 SHA1: 258bde6eee495816d1f08cac695a79ef63ad5c7d MD5sum: dafae6c0efb6cf55a5b3142e89db6882 Description: Library to read/write EEG data file formats (debugging symbols) xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)). . The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future. . This package provides the debugging symbols of the library. Package: lua-cnrun Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 125 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_2.1.0-1~nd+1_amd64.deb Size: 42098 SHA256: 2c36e432dee8a33ed3e3edf244133a8e3ee504ebf2689bcb4cd2cea4c3c3aed5 SHA1: 2ea1fea211ef54b7e03903e8a2ca415f44f7e782 MD5sum: 59c4c0a005e08e25ac8431288cb6d587 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: lua-cnrun-dbgsym Source: cnrun Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 300 Depends: lua-cnrun (= 2.1.0-1~nd+1) Homepage: http://johnhommer.com/academic/code/cnrun Priority: extra Section: debug Filename: pool/main/c/cnrun/lua-cnrun-dbgsym_2.1.0-1~nd+1_amd64.deb Size: 274786 SHA256: 79cb4343c08be682b26dc747fafbb6aac744009bea1e81e8b452f5eb6537a18d SHA1: f92d32a818770f588ed30d28405ff4f4dd2c7eea MD5sum: 23fb3346b82607f2f5dfa2c871981cec Description: Debug symbols for lua-cnrun Auto-Built-Package: debug-symbols Build-Ids: 3979ae39305d8fff87c59a094f5610d005feea95 Package: matlab-support-dev Source: matlab-support Version: 0.0.21~nd+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~nd+1_all.deb Size: 7512 SHA256: 42b003748752925c2ffbeacc36fadfbaa2db1073c5e6db92ccbca5f4e359be07 SHA1: 16e884448f647ec24616bfb561e976f3a01830bf MD5sum: eb6d5800a7effbe0135889275e6d7d53 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: mia-tools Source: mia Version: 2.0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8465 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd+1), libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-serialization1.54.0, libboost-system1.54.0, libboost-test1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.36.2), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.6), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd+1_amd64.deb Size: 1446164 SHA256: 20d1d2de70e82d65fd34e4b09b6db9301f79b9e111751c75122a16e521b960a7 SHA1: 54b7d4c2c84ef8d488ecd4a057eb06c437467073 MD5sum: 194a4865fc8af90e1216a99d4d968275 Description: Command line tools for gray scale image processing Command lines tools to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-dbg Source: mia Version: 2.0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29939 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd+1_amd64.deb Size: 27666718 SHA256: b600a5d9f14a1adf4ae75271b23874131880c8359bd738d71bf26478828c4a05 SHA1: efad2e85a52d7bdc26c9bc2a2013340f9034a3e4 MD5sum: 11f51ea56e54e673c71550507a86dddf Description: Debugging information for the MIA command line tools Debug information for the MIA command lines tools. These tools provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1145 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd+1_all.deb Size: 78990 SHA256: 51558554d8205e9835e53d3e5a38f2f9da5222d20da8798e81788580b9265918 SHA1: 356c818a63c03035944b985e1419040aaa7a2278 MD5sum: c9a4f6051dec225ca8244a32e5feb682 Description: Cross-referenced documentation of the MIA command line tools Cross referenced documentation of the command line tools and plug-ins that are provided by the MIA gray scale image processing tool chain. These lines tools to provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes interactively from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statistics over images. Package: mialmpick Version: 0.2.10-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.4-2~), libglib2.0-0 (>= 2.31.18), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd+1_amd64.deb Size: 69114 SHA256: 0ca279efc264e8a9070f9578964e1b2442827fd0c9f80fd091d95d05ebf7c43d SHA1: 11bb87f9082b605f26177e6d731471d78cdf0840 MD5sum: 0bd5fde3d31246d88bb1379f84cff283 Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 194 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd+1_amd64.deb Size: 165616 SHA256: c308e70402b0faecad2d5907f85dedf980828049c7cc293164b097dfa939d0c6 SHA1: e614f3e0bd426311cc8b646f1e7e5964a6398d50 MD5sum: 42ac5022034219831c47f65b0fcdf2d7 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Package: mitools Source: odin Version: 1.8.8-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 8286 Depends: neurodebian-popularity-contest, libblitz0ldbl, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), liblapack3 | liblapack.so.3, libnifti2, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.6.1), libqwt5-qt4, libstdc++6 (>= 4.9), libvtk5.8, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.8-1~nd+1_amd64.deb Size: 2032596 SHA256: aed807c6b85a04561f8a2610b6c84fe029d6ed0d83ff7be2246141ecea3fd054 SHA1: 5517ddff0365f4296aa1c226a78b9f72c92020e6 MD5sum: d265ef7f54c77e8cbf9740923abd6c34 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mriconvert Version: 1:2.0.8-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5740 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), libwxbase3.0-0 (>= 3.0.2), libwxgtk3.0-0 (>= 3.0.2) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.8-1~nd+1_amd64.deb Size: 842288 SHA256: ccad6b0379034001c5af4d4da031d6b598d8ac23bfd40185a44a27cf8d9a68c9 SHA1: a04bc944c2fdd7ff217fcd629d5da739691e78ab MD5sum: e688758621c38cda989cc72ef6622216 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~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 16525 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~nd+1_amd64.deb Size: 2269718 SHA256: 325ad6020709a12fc254d12ccffd837bf3502873e7591323f57077ab058e3269 SHA1: 5633ac28535a6a5c6ff00eb35303b68bc31eba88 MD5sum: 132f51a05f07fa4c84c1448219545d3c 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~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1710 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd+1_all.deb Size: 1661584 SHA256: a8efc9af5e1b70f033b6614058ec4922357638a5a358d3150ef484c10bbf345c SHA1: 647ab896ea9b9c2d8c1a02661725b8aaea9c1390 MD5sum: 73a4aef17ff9025d2365cb04480512ec 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~nd+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~nd+1_all.deb Size: 580068 SHA256: a8ca01a92a6803851700c880726c6e0eeaed4ada4184718c44c07e41c600816e SHA1: 3ca8963aadc1f5609e9c52a9287c012fa659b3e6 MD5sum: 0d1df88b9a4fd32bf31c1c184c0cbc17 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: 0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: neurodebian-popularity-contest, num-utils, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.2-1~nd+1_all.deb Size: 637206 SHA256: 30a53d376792e4c3a86b72073f5d992bf7785e4adeac0d734b16a3f3445d571e SHA1: 937cfe6d76f82623163780047690a52977e5b7e2 MD5sum: 24f9bd4c5329daf7c6c167998750a077 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: mrtrix Version: 0.2.12-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 9210 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.14), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.11), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libice6 (>= 1:1.0.0), libpango-1.0-0 (>= 1.14.0), libpangocairo-1.0-0 (>= 1.14.0), libpangoft2-1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.27.1), libpangox-1.0-0 (>= 0.0.2), libsigc++-2.0-0c2a (>= 2.2.0), libsm6, libstdc++6 (>= 4.6), libx11-6, libxmu6, libxt6, zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.12-1~nd+1_amd64.deb Size: 1356374 SHA256: 8c7c224cbaaba84d9875f8a7d051564ef29a1623a9f0bafe2b54f727321e88c0 SHA1: cf487d588a2c5bf5fa3953eac367201287197756 MD5sum: 502ab2c4f2fd6f7232bc65a81fe353ac Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.12-1~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3528 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.12-1~nd+1_all.deb Size: 3199776 SHA256: 4abb82cb1f240754d3bead18288426bdd8862b186cbca4ace358b42c97a1dfe7 SHA1: b0e995bc80a61c78c328a8a3d226cb35155ebd31 MD5sum: 6e421c1e6eb30afffc6a98884e70112e Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: mwrap Version: 0.33-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 271 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Recommends: octave Homepage: http://www.cims.nyu.edu/~dbindel/mwrap/ Priority: extra Section: devel Filename: pool/main/m/mwrap/mwrap_0.33-1~nd+1_amd64.deb Size: 218906 SHA256: 1e7364b108592a508418a3f09781ef0ef5c31b2cfd8e7276c68a62cd5efe494e SHA1: 59d84dfe7ff2af2ca919af5eda52dcc221cb42b5 MD5sum: b8046f75ed3fd3b5483d95b2b6b928db Description: Octave/MATLAB mex generator MWrap is an interface generation system in the spirit of SWIG or matwrap. From a set of augmented Octave/MATLAB script files, MWrap will generate a MEX gateway to desired C/C++ function calls and Octave/MATLAB function files to access that gateway. The details of converting to and from Octave/MATLAB's data structures, and of allocating and freeing temporary storage, are hidden from the user. Package: ncdu Version: 1.11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libncursesw5 (>= 6), libtinfo5 (>= 6) Homepage: http://dev.yorhel.nl/ncdu/ Priority: optional Section: admin Filename: pool/main/n/ncdu/ncdu_1.11-1~nd+1_amd64.deb Size: 40020 SHA256: b89cbbc9153c1ae849a6173a8f3fef6d42f741da850e0110e0e330b53ddf0afe SHA1: 8ee0fe929504001c9a8a3a6bb4564ae3905232f1 MD5sum: 5ce792627c004241c9cbc66f12f0eb0e Description: ncurses disk usage viewer Ncdu is a ncurses-based du viewer. It provides a fast and easy-to-use interface through famous du utility. It allows one to browse through the directories and show percentages of disk usage with ncurses library. Package: ncdu-dbgsym Source: ncdu Version: 1.11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 73 Depends: ncdu (= 1.11-1~nd+1) Homepage: http://dev.yorhel.nl/ncdu/ Priority: extra Section: debug Filename: pool/main/n/ncdu/ncdu-dbgsym_1.11-1~nd+1_amd64.deb Size: 53228 SHA256: fe6d147d610c8f21d0b5f0f48ff54191a69b43dc7cbbe4de9ae593929e830b78 SHA1: fa779590ee96155ca573f5ded3ae0ce324b3bce0 MD5sum: ff908b827f905bdbb9340c38ef3ca135 Description: Debug symbols for ncdu Auto-Built-Package: debug-symbols Build-Ids: 22326ca39404aa35f17095fcbf06e7af9707b95b Package: netselect Version: 0.3.ds1-25~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), 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~nd+1_amd64.deb Size: 31404 SHA256: fdb097bf87bc11e47a533b71bd36b88537df4e457f1ee9d61922e333eb4f6136 SHA1: 412307fe6f842e9ff44121d862908168f4481713 MD5sum: 3340bc6ab36a9c6c57522b4669d3ea90 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd+1_all.deb Size: 16790 SHA256: 97280acc29ad04928a2171d14f076325e227c153af82af6002a68cc2f04cdc97 SHA1: d5262a5b9d1465c562d40e782a920ff0b19c6c0e MD5sum: 22f92cf44ff49488ceeed27c77ee0d4e 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: 0.37.5~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 91 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_0.37.5~nd+1_all.deb Size: 34540 SHA256: 9cdc50fbfd82c854d6405d91450f466fbc870815d1dfee8ff883cdb67504cfa2 SHA1: b7d1177788da779db6d063c3cbe5e09c985fcb2b MD5sum: 803c44fb6ec128023307cb68bed1b81a 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: 0.37.5~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: gnupg2 | gnupg, dirmngr 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_0.37.5~nd+1_all.deb Size: 10336 SHA256: 4a91ea7e4b52196a2d3f8dc5c0364eef3d212a1c73da2e7e3edbd1e3a7cec4f3 SHA1: bd51fee3598ad553499e3aa6b792b738c22a2486 MD5sum: 7a1b106f528e632a441d6bc1b68d48a5 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: 0.37.5~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.5~nd+1_all.deb Size: 116328 SHA256: 668ad8dfceacac066cc00cafb1bcc71ea387a32894f90d43737502ae2dee95ad SHA1: d7e25d3efc1abf2ed20404727e215e539eb12178 MD5sum: 374bbd87451999747ed09fc2e71b0507 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: 0.37.5~nd+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_0.37.5~nd+1_all.deb Size: 32764 SHA256: c21052322b7bcdcc789d14c5b6f2769a1dd12b7058ce5e583fd4e9ed86498681 SHA1: f890ebe869538064ae046c0d3b7591e00c9cbd31 MD5sum: 130b23ca9a2d228c73abcb13991e0636 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-guest-additions Source: neurodebian Version: 0.32~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd+1_all.deb Size: 14030 SHA256: a7b1c22382ef38bcb02197d3f88ef51f8e1f2f5152ad7c18e6d040b6803d3c9f SHA1: 0b8bca805ed756dadec92b4e76d3701ed9b400c6 MD5sum: 6bd47ac8ce904b7e445aca38e8d806a8 Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.32~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd+1_all.deb Size: 7418 SHA256: 6a6686a0d7186992aeeb0520359ca34c15210792010af928b382b5f4caa888a7 SHA1: 89cec44d84d971babd0be50534f2560073246957 MD5sum: 778a5b4f7b7cd1933cfb8808beedb823 Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.5~nd+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_0.37.5~nd+1_all.deb Size: 12366 SHA256: 41ad7493a475c34c4bc292607d74a8fcc646e8b034efdc360fee7636429f16e3 SHA1: 4c9d5b969448484ec651951d2019b4a1780c8d86 MD5sum: f25cf019eb2f9781fee16fc3fab7a1e8 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: nifti-bin Source: nifticlib Version: 2.0.0-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 176 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-2~nd+1_amd64.deb Size: 55346 SHA256: 34bd3593cbbb7dc00560fb866c15d066c88511a9b50091b3f68e9e6f1312b29e SHA1: e4d5d44eb8a440ee7621c0a2a3dea890930c1bae MD5sum: 1380ede4b4b9b911a9c15d9811cfdf58 Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: nifti2dicom Version: 0.4.11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2317 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdcm2.6, libinsighttoolkit4.9, libstdc++6 (>= 5.2), nifti2dicom-data (= 0.4.11-1~nd+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.11-1~nd+1_amd64.deb Size: 348770 SHA256: c61b0bb4251bd70a8741a54eaade906ab99d590fc3019bfb134be935e0b06c9c SHA1: e8f3db0d41cd2d929d0b99c30828f0d172419e1d MD5sum: a0ffde12264cc096e64f2192f03d9ff6 Description: convert 3D medical images to DICOM 2D series Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package includes the command line tools. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.11-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 647 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.11-1~nd+1_all.deb Size: 616676 SHA256: b4e0d532aed4c6f71600c96de5ce5c284f2dcff6142c17c104b285fb5c608ce0 SHA1: 2dd827d7ffea474a3b83920ce6cebe36e28d55c9 MD5sum: 8df5623f6d0fe2926cf1c6c32ebe7a80 Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nifti2dicom-dbg Source: nifti2dicom Version: 0.4.11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38399 Depends: neurodebian-popularity-contest, nifti2dicom (= 0.4.11-1~nd+1) | qnifti2dicom (= 0.4.11-1~nd+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: extra Section: debug Filename: pool/main/n/nifti2dicom/nifti2dicom-dbg_0.4.11-1~nd+1_amd64.deb Size: 6171602 SHA256: 7747d46367b197c05988856cecc1b30acb32662fc94f0ce94f0e4cf2f3694127 SHA1: be099217b4d464366bcfabb3a2db3ac27c811bd3 MD5sum: ac7d648e25e0609a9a2be9ed6f07a875 Description: convert 3D medical images to DICOM 2D series (debug symbols) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the debugging symbols necessary to debug crashes in nifti2dicom. Package: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 36 Depends: python-nibabel (>= 1.0.0), python-nipy (>= 0.1.2+20110114), python-dipy (>= 0.5.0), python-nipype (>= 0.3.3), python-nitime (>= 0.2) Suggests: python-mvpa, psychopy Homepage: http://www.nipy.org Priority: extra Section: python Filename: pool/main/n/nipy-suite/nipy-suite_0.1.0-2_all.deb Size: 3898 SHA256: 882c8580ebd2d458a92f8d851d1ec9291fecf05f6ed98a8b754eb831c95368c8 SHA1: 6501d1d201160520f5aad29d0f9007c17b7d9778 MD5sum: eb090e568264d2f439892bcb98485b8c Description: Neuroimaging in Python NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. nipy-suite is a metapackage depending on the projects developed under NiPy project umbrella, such as - nibabel: bindings to various neuroimaging data formats - nipy: analysis of structural and functional neuroimaging data - nitime: timeseries analysis - dipy: analysis of MR diffusion imaging data - nipype: pipelines and worfklows Package: nipy-suite-doc Source: nipy-suite Version: 0.1.0-2 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 32 Depends: python-nibabel-doc (>= 1.0.0), python-nipy-doc (>= 0.1.2+20110114), python-dipy-doc (>= 0.5.0), python-nipype-doc (>= 0.3.3), python-nitime-doc (>= 0.2) Suggests: python-mvpa-doc Homepage: http://www.nipy.org Priority: extra Section: doc Filename: pool/main/n/nipy-suite/nipy-suite-doc_0.1.0-2_all.deb Size: 2250 SHA256: 54985bd9d6eaa352608b357f2deeb066bd2ac12d3c2e463082f5d9178701bbad SHA1: 5d2f5e94ff6b7ff737fe966f4a2e5ff67df93cca MD5sum: 37d2f8b6b6d203edf208afb0cdb56fa3 Description: Neuroimaging in Python -- documentation NiPy is a comprehensive suite of Python modules to perform analysis of Neuroimaging data in Python. . nipy-suite-doc is a metapackage depending on the documentation packages for NiPy projects. Package: nuitka Version: 0.5.24.4+ds-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3102 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.24.4+ds-1~nd+1_all.deb Size: 639814 SHA256: e8f28472942046c5164950301f12bcd2457990ed36eaf7f528b82520737e1985 SHA1: b02b97edabe644d488ae348dcb785609a4e26b1a MD5sum: d7d620051a5feff04d3d57496a09df8b Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: numdiff Version: 5.6.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 857 Depends: neurodebian-popularity-contest, libc6 (>= 2.3), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.6.0-1~nd+1_amd64.deb Size: 597428 SHA256: 0ee3e2dd13cb18e6983632a6dafea4c54b85743820dc5ecf4a4c664292b54ce4 SHA1: 48d796409c1304a056ab84175b8f2f6d9f4e9eeb MD5sum: 2e4fbf96f33b128a979b42ea1c583c08 Description: Compare similar files with numeric fields. Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libcholmod2.1.2, libgcc1 (>= 1:4.1.1), liboctave2, libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd+1_amd64.deb Size: 19868 SHA256: 79d43922d3f0a85feb48937d411c600f9fcd68d353c3b9cbc1139469aee60205 SHA1: fa2f83deb862d98607982bfb79fcf919f258cba0 MD5sum: e91ea75cc961e2b5b0944f1ea2316e5b Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.2-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 317 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdf0, liboctave1, libstdc++6 (>= 4.6) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.2-2~nd+1_amd64.deb Size: 124064 SHA256: c1d8fc2849edfc0783ec9188622b178e6238a7475dd1aff75edc62f434205ac4 SHA1: d913b820999d92da0967a60552238014a152b34e MD5sum: 572cb60392bc7a8fb5b105a1efa029c5 Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. Package: octave-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd+1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), liboctave1 (>= 3.6.2), libstdc++6 (>= 4.1.1) Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: math Filename: pool/main/n/nlopt/octave-nlopt_2.4.1+dfsg-1~nd+1_amd64.deb Size: 25770 SHA256: a7aeba5952aa6077cef815841908cd77d02342903ee2746f8899a0fcb57a0261 SHA1: e00515c811f011b9d2f966005b0b962c11f4372e MD5sum: 80420741c26e4feb07711ef9796fded6 Description: nonlinear optimization library -- GNU Octave package NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the module for the GNU Octave. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4455 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgomp1 (>= 4.2.1), libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), liboctave3v5, libopenal1 (>= 1.14), libpciaccess0 (>= 0.10.7), libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3, libxi6 (>= 2:1.2.99.4), libxml2 (>= 2.6.27), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1), psychtoolbox-3-lib (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1_amd64.deb Size: 878720 SHA256: 46c8d71ecedd02ffd2dc0c8c1a03a16de3d33c90ec54723dd62cc61598b39951 SHA1: 713c26f664949c2ccceb3a9621bb45e99d0844e4 MD5sum: 9d4bfefd4bf48dff51b17ef3418f7c10 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: odin Version: 1.8.8-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4451 Depends: neurodebian-popularity-contest, libblitz0ldbl, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libgcc1 (>= 1:4.1.1), liblapack3 | liblapack.so.3, libnifti2, libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, mitools (= 1.8.8-1~nd+1), zlib1g (>= 1:1.1.4), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.8-1~nd+1_amd64.deb Size: 1278988 SHA256: 5740c13bb351a33d0e693a88c021d2d6de2aab6f102a7f3ed59d77f603ca8297 SHA1: 5d878f2d3b5f075b7313adc240956b826aa07348 MD5sum: 3f3c6fa3b42e65daaff1e74c13a15b54 Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~sid.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~sid.nd1_all.deb Size: 34360 SHA256: 15e2e7aefc8b1af85c120f648897950db56fb71fe5999c5a3ca51b1c70bc0fb4 SHA1: 84e8c88b4d56f44c987808ba5c54b1799a0403ee MD5sum: 0eaf72ffeedd568782315315e95b4dfe Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 644 Depends: neurodebian-popularity-contest, libatlas3-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.1.1) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-4~nd+1_amd64.deb Size: 198490 SHA256: a3a1ab01dfe4e33444b79e1b6e9e2e37ed5ce4c3189a193a2ea8dda9541cca17 SHA1: 31bd8b26a51d103fed134aab9575535f6808dada MD5sum: 81725a3c6a1d52cd2cf43926a7149093 Description: openmeeg library -- command line tools OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides command line interface to openmeeg functionality. Package: opensesame Version: 0.27.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26639 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd+1_all.deb Size: 24612138 SHA256: b223ca6a17d69da2863cd4ddba9b499d0a3b8b554862fe6623ec17c63eab74a4 SHA1: bf7885235942fade9f1256a1968979918212a7bf MD5sum: daca1a779d091bd428ceb9f90818b04d Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Package: openstack-pkg-tools Version: 52~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 191 Depends: neurodebian-popularity-contest, autopkgtest, libxml-xpath-perl, madison-lite, pristine-tar Priority: extra Section: devel Filename: pool/main/o/openstack-pkg-tools/openstack-pkg-tools_52~nd+1_all.deb Size: 52240 SHA256: ba46048f89647d249f8ddfb0e4ce6f3adcb9c6979658840004a8722b471638af SHA1: c636a2b5d00d5966d376afd02bd6f1faace38cc4 MD5sum: ecacd02d3a6cf711d4620b0a5f111440 Description: Tools and scripts for building Openstack packages in Debian This package contains some useful shell scripts and helpers for building the Openstack packages in Debian, including: . * shared code for maintainer scripts (.config, .postinst, ...). * init script templates to automatically generate init scripts for sysv-rc, systemd and upstart. * tools to build backports using sbuild and/or Jenkins based on gbp workflow. * utility to maintain git packaging (to be included in a debian/rules). . Even if this package is maintained in order to build OpenStack packages, it is of a general purpose, and it can be used for building any package. Package: openvibe-bin Source: openvibe Version: 0.14.3+dfsg2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1205 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd+1), openvibe-data (= 0.14.3+dfsg2-1~nd+1), libboost-regex1.49.0 (>= 1.49.0-1), libboost-thread1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.18.0), libopenal1, libpango1.0-0 (>= 1.14.0), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Homepage: http://openvibe.inria.fr Priority: extra Section: science Filename: pool/main/o/openvibe/openvibe-bin_0.14.3+dfsg2-1~nd+1_amd64.deb Size: 447970 SHA256: 7b2d912cd8599f4c61f289666ae509a71f31ccc2ab571d768255a80a9f6b7cd7 SHA1: ae83c9f3d9582f5a8af3f3c08ce4acb6b239222c MD5sum: 25b942fef2973c820b235f5333ae2f15 Description: Software platform for BCI (tools and demos) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains differents executable including acquisition server, tools and demos. Package: openvibe-data Source: openvibe Version: 0.14.3+dfsg2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9328 Depends: neurodebian-popularity-contest Homepage: http://openvibe.inria.fr Priority: extra Section: science Filename: pool/main/o/openvibe/openvibe-data_0.14.3+dfsg2-1~nd+1_all.deb Size: 2024448 SHA256: 577686111aba7c2eafbe4c25ab1052d26958bd64471319884a324b9825c07d16 SHA1: 2ab042fb217b2ffec6f55b478cf1e8405786832a MD5sum: 8d7802d259052ef28a0dd2febd7fa4e9 Description: Software platform for BCI (Data files) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the data files. Package: openvibe-dev Source: openvibe Version: 0.14.3+dfsg2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 715 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd+1) Homepage: http://openvibe.inria.fr Priority: extra Section: libdevel Filename: pool/main/o/openvibe/openvibe-dev_0.14.3+dfsg2-1~nd+1_amd64.deb Size: 100676 SHA256: bc2a9e83737bc399853aea7d8d904fe3553ae038a23a31be11d48ee60f9095b3 SHA1: 82cac7a2e87426936e703b7f53e9082b662779ef MD5sum: a61190af7fb5d3c4b8a1b31855536ea7 Description: Software platform for BCI (development files) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the development files. Package: openvibe-libs Source: openvibe Version: 0.14.3+dfsg2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2229 Depends: neurodebian-popularity-contest, openvibe-data (= 0.14.3+dfsg2-1~nd+1), libc6 (>= 2.4), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libogre-1.7.4, libstdc++6 (>= 4.6), libx11-6 Homepage: http://openvibe.inria.fr Priority: extra Section: libs Filename: pool/main/o/openvibe/openvibe-libs_0.14.3+dfsg2-1~nd+1_amd64.deb Size: 638282 SHA256: 7d9b0397df7b057acd63c673fe9a190343ff2f65262a21d6228adf7ffd88c721 SHA1: 41160ede82b716c1204c7c0cb7e1b900e0f9ca4c MD5sum: 41bba6be14661098b6f62fff36834075 Description: Software platform for BCI (shared libraries) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the shared libraries. Package: openvibe-plugins Source: openvibe Version: 0.14.3+dfsg2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5663 Depends: neurodebian-popularity-contest, openvibe-libs (= 0.14.3+dfsg2-1~nd+1), openvibe-data (= 0.14.3+dfsg2-1~nd+1), libalut0 (>= 1.0.1), libboost-regex1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.18.0), libitpp7, liblapack3 | liblapack.so.3 | libatlas3-base, libopenal1, libpango1.0-0 (>= 1.14.0), libstdc++6 (>= 4.6), libvorbisfile3 (>= 1.1.2), libvrpnserver0, libx11-6 Homepage: http://openvibe.inria.fr Priority: extra Section: libs Filename: pool/main/o/openvibe/openvibe-plugins_0.14.3+dfsg2-1~nd+1_amd64.deb Size: 1663708 SHA256: d8bbadfadaeb5c6c899d1e25d7eadcdf16e2ef4b0e27dfc9258e6836288a83f4 SHA1: 2982a5ff6b380cb145d1c33370cf993fc618e5fb MD5sum: b6d23c4db7d32d9ae3a85798dbc838d1 Description: Software platform for BCI (plugins) OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI). OpenViBE is a software for real-time neurosciences (that is, for real-time processing of brain signals). It can be used to acquire, filter, process, classify and visualize brain signals in real time. . The graphical user interface of OpenViBE is simple to access and very easy to use for creating BCI scenarios and saving them for later use. In the designer, the available functions are listed in the right-hand window. The user simply drags and drops the selected functions in the left-hand window. He can then connect boxes together to add processing steps to the scenario being created. Lastly, the application is started by pressing the Play button to run the BCI. . OpenViBE is a library of functions written in C++ which can be integrated and applied quickly and easily using modules. The platform's main advantages are modularity, portability, availability of different tools for different types of user, including programmers and non-programmers, superior code performance and compatibility with virtual reality technologies. . The software also offers many 2D and 3D visualization tools to represent brain activity in real time. It is compatible with many EEG- and MEG-type machines because of its generic acquisition server. . OpenViBE offers many pre-configured scenarios for different applications including mental imagery, neurofeedback, P300 signals, etc... . This package contains the plugins. Package: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 19847 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph99, libopenwalnut1, libstdc++6 (>= 4.6) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.4.0~rc1+hg3a3147463ee2-1~nd+1_amd64.deb Size: 3317846 SHA256: 5e60749d27d869ed5930886f32730c10bfe434ee0b2167f6c1186817e3e1ff08 SHA1: d4abb6e549204d1e142fc4a0e66722f85d7a4b34 MD5sum: ff29e1b180dbf91d513f1f39ec4a3423 Description: Loaders, algorithms and visualization modules for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1955 Depends: neurodebian-popularity-contest, libboost-filesystem1.54.0, libboost-program-options1.54.0, libboost-regex1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libopenscenegraph99, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4 (>= 2.1.0~2011week13), libstdc++6 (>= 4.6), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd+1_amd64.deb Size: 733878 SHA256: 74016e01f29b41dd10802f60a43b79a1c43e4cafd5d7eb8c68dde0c0a2263280 SHA1: f5e02833140da1a64f4236f35004c78eef4f516f MD5sum: 5a0fddba8ef9cfac852a186fbacf71b7 Description: Qt based user interface for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: p7zip Version: 16.02+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 866 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5) Suggests: p7zip-full Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip_16.02+dfsg-1~nd+1_amd64.deb Size: 350428 SHA256: 6cafa5c7d78df44931b4e45017413c67d838aa0a3de452d96f6dc8bc42924335 SHA1: 3bf2ff8c33ba9be8872a1008bd0f900996acf50e MD5sum: 944e5d212f60b1cf79c5e407fe392d5c Description: 7zr file archiver with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip provides: - /usr/bin/7zr a standalone minimal version of the 7-zip tool that only handles 7z, LZMA and XZ archives. 7z compression is 30-50% better than ZIP compression. - /usr/bin/p7zip a gzip-like wrapper around 7zr. . p7zip can be used with popular compression interfaces (such as File Roller or Nautilus). . Another package, p7zip-full, provides 7z and 7za which support more compression formats. Package: p7zip-dbgsym Source: p7zip Version: 16.02+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2490 Depends: p7zip (= 16.02+dfsg-1~nd+1) Homepage: http://p7zip.sourceforge.net/ Priority: extra Section: debug Filename: pool/main/p/p7zip/p7zip-dbgsym_16.02+dfsg-1~nd+1_amd64.deb Size: 2348626 SHA256: 08ceef3a36d62535968aa4d018fa9563d0e5444d4f879dfb53097c8d97ed28cd SHA1: c2cb48c11f58003c381e2579f640e53a8c1e3560 MD5sum: af114f943c7938369b9b58ad5c187bab Description: Debug symbols for p7zip Auto-Built-Package: debug-symbols Build-Ids: 8f2b3d75b6afbc97e43eeaad2cc9b112efd592bf Package: p7zip-full Source: p7zip Version: 16.02+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4215 Pre-Depends: dpkg (>= 1.17.13) Depends: neurodebian-popularity-contest, p7zip (= 16.02+dfsg-1~nd+1), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5) Suggests: p7zip-rar Breaks: p7zip (<< 15.09+dfsg-3~) Replaces: p7zip (<< 15.09+dfsg-3~) Homepage: http://p7zip.sourceforge.net/ Priority: optional Section: utils Filename: pool/main/p/p7zip/p7zip-full_16.02+dfsg-1~nd+1_amd64.deb Size: 1160186 SHA256: 8e169e72d206e3f08fd07c7ac41a0de5b8d0398f41e651917023ddc57539cac6 SHA1: 3b78740aef2cf19758601bf27c79d679dd67c2d9 MD5sum: be12fba36c666e3b7f0da10930dd102e Description: 7z and 7za file archivers with high compression ratio p7zip is the Unix command-line port of 7-Zip, a file archiver that handles the 7z format which features very high compression ratios. . p7zip-full provides utilities to pack and unpack 7z archives within a shell or using a GUI (such as Ark, File Roller or Nautilus). . Installing p7zip-full allows File Roller to use the very efficient 7z compression format for packing and unpacking files and directories. Additionally, it provides the 7z and 7za commands. . List of supported formats: - Packing / unpacking: 7z, ZIP, GZIP, BZIP2, XZ and TAR - Unpacking only: APM, ARJ, CAB, CHM, CPIO, CramFS, DEB, DMG, FAT, HFS, ISO, LZH, LZMA, LZMA2, MBR, MSI, MSLZ, NSIS, NTFS, RAR (only if non-free p7zip-rar package is installed), RPM, SquashFS, UDF, VHD, WIM, XAR and Z. . The dependent package, p7zip, provides 7zr, a light version of 7za, and p7zip, a gzip-like wrapper around 7zr. Package: p7zip-full-dbgsym Source: p7zip Version: 16.02+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 11417 Depends: p7zip-full (= 16.02+dfsg-1~nd+1) Homepage: http://p7zip.sourceforge.net/ Priority: extra Section: debug Filename: pool/main/p/p7zip/p7zip-full-dbgsym_16.02+dfsg-1~nd+1_amd64.deb Size: 10772908 SHA256: dbb55230894371c82b2176253b44a524e049dcb10370e74fb762f62ab387657e SHA1: b4ddcb59b79bc3ebd2a977f0d39baa58987c44f9 MD5sum: deeb5a433dcafb96a1bba25f72c1e4da Description: Debug symbols for p7zip-full Auto-Built-Package: debug-symbols Build-Ids: 0d41268ff911424cc40f64d4126372f41eeb5c46 aa9a2422486fcd1ae137c8598dbf0fae624ff538 ea98c1501f1e0276f6fcdf76168bdf1c1b1f905b eac14f194f6028c2bcda1acdf84c016793ce54b4 Package: packaging-tutorial Version: 0.8~nd0 Architecture: all Maintainer: Lucas Nussbaum Installed-Size: 1550 Priority: extra Section: doc Filename: pool/main/p/packaging-tutorial/packaging-tutorial_0.8~nd0_all.deb Size: 1488332 SHA256: 491bc5917f698fee06888998e8a295a6caac2950148bb160b457aff72437eadb SHA1: c5d75d04b01f681ead660ce8d8fe068ab887fba0 MD5sum: 8fbf7c362fd4091a78c50404eb694402 Description: introduction to Debian packaging This tutorial is an introduction to Debian packaging. It teaches prospective developers how to modify existing packages, how to create their own packages, and how to interact with the Debian community. In addition to the main tutorial, it includes three practical sessions on modifying the 'grep' package, and packaging the 'gnujump' game and a Java library. Package: prov-tools Source: python-prov Version: 1.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, python3:any (>= 3.3~), python3-prov (= 1.4.0-1~nd+1) Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/prov-tools_1.4.0-1~nd+1_all.deb Size: 6464 SHA256: 6ffeb72e63c20f41fc6cb210bf9894c26114ab31bf3492f72a094b0d0385dc1b SHA1: b9f38a334042f3c2bce65f745929341ea19e3d2f MD5sum: 531be97829c3ba53d6be585b9963f7dd Description: tools for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the command-line tools for the prov library. Package: psychopy Version: 1.83.04.dfsg-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15088 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-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.83.04.dfsg-2~nd+1_all.deb Size: 6133504 SHA256: 5a51428a188f230695b67857a223d408641d3a5a349bf3f0737dfdabe13e8d8b SHA1: 89e33dba2565b3a998863ab68559d263a0b99491 MD5sum: 9aa8755ac3045cc18cfeb071ba269bcd Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253898 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1_all.deb Size: 24153226 SHA256: bb28c91d9e75bfac98426b6d5cb626435437b3567fe47f76d71b4a58cc73c7cf SHA1: 65f346510259f8fa74bf516416a8c3bc1f21ad03 MD5sum: 7cba0bf5ab43e1a9ae106e788cf28a9d Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18658 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1_amd64.deb Size: 1262628 SHA256: 34e33d2d71be412240c07447eb6a219caaa9e558eb654a26e7021b4a8a6ef1f3 SHA1: 2fdbe3683894266af4829af885b19132129c183b MD5sum: e653a2fc6405cc409efc8e4e49492d5e Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 190 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libfontconfig1 (>= 2.11), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 5) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd+1_amd64.deb Size: 73068 SHA256: d911e452a2b98336ef535e20cdc8fcc5f35130f2ea089823004b69e86839f969 SHA1: 084ccd6f2f0dedf88ae1d2d494e66cce9d5593c9 MD5sum: f0822b9cd8541894b1ce026dd3aef430 Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: pypy-hypothesis Source: python-hypothesis Version: 3.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 411 Depends: neurodebian-popularity-contest, pypy-enum34, pypy Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/pypy-hypothesis_3.6.0-1~nd+1_all.deb Size: 95378 SHA256: e01c780069e5b2e3514b2da1b13ff19bcdc4734e83086af84a66ae7d4840d3b3 SHA1: bbddd3788c3c13c8ce80bfa98a2b3af3a8a02595 MD5sum: 2237ede9a3edd4b7a4db4608a689b0d6 Description: advanced Quickcheck style testing library for PyPy Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the PyPy module. Package: pypy-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, pypy Suggests: pypy-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/pypy-pkg-resources_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 111974 SHA256: b78188cea2681341ce323fbd36e9d12817a54e509566b931106d6954205b46ff SHA1: af3ee3c64c7baef47af10db015369be678bbd30d MD5sum: 8e3e882391ac969e4cc4e2fe5f3afd08 Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: pypy-py Source: python-py Version: 1.4.31-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 Depends: neurodebian-popularity-contest, pypy, pypy-pkg-resources Suggests: subversion, pypy-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/pypy-py_1.4.31-2~nd+1_all.deb Size: 82242 SHA256: fb104d8144ba49ce0749d43b82315c43a3ba8d91cc40f7cd2b3f6390ab87abfb SHA1: 83c9a768d5b8e4c60277d3613096311974a8bb88 MD5sum: a94959cf70b61f84d403ce89e57057c3 Description: Advanced Python development support library (PyPy) 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 PyPy 2 modules. Package: pypy-pytest Source: pytest Version: 3.0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 644 Depends: neurodebian-popularity-contest, pypy-pkg-resources, pypy-py (>= 1.4.29), pypy Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/pypy-pytest_3.0.4-1~nd+1_all.deb Size: 180974 SHA256: ffa719a5cfa6c4a0dc367f85adc059771ac0594dc9107b6767d7a91915480578 SHA1: 371068c9e2a074171a040842ba6c39e00b3f8deb MD5sum: eba9e00726fb95fbbbe9f769155368e9 Description: Simple, powerful testing in PyPy 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 PyPy module and the py.test-pypy script. Package: pypy-setuptools Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 431 Depends: neurodebian-popularity-contest, pypy-pkg-resources (= 20.10.1-1.1~bpo8+1~nd+1), pypy Suggests: python-setuptools-doc Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/pypy-setuptools_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 121856 SHA256: 35889dc13125b06712f81173a5ac6d0fa62544a0d9ad787c35746c3808762ab6 SHA1: 73a775f25eae45257fcefffed988ef04fecf07db MD5sum: 0efb61e2b9546a7383e2bf03545af2dc Description: PyPy Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: python-argcomplete Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 113 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd+1_all.deb Size: 25852 SHA256: e961c7c94be985b71d0b9c6496f2342ca95aed4bec75d0a92d8c28837deb3390 SHA1: f14e66ab17ffd8ee30482d8a7d43d51871e8845c MD5sum: ac0f6a6a42aabd4109473218a09e9e21 Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-biosig Source: biosig4c++ Version: 1.4.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 203 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~nd+1_amd64.deb Size: 42642 SHA256: 27376b4ff82aca7b9a6e2f8b0cb786b42d57fc3035f384e1e5243b1d7933ae6b SHA1: d9f21b9a13b0c862310a93e865e921b1d56160e5 MD5sum: c9cf5a3c75f1e0f4ab69e9e9d45bd162 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-boto3 Version: 1.2.2-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 725 Depends: neurodebian-popularity-contest, python-botocore, python-concurrent.futures, python-jmespath, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-requests, python-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python-boto3_1.2.2-2~nd+1_all.deb Size: 63240 SHA256: 09591687fa5a2f6e26bd6c1c8d469e4fb159d63b28f1fc9e75d30af54183f6b7 SHA1: 373f10155429cfc95b9b13a555642e1a4d7fa274 MD5sum: 8c4def388d440191cc6a54f5203c2609 Description: Python interface to Amazon's Web Services - Python 2.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python-brian Source: brian Version: 1.4.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2456 Depends: neurodebian-popularity-contest, python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-brian-lib (>= 1.4.3-1~nd+1) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.3-1~nd+1_all.deb Size: 402054 SHA256: 4d8b568ca6ce53db9403438830dc7a17577f3e0ad5c79979ec2a2366959f0c4f SHA1: 5109b5627ea5c22fbed8c9259ede95dc14b63a97 MD5sum: f8ddc31d598c27195a3055a212932cad Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7316 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.3-1~nd+1_all.deb Size: 1976078 SHA256: 9d045a63f64430c967de2d6d0f706773a1bd2d110136445345305435f9cc4cf2 SHA1: fdb9dcc1f2bdcd0ba7fee379170094eeaeb1d237 MD5sum: 75abb4ae9227a4a793743e2b5e09da95 Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.4.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.3-1~nd+1_amd64.deb Size: 40756 SHA256: 94dca36c04e82e9b5cdf79b8e9d7b8be92453ca5b33d16eb1d22ef85ee681a9f SHA1: ef321687dff9d1f7e1bdcdf145cc15507ceade4d MD5sum: c3000892280c2848bd3e84bb275d5ac7 Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-brian-lib-dbgsym Source: brian Version: 1.4.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 167 Depends: python-brian-lib (= 1.4.3-1~nd+1) Homepage: http://www.briansimulator.org/ Priority: extra Section: debug Filename: pool/main/b/brian/python-brian-lib-dbgsym_1.4.3-1~nd+1_amd64.deb Size: 133792 SHA256: b2f0c2b610c81a2e9deec57ede7bf42746ce3f4793ff1f7c597e659ed9e1871a SHA1: 460fcf13c2a2776174714736c9f2d7b8cc7a8fec MD5sum: 206c8530f29ee6860e5487f494c32e8d Description: Debug symbols for python-brian-lib Auto-Built-Package: debug-symbols Build-Ids: 2eeced323ebbd8f79a924dcfa57c0710d011dddc 52c7d907e546c06c9cdc89247fc4888438672c2d Package: python-cfflib Source: cfflib Version: 2.0.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 768 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-numpy, python-networkx (>= 1.4), python-nibabel (>= 1.1.0) Recommends: python-nose, python-sphinx, python-tables, python-h5py Provides: python2.6-cfflib, python2.7-cfflib Homepage: http://cmtk.org/cfflib Priority: extra Section: python Filename: pool/main/c/cfflib/python-cfflib_2.0.5-1~nd+1_all.deb Size: 217692 SHA256: 4da2bdfd6e65beb307156093efe58c8242305e225741677f043c95133dd02928 SHA1: f5afff0937ac80443da91ebd51b53ce9c454f296 MD5sum: e6da3383a7a7a89da2d0d5b33f4910b5 Description: Multi-modal connectome and metadata management and integration The Connectome File Format Library (cfflib) is a Python module for multi-modal neuroimaging connectome data and metadata management and integration. . It enables single subject and multi-subject data integration for a variety of modalities, such as networks, surfaces, volumes, fiber tracks, timeseries, scripts, arbitrary data objects such as homogeneous arrays or CSV/JSON files. It relies on existing Python modules and the standard library for basic data I/O, and adds a layer of metadata annotation as tags or with structured properties to individual data objects. Package: python-citeproc Source: citeproc-py Version: 0.3.0-1~nd+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~nd+1_all.deb Size: 80320 SHA256: 697b8521e8930432817b1503eb837c18fcc58f31d87fc3f958bfb110ca13378a SHA1: d4971cc97575a0c8c08f44c2cfb1de51bb281917 MD5sum: 634926f49184a46c2a5d8b35eec480f4 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~nd+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~nd+1_all.deb Size: 8654 SHA256: d3a0ccdd81271c47039bb787b192809749186f00bbadd53643e2299ac3dbf0cb SHA1: 8315929753d4260508bca756c44798061e425b97 MD5sum: 6cbc70f15c714d3bcdc17fbca8d88318 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-datalad Source: datalad Version: 0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3054 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), patool, python-appdirs, python-git (>= 2.0.3~), python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage | python-keyring (<< 9.2), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0), python-boto, python-jsmin, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-requests-ftp, python-scrapy, python-vcr, python-yaml Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.4-1~nd+1_all.deb Size: 594286 SHA256: 26079139ae498369e4b506e989d02063d4e31724e5964d20b6f2ccfd899da6a2 SHA1: 50d9b5f1d0d01fd6e9e5b804d99b40f149ad08f7 MD5sum: da48984d82e00f3e9122ee881bbe479c Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling, publishing, and testing. If you need base functionality, install without Recommends. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 509 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~nd+1_all.deb Size: 77460 SHA256: 1bde8fbdc4666fd59d20bd49513099826a1624dd961f4aee5c4fba6dcf7b223f SHA1: 8b4862f49a899b0e500b9a748eadd91f2dbf4e0a MD5sum: 6bfb2dd5c3a8f1394ec264c8309b9adc 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1522 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~nd+1_all.deb Size: 357756 SHA256: 438973cbca9e0829b3f9a70b5cb6c86f5ed945e4140d798288ba8576655d447a SHA1: 018cbb7f235a0fe220323e858cd241db2b40ea80 MD5sum: 734af5fe26acb1f95dfbfacfb16d6d46 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: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5799 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.10.1-1~nd+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_0.10.1-1~nd+1_all.deb Size: 2435144 SHA256: 2e8075e916ee5d45fe0e5488a5788246415d6856dac3a81b5b091a7c962998ee SHA1: cb28bf853dc8023afd1053fe08de5681532359d7 MD5sum: 68618b3cad69fbde37ce5a51c414dbca 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: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14485 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_0.10.1-1~nd+1_all.deb Size: 11463990 SHA256: fd636c451cff35647e431fa18dbdfc24f5bd6122a251dc273c68f76c9b7db671 SHA1: 3442bd8cd769d598df4f309c2af19970298cb441 MD5sum: 776a7425812024681f21963fe9b7861c 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: 0.10.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6789 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), 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_0.10.1-1~nd+1_amd64.deb Size: 1161150 SHA256: 11c5880ea17e7a9bea5fcdbbe6a596fe9dbaab5c83d8f64a20250015521d0e47 SHA1: f158eb2d1933ee615de97556ec796e8393605683 MD5sum: 3c2590facba15e1b6313bc42c5f9ff89 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-dipy-lib-dbgsym Source: dipy Version: 0.10.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 7041 Depends: python-dipy-lib (= 0.10.1-1~nd+1) Homepage: http://nipy.org/dipy Priority: extra Section: debug Filename: pool/main/d/dipy/python-dipy-lib-dbgsym_0.10.1-1~nd+1_amd64.deb Size: 6208574 SHA256: 6ea5f0d3b6d96877287909016088058b4ac384afea43d2f0a30cc21a9298ad77 SHA1: 3d168f1fe9c338608734983b40e50bcdb8c9ee3a MD5sum: 35e473be34803e5a51e79c2280f7c018 Description: Debug symbols for python-dipy-lib Auto-Built-Package: debug-symbols Build-Ids: 0fabfd3e089c7c1cef42487e3202ef03d4bc693b 129be91f5a7341b76d83d911fb428a5bbecc2abc 27175e52ceb0f011db08c005b1ed12ef9d8bcf2a 2afc0000f9ad3d227628e6a563fe467fac26a3c1 3597c4da567bd963fb39ee0e3d9a298f9f859896 3701d2a619fe9c0f1fe25ebf37857325a8288305 3751bc61de2c980261351e93ccf73d4163d4525e 49001c0862504d86284b0f5097e21d2dcedab09a 57ef92780ccded839c6200c06cc791227c79ccf7 63f65cdaa1e4dea10ea570c3b9f5610b4392070d 73afd4be1ce2814e3d8ec875f6d12f31c408db20 74153f4a1db3e9a97f8d97043958a1f4fe145a7a 8f00f9af3253393f9aa077f8f3ff1fc17c42e43e 99e29889eb6e0d65d154b15f5282a877884f045e 9b7d8246fd28839813a79ccd0f41a2af5fbd69e3 a46c60df4a449bbef0596b0d71e5d42ca16e9f7d a895fdd615c121e65e4956d2ef1ff342497364df ca4f359f5d626f04209b6426f5b235084fd183d6 d0ab63ec4c791c0b524c186a7fac16947773cf59 d4f9a5e8504ac390ca20c4bb02dc82b236795182 d8b32d97f3a4af5e2e2e40ba584ec86c530a3244 d8ea09dc04abb45454dae823d46aa7792c9432ed e3b6b77cdf39724dfdf439072eaf183f2250b7b5 e43b94421ee48431f3ea617531f9a5e2b126fc59 edbfff2d225ee147dea601b63007df375639176a Python-Version: 2.7 Package: python-docker Version: 1.7.2-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python-requests, python-six (>= 1.4.0), python-websocket, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/dotcloud/docker-py/ Priority: optional Section: python Filename: pool/main/p/python-docker/python-docker_1.7.2-1~bpo8+1~nd+1_all.deb Size: 27060 SHA256: 5cd7d553edec43fd4ece03e57ba315cd8cd992c035022158aee56ce171f8f03b SHA1: de68d545918b913f6baa5fa7453567314afa226e MD5sum: e770ce1dc614a1606b6ea23b8b88ab30 Description: Python wrapper to access docker.io's control socket This package contains oodles of routines that aid in controling docker.io over it's socket control, the same way the docker.io client controls the daemon. . This package provides Python 2 module bindings only. Package: python-dockerpty Source: dockerpty Version: 0.4.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python-dockerpty_0.4.1-1~nd+1_all.deb Size: 10882 SHA256: b5d6cc788c5184e41a059687050b2d8bf2e898abaff971f0ae22b8f538e652b9 SHA1: 6c3ee553947a51ba3b54fd1e561bc7f9062b202f MD5sum: 25b8f8456e493fef48261ed6b9514060 Description: Pseudo-tty handler for docker Python client (Python 2.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 2.x version of dockerpty. Package: python-duecredit Source: duecredit Version: 0.5.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 237 Depends: neurodebian-popularity-contest, python-citeproc, python-requests, python-six, 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_0.5.0-1~nd+1_all.deb Size: 52502 SHA256: 5a397c52164cecbb671000e71ccd7cb8cfce9553c1f0859e834e49bcd7994b2e SHA1: 79df197750262cbb6c19b9bfd5907556f6c8bdeb MD5sum: b5a778b5ae0b41215abbd3e0260c0bf2 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2419 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~nd+1_all.deb Size: 698616 SHA256: 0b51538d13146d68e561a4e41f6434c5d2da0f595efe67c50f01a4e534ef8aaf SHA1: dac42ac93d31516c2d67b397da1446658d3238ab MD5sum: baf8ddfb4a408c0e43865522241da0e7 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: 1:0.5.2+git6-g5455843+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.2+git6-g5455843+dfsg-1~nd+1), libpython2.7 (>= 2.7) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.2+git6-g5455843+dfsg-1~nd+1_amd64.deb Size: 47680 SHA256: 6504acc10477d9ef772afde99acd1d5ea0a4b701a7e892068d17766f417af85a SHA1: 680c8a7cbdd107cdd73b361ff981425f4bbf2a04 MD5sum: 87f6b0661ab9fb1e0853f08fd545cb48 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-funcsigs Version: 0.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python-funcsigs_0.4-2~nd+1_all.deb Size: 12992 SHA256: ffa5a791589955ce10c1f51009145f0258412f756260a8e041e10c5768a731d5 SHA1: 576edf525d446f2e0b1614396380b718ba1189e4 MD5sum: b37731fa0021f337711055db08ea669d Description: function signatures from PEP362 - Python 2.7 funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 2.7 module. Package: python-funcsigs-doc Source: python-funcsigs Version: 0.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 122 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://funcsigs.readthedocs.org Priority: optional Section: doc Filename: pool/main/p/python-funcsigs/python-funcsigs-doc_0.4-2~nd+1_all.deb Size: 23708 SHA256: 4b7ab90b7981cb7d54ec60ce531d3118fc451153e75c7ab913505376437efc9d SHA1: 58ca05578ee852376c61fba2ef8b49e3b87c1551 MD5sum: 29990bf500d495d67ac4a88c369b69e6 Description: function signatures from PEP362 - doc funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the documentation. Package: python-future Version: 0.15.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1712 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python2.7:any, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python-future_0.15.2-1~nd+1_all.deb Size: 348338 SHA256: cfa260c22586caec87848fde7b08104a1a6d613245185f72d22d5f2c631f45af SHA1: a300c53c8048687b2ca7575f1958869c720209f1 MD5sum: 0f64bb428c1fd4d3066f1969a59fc594 Description: single-source support for Python 3 and 2 - Python 2.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 2.x module. Package: python-future-doc Source: python-future Version: 0.15.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1889 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://python-future.org Priority: optional Section: doc Filename: pool/main/p/python-future/python-future-doc_0.15.2-1~nd+1_all.deb Size: 319714 SHA256: 849dbdad405ea50ea53f40b2b3767e4619b518eb5bba2d6d074d9a175e0082b6 SHA1: a7e9e6457db2dd27ea31b0dbb3d4867eb18c2872 MD5sum: 651fc20d4acb400cf43ee6d43c9e41d8 Description: Clean single-source support for Python 3 and 2 - doc Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the documentation. Package: python-git Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1624 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 2), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.1.0-1~nd+1_all.deb Size: 298452 SHA256: 7be2bc5080be8a8df8db4b196fd92de84a4de6ad3d95f8f1628af605d5b37634 SHA1: 8165d129d8a2857db64c978d559eb922f63b5d94 MD5sum: d064f3d1a8ee842c9d725331bcb0364d Description: Python library to interact with Git repositories - Python 2.7 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. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 979 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.1.0-1~nd+1_all.deb Size: 127454 SHA256: b881af76556f4c46a9d5b2423ed6975315384851b66fb2c87cdf779d462a3066 SHA1: bed1886154b4e8fde0a8ca3378668b4a06369fc9 MD5sum: 37e16f5c669b99a740f389966f029749 Description: Python library to interact with Git repositories - docs 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. . This package provides the documentation. Package: python-gitdb Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 215 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_2.0.0-1~nd+1_amd64.deb Size: 46082 SHA256: c4bcdac1c96eda148ac42792fd7a08886c9e1159e424f71dcaf9cdecb0445190 SHA1: 1f99679d361c11f31f30d1fc31096cdce7fe0a45 MD5sum: 09a91cf02497321128a475195b1afe4b Description: pure-Python git object database (Python 2) 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. . This package for Python 2. Package: python-humanize Version: 0.5.1-2~nd+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~nd+1_all.deb Size: 12948 SHA256: 4c4af0de554075bad41bfcb0e3cb8e192e87c5f97642ef0346d1f53df52a3b5f SHA1: f426f555e49355e10cb0cb480840235c56275883 MD5sum: 926ebef411d9a842e0385128133118d7 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-hypothesis Version: 3.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 411 Depends: neurodebian-popularity-contest, python-enum34, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python-hypothesis_3.6.0-1~nd+1_all.deb Size: 95266 SHA256: 8b552f81ac1acafa3c610a571016f3e1c2a6da093d179eff1f52bbb66432c5f9 SHA1: e10b1d3b885ad05e7edd2d5a40489384dffefd61 MD5sum: bf4213814cd87f0a43d2f402aa04858b Description: advanced Quickcheck style testing library for Python 2 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 2 module. Package: python-hypothesis-doc Source: python-hypothesis Version: 3.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1159 Depends: neurodebian-popularity-contest Homepage: https://github.com/DRMacIver/hypothesis Priority: extra Section: doc Filename: pool/main/p/python-hypothesis/python-hypothesis-doc_3.6.0-1~nd+1_all.deb Size: 163988 SHA256: ab3a23b2b5c894288b31fc4527e5e8bb364992467c7712db9de8092122d365dd SHA1: 5cc06ef2fe7dc7fefde1e7a1da9b078b4cb0909f MD5sum: 32d0ead2e160a2273644aae49ca7271a Description: advanced Quickcheck style testing library (documentation) Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the documentation for Hypothesis. Package: python-jdcal Source: jdcal Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python-jdcal_1.0-1~nd+1_all.deb Size: 7758 SHA256: 94412136ef6ac30b47b2fbde317ab011af097fef09813125147eaab6eefc8478 SHA1: 1e15930886d85192e3364b7efb6450730911da89 MD5sum: 75204676241ba5bb009d2f05a88634b5 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python-joblib Source: joblib Version: 0.10.3+git55-g660fe5d-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 488 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~) Recommends: python-numpy, python-pytest, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.10.3+git55-g660fe5d-1~nd+1_all.deb Size: 115512 SHA256: 26a6c7ab72cda03611eddf6d8af6bcf8075d822a64c1fbf488671094a5fdbe8c SHA1: 6a41ed42c4d3b1e93c64e83825279b3918054edd MD5sum: e3a66cca28e4446046734142e97dbe95 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-jsmin Version: 2.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python-jsmin_2.2.1-1~nd+1_all.deb Size: 21496 SHA256: ed21143372ccce7789de21af21b3a18fe46c9228a6d256bb5005603d4e7f96ec SHA1: 52e446ef90ca8dfef7d594e004b55c9dee3791ad MD5sum: 93563a3f269126625636d8b03d9cd7e3 Description: JavaScript minifier written in Python - Python 2.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 2.x module. Package: python-lazyarray Source: lazyarray Version: 0.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 19 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy Homepage: http://bitbucket.org/apdavison/lazyarray/ Priority: optional Section: python Filename: pool/main/l/lazyarray/python-lazyarray_0.1.0-1~nd+1_all.deb Size: 7328 SHA256: dbb35c5dc374c7bc62e95a56d3a14314105025852a66ba61f2472e4ea5b8be65 SHA1: a7bdc4dd42a3963a810fe0c0e73e4ad7ed6a7995 MD5sum: 1d204a47646dc6ed4152895171c87bc9 Description: Python module providing a NumPy-compatible lazily-evaluated array The 'larray' class is a NumPy-compatible numerical array where operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Consequently, use of an 'larray' can potentially save considerable computation time and memory in cases where arrays are used conditionally, or only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array). Package: python-lda Source: lda Version: 1.0.2-9~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1242 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~nd+1_amd64.deb Size: 234944 SHA256: 9f981ee72c7b85def186a027f4344220b0715dc04142c7d3e614ec785d1ec7fb SHA1: 5dfab383c248b18ba18b85d39bcd28b731ca336d MD5sum: 4870c70ce2b7693f88263183be3be33d 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-libsvm Source: libsvm Version: 3.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 76 Depends: neurodebian-popularity-contest, libsvm3 (= 3.0-1~nd+1), python, python-support (>= 0.90.0) Provides: python2.5-libsvm, python2.6-libsvm Homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Priority: optional Section: python Filename: pool/main/libs/libsvm/python-libsvm_3.0-1~nd+1_amd64.deb Size: 14310 SHA256: fd999ffd87492f02d03cc112367d112f9a9f40f29b7281a27fb1e6d82184e706 SHA1: 85c8da86fcc992c1e7f2c347b2c26562024e4e1b MD5sum: fbe7317e20d2a6f8cf761596d683732f Description: Python interface for support vector machine library Python interface for the LIBSVM library using ctypes. This new python interface is provided since 2.91, and it is incompatible with the old one. Package: python-mdp Source: mdp Version: 3.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1391 Depends: neurodebian-popularity-contest, python-future, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-pytest, python-scipy, python-libsvm, python-joblib, python-sklearn, python-pp Enhances: python-mvpa2 Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.5-1~nd+1_all.deb Size: 277554 SHA256: f4e162fc6a74c97cafc113d1f6fa3ab2c71c02e13efe9b73316d6570a3ae8905 SHA1: 4f1d93c2e31cc3157fb0716b0d236d214f85f671 MD5sum: 56e7c89d5d1c7b5317f610324edf6425 Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-mne Version: 0.13.1+dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9796 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), 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, python-pycuda, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.13.1+dfsg-1~nd+1_all.deb Size: 4506444 SHA256: df01427391c700ffc39e1c1683426b22c1f77a130603dc932fe28cde1efdbb42 SHA1: 7c4245e3744d565df9cc34809a8724bce251e600 MD5sum: e934c1bd0902ebfef9d93ac5bb6910ea Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-mpi4py Source: mpi4py Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1466 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.10, python (>= 2.7), python (<< 2.8), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_2.0.0-1~nd+1_amd64.deb Size: 341016 SHA256: 46e073afc9016856eaaadba8e2ffec61eabb0901031fe6969765625fca55dc8a SHA1: 928e7b97a9e62451eab5ce15745dc504de90ed67 MD5sum: a8db0801f0626c680f2ce1e18c9ddf68 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5700 Depends: neurodebian-popularity-contest, python-mpi4py (= 2.0.0-1~nd+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_2.0.0-1~nd+1_amd64.deb Size: 1041728 SHA256: 85dcef75dd8792c79b01754fe688d58049a70cf5c21fa3061f2db12b9923a364 SHA1: f9ecb0f313d6ff58ced9b606d0e843a501a4ec4f MD5sum: 8be7773d452490918a776e27367f37d8 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 2.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 318 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_2.0.0-1~nd+1_all.deb Size: 55418 SHA256: 7b55e630cb0ef72ec388d187b78381f643b9f0542f6f3e50443a79109f9a903b SHA1: 8deea62d2295fd769d5dc228382176f790d8a9af MD5sum: 807a332c99480abebbc8150caab3f00f Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-msgpack Source: msgpack-python Version: 0.4.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 179 Depends: neurodebian-popularity-contest, python (>= 2.7~), python:any (>= 2.7.5-5~), python (<< 2.8), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Breaks: msgpack-python (<< 0.3.0-1) Replaces: msgpack-python (<< 0.3.0-1) Provides: msgpack-python Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python-msgpack_0.4.2-1~nd+1_amd64.deb Size: 55726 SHA256: 8820511beb08569dd7f1adb17856d60c3008f64e34927c80e8e2fbafba7467a1 SHA1: a35a762690193932c13a7b77532d40ee815d9e56 MD5sum: 0240d374f3894c3f8ddc6e5837e963cd Description: Python implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python extension module implementing the MessagePack format. Package: python-mvpa Source: pymvpa Version: 0.4.8-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3547 Depends: neurodebian-popularity-contest, python (>= 2.5), python-numpy, python-support (>= 0.90.0), python2.7, python-mvpa-lib (>= 0.4.8-1~nd+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.6-mvpa, python2.7-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.8-1~nd+1_all.deb Size: 2205002 SHA256: 41465c88b5c5d855bb5cfb183ef31b621031eb691ba5a8f3ac481bec2fe61bd8 SHA1: 40e31da97e30b6c2af3f28dfcd4b255560f765e2 MD5sum: b36ff1ec87893ae209624c75e8934b87 Description: multivariate pattern analysis with Python 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, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.6, 2.7 Package: python-mvpa-doc Source: pymvpa Version: 0.4.8-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 37565 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.8-1~nd+1_all.deb Size: 8454400 SHA256: 9f730cbbc6fdcfce45ecca5ef036d74ea074eaedf2b4105fde7baf0028f11350 SHA1: 4510a24072100ffb1d4220f2d66d21abde733b9d MD5sum: 32c7629e7f9e01d9f7ca4d2c621b85be Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.8-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 200 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.6), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.6-mvpa-lib, python2.7-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.8-1~nd+1_amd64.deb Size: 72992 SHA256: 2a1e34073aa32faa8b3900965e38bf6b79be445d1a6c534b2cfc9222d4b4cb6f SHA1: 05b67d071af7b7e7cb9b7efa94a581869c94e0d6 MD5sum: 611866ebca9f87e19d374ce747a46f3b Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.6, 2.7 Package: python-mvpa2 Source: pymvpa2 Version: 2.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8535 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.6.6-7~), python-mvpa2-lib (>= 2.6.0-1~nd+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, python-duecredit 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_2.6.0-1~nd+1_all.deb Size: 5093362 SHA256: eccc67e34f5028bc967f4f8f4e1a959c66bbfdeab60869ba7025655ac25b5195 SHA1: 4c4cb6ca095348f743ffaa55acae0f8d7e6e2118 MD5sum: 8d62249ab4c9d261634a43d08c829304 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: 2.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35987 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_2.6.0-1~nd+1_all.deb Size: 4641656 SHA256: bfa0bc9bd06b9af4427d5dec27aa4fe86324c032af052fe9bf6f67a663d3e17b SHA1: 234c3079d6d1e9fd64f42e334ae716e0e7ccb0bc MD5sum: 811d93ce8fd1a9046ae849349d7f424e 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: 2.6.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 142 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.6.0-1~nd+1_amd64.deb Size: 50764 SHA256: 15af6ca6f126ca7db56201fc36a154f73661b1ab3ee22da110a7eb6f49708dcb SHA1: 2dcfc8a31f181d3210845fadf0a42a04a349ec50 MD5sum: a900af03c47841ae1497812afc4ac07e 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-mvpa2-lib-dbgsym Source: pymvpa2 Version: 2.6.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: python-mvpa2-lib (= 2.6.0-1~nd+1) Homepage: http://www.pymvpa.org Priority: extra Section: debug Filename: pool/main/p/pymvpa2/python-mvpa2-lib-dbgsym_2.6.0-1~nd+1_amd64.deb Size: 91710 SHA256: bfb03ab0d29e029fba0ebc23d2a285c2eb1eba7d8b85fc66c95cff7d979175ec SHA1: 92cd574b1ac40fe66472f7c496c7b02bf1ec52b9 MD5sum: 43c622c210439e748d42739ae7d3377c Description: Debug symbols for python-mvpa2-lib Auto-Built-Package: debug-symbols Build-Ids: 498088c17949d40dd5daa9a8004c409789a4b59c e739c5c545b5eb965df0bc3702f0ad31b115ca71 Python-Version: 2.7 Package: python-neo Source: neo Version: 0.3.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2909 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Suggests: python-nose Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.3.3-1~nd+1_all.deb Size: 1378610 SHA256: 268bcbe349cdd59dcd6c81b69f509e39abc526f812bd5f07208932a109266e6b SHA1: be5f458f69e1f2108a65756ef29c1a542be0bbe1 MD5sum: 5da5190a50f6ef3282f67c895329fb02 Description: Python IO library for electrophysiological data formats NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples. . NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab). . Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement. Package: python-networkx Version: 1.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: http://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.4-2~nd+1_all.deb Size: 647276 SHA256: 8686482d59b2830b57bbb4c95a26e38598c5d2b46b8bfc3c41ef5079c7de3f85 SHA1: 8e2dcdffdac74665f7c48190e2594d95466e3c37 MD5sum: e610b0ef6d98a399e29c3b2be7968038 Description: tool to create, manipulate and study complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-networkx-doc Source: python-networkx Version: 1.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15804 Depends: neurodebian-popularity-contest Homepage: http://networkx.lanl.gov/ Priority: optional Section: doc Filename: pool/main/p/python-networkx/python-networkx-doc_1.4-2~nd+1_all.deb Size: 6175086 SHA256: 7576cef9c963357c491c8ed98372493e4567e864c9bf9b30c1da2cbc2dd0cf80 SHA1: 861dba2262ad5310d0b4065953ee4838e7575ad7 MD5sum: ba0a43a93a019711296e4657536ef25b Description: tool to create, manipulate and study complex networks - documentation NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains documentation for NetworkX. Package: python-neuroshare Version: 0.9.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 106 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.8.0), python-numpy-abi9, python:any (>= 2.7.5-5~), python-h5py Homepage: http://www.g-node.org/neuroshare-tools Priority: extra Section: python Filename: pool/main/p/python-neuroshare/python-neuroshare_0.9.2-1~nd+1_amd64.deb Size: 20306 SHA256: da960b066faa1dbbdf74bcef5c2cc2e711678af6ed2f4c09add8a5059e1b8190 SHA1: a278ac11e933a8ddcb9787f84bd14d2b33c75128 MD5sum: 0a6f3b61c57c1afbb97ec51f865ece4d Description: Python interface and tools for Neuroshare The Neuroshare API is a standardized interface to access electrophysiology data stored in various different file formats. To do so, it uses format- specific shared libraries. . This package provides a high-level Python interface to the Neuroshare API that focuses on convenience for the user and enables access to all available metadata and data. The data is returned in NumPy arrays, which provides a quick route to further examination and analysis. . In addition, this package contains the ns2hdf converter tool that converts neuroshare-compatible files into the HDF5 (Hierarchical Data Format, ver. 5) file format. Package: python-neuroshare-doc Source: python-neuroshare Version: 0.9.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 284 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://www.g-node.org/neuroshare-tools Priority: extra Section: doc Filename: pool/main/p/python-neuroshare/python-neuroshare-doc_0.9.2-1~nd+1_all.deb Size: 95620 SHA256: 4b008b4e512ecc425d792b05a5f237701cff8f0b10847f9ae4cefbe836b52f12 SHA1: 0c55225790940875eff3b0dc7ac1454c7dea4230 MD5sum: acccb1a0fb534f3233a73ff94d58d8a9 Description: Python interface and tools for Neuroshare The Neuroshare API is a standardized interface to access electrophysiology data stored in various different file formats. To do so, it uses format- specific shared libraries. . This package provides a high-level Python interface to the Neuroshare API that focuses on convenience for the user and enables access to all available metadata and data. The data is returned in NumPy arrays, which provides a quick route to further examination and analysis. . In addition, this package contains the ns2hdf converter tool that converts neuroshare-compatible files into the HDF5 (Hierarchical Data Format, ver. 5) file format. . This package contains HTML documentation files for python-neuroshare. Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd+1_all.deb Size: 32506 SHA256: 1b7a6109b4cd73ca4ed17d0f33010df1d73c8bfcdd469311c48d58714fd99755 SHA1: 101a6b891d69881db9e5bd6bfc176aaa2de3ca28 MD5sum: 191a7178983f856cb47820d478a3a791 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64222 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-numpy, python-scipy Recommends: python-dicom, python-fuse, python-mock Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.1.0-1~nd+1_all.deb Size: 2172068 SHA256: 95905905bcf2e54e2dc3497eecf19eeee2c7d0755ad6a72aa60a6e3423a2c924 SHA1: ea4597a93edf101b632124d18764f7552d1c415a MD5sum: a2c35e7733d2a19d1e4257f5ab589e44 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: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20478 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_2.1.0-1~nd+1_all.deb Size: 2910884 SHA256: 335d9ba0d9e3986fa3729268afbe5bae8f8418d00137b4798245a118c335ede3 SHA1: 261458207c8c78f0edcb6bf2d6d043a0ac9cdafe MD5sum: a00c7657795573bc3a6347ca6b49d968 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-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~sid.nd1_all.deb Size: 469776 SHA256: 674d6faa8c47cc5d2abded6bf10d56d3c7b2041b70390b254d6bed4fe0b89f92 SHA1: 1e06be036a09d6114c43bcccf080aa256f7c7a69 MD5sum: 26e58a8ca88e85dfba68eae891bdcdeb Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2454 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_0.2.5~dfsg.1-1~nd+1_all.deb Size: 730826 SHA256: 86ba4f45f523aaddd13c318fcdf9583326386b119f3ee0ec294912f9c1a7c3c7 SHA1: 7ce2818339748b007d6c28c6b5efa1f5a8961603 MD5sum: cc139e26c6e7e3ddc6bff44e47515d36 Description: fast and easy statistical learning on neuroimaging data (Python 2) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 2 version. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3380 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.0+git26-gf8d3149-2~nd+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_0.4.0+git26-gf8d3149-2~nd+1_all.deb Size: 738120 SHA256: 013fc6cb302f1636d51d15ffbd29bcdd28d5d0a71253f1086ca849d5e01b8674 SHA1: f1cc922333dd586b0a7c601f1380064f16359b7b MD5sum: ed29367709c67964397e837561579eb7 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: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10714 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_0.4.0+git26-gf8d3149-2~nd+1_all.deb Size: 2880428 SHA256: 2d698f2d8b12e329565aef286500383f1b7392e04e988bb75ffa3319a2440c89 SHA1: 7f843ba36b34f678ec61f12ce5dda31404cd4165 MD5sum: ca271237b077a62a700907d9358ffd65 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: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2679 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), 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_0.4.0+git26-gf8d3149-2~nd+1_amd64.deb Size: 649872 SHA256: dcd7c83b224514b1103fb6a3adbe98ca4675bc73d99baae2c63c1e2bf05cb4a6 SHA1: befc569e2663d28ceed1a21b1fe860ddca542a23 MD5sum: 814521614c2e0c89333ec6a5b1c57d76 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: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3757 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.4.0+git26-gf8d3149-2~nd+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_0.4.0+git26-gf8d3149-2~nd+1_amd64.deb Size: 653790 SHA256: 2eee05394a0e191f06e28e7a366a9ebfd875f9a0d4a8bc9290a28adcf864a6fc SHA1: 0e835e39e4cdb0a3f7885c9431a809e179e29e11 MD5sum: d1f31a0ee2c60c33a7fe5f7cbf11ce6a 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-nipy-lib-dbg-dbgsym Source: nipy Version: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1294 Depends: python-nipy-lib-dbg (= 0.4.0+git26-gf8d3149-2~nd+1) Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg-dbgsym_0.4.0+git26-gf8d3149-2~nd+1_amd64.deb Size: 811882 SHA256: d8baabe39cc8133fe629093b5f350558db90784313c7ee9c340c6f7ba2f4cd1a SHA1: 63c2f574f011b41f8513fc9fe62229f645d35a3e MD5sum: 408a13c162175dfa0f8d5695d9e4745e Description: Debug symbols for python-nipy-lib-dbg Auto-Built-Package: debug-symbols Build-Ids: 131fd667a995aeaabb491cd0127e37ba14f0f15b 1b44c59a381f42f84bdd183cfadb510670fe83d9 23cdc73cfae6bcd56aa294a7ff29d266311017c5 28dc3b9627bf8abe1f4f4d96198f6a40e611fc6d 38cb00ef8d3e0bdf013ecd3d6713ae1707c9e7ac 52e7c0aa9e1d391d70feb255e99a34ac2a84a14b 69596d63fcbbccaf69f69deaaa73479fcfc92620 69f573784472e6f8191c65eadd353a4c0bb1a41a b007cd6f447b29fd5b0504e7109c5237a2e2fbe6 b2854677ffeec8edc628053dcb8bb3ce0878bbfb c1fdcc0e1bf260e9b4cea27d4fa32fa81aa1f35c d2b668cff1691ebd9603edd57caa915d2c3f8aa6 d4cdb07d57184ef099070e7205d17fedf417d196 fb3fd7c19cc0b1acb904edfe77e605db56d68a78 Python-Version: 2.7 Package: python-nipy-lib-dbgsym Source: nipy Version: 0.4.0+git26-gf8d3149-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2381 Depends: python-nipy-lib (= 0.4.0+git26-gf8d3149-2~nd+1) Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbgsym_0.4.0+git26-gf8d3149-2~nd+1_amd64.deb Size: 2003724 SHA256: bdf5763f123ead27863eaacdd87b91737710cc3ecae9eb6a6ff9874828c28952 SHA1: 6b1c2b38394322c375ce0dbf34f61dc921da766f MD5sum: 3da5046fda77ee6def97a16476edfd29 Description: Debug symbols for python-nipy-lib Auto-Built-Package: debug-symbols Build-Ids: 0d609d3f7d2aae5da59fc6c05a3ad0a418f2456e 15ea1b7f1eff9d9beb3f6349684bcde1bcfea793 195f98980ce4032829dec2581ee8b05be6b94031 38a741ea720a3b4d42a6162d8fc4a6535f3b5127 53f98819d554ed867e40511ad359c4c05c9e5f4c a87e822ce56585d2871defaa2e55976f9adde5f1 b5241773815965725be21a17bc73dac6197b369b bbd1d9e866480ddb93ea6e5c3cafcab69cc737e6 cc14a06ba39ee3ae66757011a78d8f7b13543a48 cc9b7e7f4fc22f85a3d0ad1e8ae45c3b35e6891e cd7871f679ceba55f473482225b6ed725447b745 d7522b7ddbc1d940d1c00bc421c3c773af30ca7c da9577097526317a0f033eac4fbdaadd3d4f1595 f9d1aa25a5ac74e7d5a0d5fd2cf5812fa44a0558 Python-Version: 2.7 Package: python-nipype Source: nipype Version: 0.12.1+git4-gbc3a0b5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9364 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib, python-funcsigs, python-future, python-prov, python-psutil Recommends: ipython, python-nose, graphviz, python-xvfbwrapper, mayavi2, python-mock 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_0.12.1+git4-gbc3a0b5-1~nd+1_all.deb Size: 1536338 SHA256: b6afcf9bb0629127754f500f612c719b3579fcbb0158f15355423c8e79c95f8b SHA1: b7ec5d512341994917e77cfc7caa0eb443aae86b MD5sum: 1141ae8fcb801f38418565919dbfcd73 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: 0.12.1+git4-gbc3a0b5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31924 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_0.12.1+git4-gbc3a0b5-1~nd+1_all.deb Size: 13293580 SHA256: 6aaa26264411b98d8bcae47c15e29a6e9f2b3d3fd94f695d2e26b00ebddabe71 SHA1: 97d64cd3cf6404bba2f0d03c46102ff2e11db166 MD5sum: 60267213f89d85bb67eea0fb402526b8 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.7-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9377 Depends: neurodebian-popularity-contest, python-matplotlib, python-numpy, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.7-1~nd+1_all.deb Size: 2549110 SHA256: 1f1979920ff2f9b1c9fa05c97dbfbc473df07b69028d955805897a7ab43d73bc SHA1: a8296a50a9c5721f421db29628c2728e6a00d4dd MD5sum: 8a5a855a038d84a38be179231de34b0a Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.7-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6905 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.7-1~nd+1_all.deb Size: 4813592 SHA256: 2006c0a2e9687480f7d9ccfd3d2fabcc184de3fc4cbd62bcc4ef0f10f7e75ea6 SHA1: 8f7e17e74e44aa70838faf9e6c62f2b6721428c2 MD5sum: b85157562421c2d8240c267925be8f67 Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-nlopt Source: nlopt Version: 2.4.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 261 Depends: neurodebian-popularity-contest, libnlopt0 (= 2.4.1+dfsg-1~nd+1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nlopt Homepage: http://ab-initio.mit.edu/wiki/index.php/NLopt Priority: optional Section: python Filename: pool/main/n/nlopt/python-nlopt_2.4.1+dfsg-1~nd+1_amd64.deb Size: 68194 SHA256: 10502d7c966cc11e2aa1336448f18efd21d818c8b0c19b7f0dc3f7ceecb586e3 SHA1: df7953d483598e9412e823f89c4753fcccc7f9c7 MD5sum: c5d5d6ea8e486fedc9d76f2c85058e6e Description: nonlinear optimization library -- Python bindings NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: . * Callable from C, C++, Fortran, GNU Octave, Python, GNU Guile, GNU R. * A common interface for many different algorithms * Support for large-scale optimization. * Both global and local optimization algorithms. * Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. * Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. . This package contains the Python bindings. Package: python-nosexcover Source: nosexcover Version: 1.0.10-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python-nosexcover_1.0.10-2~nd+1_all.deb Size: 5128 SHA256: cb2e2c1da583fc4dd2c737eb6e748c26717ff623d08d0d28b22deacc09eafd51 SHA1: 06cd26e47b00d11c56c9f57261f5f51dcd3e5c34 MD5sum: e40a78d353eefee1076e93c269f9e889 Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python-numexpr Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 417 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.6.1-2~nd+1_amd64.deb Size: 142150 SHA256: a14d67968699edba7783499afe72bf31788ba16643fdd15a5b0ec35367c7914c SHA1: c07c2f4ccbb82def4f6b0cf9d4429ba70181e3d5 MD5sum: 396aba0e502616c71045d70625283ecc 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: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 287 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), python-dbg:any (<< 2.8), python-dbg:any (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-numexpr (= 2.6.1-2~nd+1), python-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.6.1-2~nd+1_amd64.deb Size: 110700 SHA256: 76b2ac8cc10b28be2ef9eda400f22664386d2efff56aa1c4c3eec323991f3a4d SHA1: 4799af6e7e9e7f2321366dcf89e704fac26ad579 MD5sum: 13d63f861b92b2e9ff17a1af3a4b21a1 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-numexpr-dbg-dbgsym Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 235 Depends: python-numexpr-dbg (= 2.6.1-2~nd+1) Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg-dbgsym_2.6.1-2~nd+1_amd64.deb Size: 217156 SHA256: 052e62da86d12936236df57be1d8de961f73221293be2eb3add8b80914512c12 SHA1: 2f4df6b8363c98a003ea0a288c2081d332eba422 MD5sum: dcdaaf9baa3c1ded316294be282bf2ba Description: Debug symbols for python-numexpr-dbg Auto-Built-Package: debug-symbols Build-Ids: fe38c82c0e0a0f21335f4238dee75138fc9f3c0f Package: python-numexpr-dbgsym Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: python-numexpr (= 2.6.1-2~nd+1) Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbgsym_2.6.1-2~nd+1_amd64.deb Size: 216100 SHA256: 7d7facf864dbc923cd1c3af875c71212c7cef0622f11b8d1c5036e060647d974 SHA1: 33019291f03e0d61591a40ba52d742488ebe8d77 MD5sum: 765dbd1cde0aa991e41a7f03f29c4bd8 Description: Debug symbols for python-numexpr Auto-Built-Package: debug-symbols Build-Ids: e6168211f33679983fc5f37df534f3a17a579a5c Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-4~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 668 Depends: neurodebian-popularity-contest, libatlas3-base, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.7-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-4~nd+1_amd64.deb Size: 171844 SHA256: 380eefae3ddc46db6eedbbc6abda1af03fedb46930b56b78f51f31e09315591a SHA1: 7049470e0f8c2a63852c0e3091a5d67014aaf7c3 MD5sum: b49225aa046227e4d23ce7cb86b0e0b9 Description: openmeeg library -- Python bindings OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography). . This package provides Python bindings for OpenMEEG library. Python-Version: 2.7 Package: python-openopt Source: openopt Version: 0.38+svn1589-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 954 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-cvxopt, python-matplotlib, python-setproctitle Suggests: lp-solve Conflicts: python-scikits-openopt Replaces: python-scikits-openopt Provides: python2.6-openopt, python2.7-openopt Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.38+svn1589-1~nd+1_all.deb Size: 245088 SHA256: 720267e7fc1297916d72081d7bffedfc4e911f4cba267f9e83f65ee6cf7eac3b SHA1: 2a31c5c6bad612fa5d880b23d6c2c2628c1aef20 MD5sum: 5ffcdd148bf0a2e648d7c3960953fc20 Description: Python module for numerical optimization Numerical optimization framework developed in Python which provides connections to lots of solvers with easy and unified OpenOpt syntax. Problems which can be tackled with OpenOpt * Linear Problem (LP) * Mixed-Integer Linear Problem (MILP) * Quadratic Problem (QP) * Non-Linear Problem (NLP) * Non-Smooth Problem (NSP) * Non-Linear Solve Problem (NLSP) * Least Squares Problem (LSP) * Linear Least Squares Problem (LLSP) * Mini-Max Problem (MMP) * Global Problem (GLP) . A variety of solvers is available (e.g. IPOPT, ALGENCAN). Python-Version: 2.6, 2.7 Package: python-openpyxl Source: openpyxl Version: 2.3.0-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1323 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-jdcal, python-lxml (>= 3.3.4) | python-et-xmlfile Recommends: python-pytest, python-pil, python-imaging Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0-2~nd+1_all.deb Size: 199160 SHA256: 05a6d8042a17df46073966e3511d62d65165577bce600318f43d90f841152376 SHA1: 8f5916a8d5bdfb1c76ff1270fc7d6772833b59f7 MD5sum: aeea901ce8f8c17afb4ba3a6449c7ae1 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-packaging Version: 16.2-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, python-pyparsing, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://pypi.python.org/pypi/packaging Priority: optional Section: python Filename: pool/main/p/python-packaging/python-packaging_16.2-2~nd+1_all.deb Size: 17192 SHA256: 9d0ec2e40865cd2c2a838f179534b6a56f48aad4e4916473f74d2eac663a9837 SHA1: f93b19dec144a8424524e50a3699ac63765dfe04 MD5sum: 44b021089123e22cde0541630c5b36f6 Description: core utilities for python packages These core utilities currently consist of: - Version Handling (PEP 440) - Dependency Specification (PEP 440) Package: python-pandas Source: pandas Version: 0.19.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25229 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-dateutil, python-numpy (>= 1:1.7~), python-tz, python:any (>= 2.6.6-7~), python-pandas-lib (>= 0.19.2-1~nd+1), python-pkg-resources, 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_0.19.2-1~nd+1_all.deb Size: 2614296 SHA256: 5d9b5aabc7445477a12a7d0de2c96d2426e01836e965c3a10facc6a2a58e93a4 SHA1: c3b577c1be09ff0ddd7ae92ccdc6e8e028e078b2 MD5sum: aedd114817cc3d8df00e9a1807ea3975 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: 0.19.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56882 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_0.19.2-1~nd+1_all.deb Size: 5061500 SHA256: d1bb28999e625615449523ed369c4b4db568cd5052b680a3d9ecf895fb84b67d SHA1: 6b6c5b23dd1f554e5b087e015343235fa80a8d73 MD5sum: 385d5b7dab06953634fd990a66a666c6 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.19.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8687 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.19.2-1~nd+1_amd64.deb Size: 2274900 SHA256: 78e3700c2206839fffeede0702491ac2f2a2f55acd85694dd5362141cba14a23 SHA1: 1e8e88b033f485bbfdaafb647795e65f36063443 MD5sum: 8ec8ea798141d0d92339de433d4de5f0 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-pandas-lib-dbgsym Source: pandas Version: 0.19.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8521 Depends: python-pandas-lib (= 0.19.2-1~nd+1) Homepage: http://pandas.sourceforge.net Priority: extra Section: debug Filename: pool/main/p/pandas/python-pandas-lib-dbgsym_0.19.2-1~nd+1_amd64.deb Size: 7773940 SHA256: b3ce5f4fc95725f7b9fb6124c41bcd51abba2c71bac64c1a629d21ad5fa7c84d SHA1: 5fdafb52344cfebaac7c5cf17cf536c5f3b4cc69 MD5sum: e175f2acba281184c45216900e243f0b Description: Debug symbols for python-pandas-lib Auto-Built-Package: debug-symbols Build-Ids: 06e57935add28fca832afd814399ea1ebac8de9a 17e28d739414bc1a2699160a6d07b43b76718565 3237bd7f98874105ab6005087d0f9166e6bf0edf 341b6853993c16d81baffde6494056a637a9a194 424a8f9f0fc1e19ebcf6bc4759549feb4731fb22 524220bc3c8472dbebb6897c5a6fe18873829015 7e16cdba73273ea4a9123a0c91d42beb8fdb6af1 82a6a41ab13c2726d2384c7e76c3d0f3bbc1399a 835cf737734d7614dcd30acd1f8d028c9f7b23c9 8409483c29b0e73039a70d5824c773e032679ee9 ac7684899b2423a6be5f5a7d4bf740646de390d3 c101b6e23ee9ec0d04b16392299d4a4bad290fea e3d4b86b5d33b4887ec41ee5a131bd1eb22ff792 e59ea1b5dc3a5071bba647fdbdfbcf7c25dbd199 f0ef7942afce43112d26978e9f46baf3dd7dc262 f2f5b41a06c25d623a0ed909eb86580a8377a9f0 Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 783 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), 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+git34-ga5b54c2-1~nd+1_all.deb Size: 171488 SHA256: 5a16740bcdfe521a93a3d595251a662b967be847823d702c8aee6b088cfa4f89 SHA1: ec77b76fa166628a05dff1a5307722de2dcb537d MD5sum: 7a421430e7b1b9e30df92c2752c9b63b 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+git34-ga5b54c2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1066 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+git34-ga5b54c2-1~nd+1_all.deb Size: 236658 SHA256: dcbf0fe0f0e8c68027f80161be5a7ded3e833f803f2a45b0f21938ca5b6df1a3 SHA1: 1dc05739d69b36e6b2c6277599ab6fcfd10f12e4 MD5sum: c71dc8df1f2621d729e7cdd37af68bc0 Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 441 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python-pkg-resources_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 141372 SHA256: 4f8e5de7035f1e6394fd7be0f0423350f6e4d98126a8f23fd63aef3ae0ce25f3 SHA1: 5e502b07a69b4933aad7bf1e99c056b2d1dd91e0 MD5sum: 1511960fe4a84a84b6194f9462a88ce7 Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python-pp Source: parallelpython Version: 1.6.2-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.parallelpython.com/ Priority: optional Section: python Filename: pool/main/p/parallelpython/python-pp_1.6.2-2~nd+1_all.deb Size: 34266 SHA256: 6ef3aa699e927edfc8ec788d98beac10bec4de47387f92d79d44b0183b3c3c3d SHA1: d8942b2e7dddc5e29cc52b2a4cca69a392348a09 MD5sum: 36530320f9038b882b0e8b9d5be61505 Description: parallel and distributed programming toolkit for Python Parallel Python module (pp) provides an easy and efficient way to create parallel-enabled applications for SMP computers and clusters. pp module features cross-platform portability and dynamic load balancing. Thus application written with PP will parallelize efficiently even on heterogeneous and multi-platform clusters (including clusters running other application with variable CPU loads). Python-Version: 2.6, 2.7 Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd+1_all.deb Size: 81598 SHA256: 3842060cc266ddff9a61fb88f4c4e34004ad6e6aba6ba60d74ce046dc8c1b126 SHA1: 36cc022ca9cf83a947a9c1a3c7eabffa69dea1f2 MD5sum: 23b94adc9313ef79112c781728008a69 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-prov Version: 1.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1235 Depends: neurodebian-popularity-contest, python-dateutil, python-lxml, python-networkx, python-six (>= 1.9.0), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-prov-doc, python-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python-prov_1.4.0-1~nd+1_all.deb Size: 69980 SHA256: 0dd3c2efbf3b45e9400ad88faa9b3011b54c5b6c3f234023a737918d82109f0b SHA1: f3edc6ecdc850abb3eb38ba54f86016622f424ea MD5sum: b2e51315211190021ccaebcc070e7fa8 Description: W3C Provenance Data Model (Python 2) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 2. Package: python-prov-doc Source: python-prov Version: 1.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 814 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/trungdong/prov Priority: optional Section: doc Filename: pool/main/p/python-prov/python-prov-doc_1.4.0-1~nd+1_all.deb Size: 69190 SHA256: 6405fa03081e5f117dbf6e85cfb472b28002ac787f9bd4fc27dcc332f0a27f7e SHA1: 73a48d939942467ccad77c4f292295d81eeea920 MD5sum: 2b40eb8842cde2ece66d4f20c9f57318 Description: documentation for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the documentation for the prov library. Package: python-psutil Version: 2.1.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 541 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python (>= 2.7~), python (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python-psutil_2.1.1-1~nd+1_amd64.deb Size: 116524 SHA256: 367bbb70b6a6929dfd8e7b5fab3a1ec84fb8f0cbf875c88deed42e9c9e4fcbcc SHA1: a20f1b386856f3567d30d2a8ceec79cb8d9b9c61 MD5sum: e153ef44eefd3a1e4e576efc9293e5b2 Description: module providing convenience functions for managing processes psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. Package: python-py Version: 1.4.31-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 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_1.4.31-2~nd+1_all.deb Size: 82202 SHA256: 2a7ab07684889a19419f62000f613277009e21b2947d793dbe67a0e3408240a0 SHA1: 0545a23cc3b644673cf663a2670aa5708613da6b MD5sum: 910e023f99ba83a1cd988cd00ca8d7ff 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-pydotplus Version: 2.0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python-pyparsing (>= 2.0.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python-pydotplus_2.0.2-1~nd+1_all.deb Size: 20174 SHA256: 69c4d5e3b836af825c47f4a7eddb17adb6b76a639e45514db3d2832027a4698a SHA1: 2ea8d4e2da2f282573fb8d3f42b1e79eb8e7bf20 MD5sum: f8fdbf53270a8715a4d11059d00f1f04 Description: interface to Graphviz's Dot language - Python 2.7 PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 2.7 module. Package: python-pydotplus-doc Source: python-pydotplus Version: 2.0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 531 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-1~nd+1_all.deb Size: 47424 SHA256: 029e1fe6d5d0649d4c411f8cdb222e8d68ee917be8dca3dd40ac3af11af73cd0 SHA1: b67474f69655dfb35ae47aac35fed0077177447d MD5sum: bbee946696aa2a9cd3bb5a18a4e7e7a5 Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyentropy Source: pyentropy Version: 0.4.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy (>= 1.3) Recommends: python-scipy Suggests: python-nose Provides: python2.6-pyentropy, python2.7-pyentropy Homepage: http://code.google.com/p/pyentropy Priority: extra Section: python Filename: pool/main/p/pyentropy/python-pyentropy_0.4.1-1~nd+1_all.deb Size: 21334 SHA256: 3ab479e9d42286158d724eb219d6205e3c8071a2a8fd6436afc501b57ecf086b SHA1: 19b81597aeb2806a30580c43b1fcf5f5ad3d586d MD5sum: 662336ec73a1d4c272a6d2763ef118df Description: Python module for estimation information theoretic quantities A Python module for estimation of entropy and information theoretic quantities using cutting edge bias correction methods, such as * Panzeri-Treves (PT) * Quadratic Extrapolation (QE) * Nemenman-Shafee-Bialek (NSB) Python-Version: 2.6, 2.7 Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1374 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>= 1.0.16), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd+1_amd64.deb Size: 280978 SHA256: 40dc56cdc406ff12e0f165ba7e660d7c3513c98ff0ac1078bcf2c1ca220294a0 SHA1: 62bbb3b34b5e3bdde2fddcdc36338df11bdd1acf MD5sum: 3bb99c47530c0801ea08c44ff27aa2b3 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd+1_all.deb Size: 819288 SHA256: 7eb7da90f6e629e4f1eb828beac597cd0d9950fd05a06f9bb135d2e58d6a2d13 SHA1: 6fd9ebae91ca87f9a3efa61b64ccb01de6b033f7 MD5sum: b608bf8ddef20a65f3bef3f99781ed82 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-pyglet Source: pyglet Version: 1.1.4.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4356 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.5-pyglet, python2.6-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.1.4.dfsg-1~nd+1_all.deb Size: 972190 SHA256: d192998b5a0ad23a8014afd611a21ad4300c71dbd5d14b3f64e3f0fd669b6210 SHA1: 5e072bcd364c59d478f4006386eb7487a8ba4dbd MD5sum: 920b7e086aa6042bef058e20b3c5b057 Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-pygraphviz Version: 1.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~), libc6 (>= 2.14), libcdt5, libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python-pygraphviz_1.3.1-1~nd+1_amd64.deb Size: 74392 SHA256: d2d79d94b058a1dee162c94a1a8efc46651bd2831f90e572bd90ef1cd56aac25 SHA1: 7aa60b164a1bf6084a067ed3159e650c2f519eb5 MD5sum: 961ba9267476867577feb8363485b1c6 Description: Python interface to the Graphviz graph layout and visualization package Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. Package: python-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 307 Depends: neurodebian-popularity-contest, python-pygraphviz (= 1.3.1-1~nd+1), python-dbg, libc6 (>= 2.14), libcdt5, libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python-pygraphviz-dbg_1.3.1-1~nd+1_amd64.deb Size: 113164 SHA256: 3bba882ca79f19b6e1c0f43e80c26c0f4c1b66859311b77886267608a774d524 SHA1: 82f136008e17e816145b0ffa3801674d4338b9b7 MD5sum: c3c0d829dcd1ca63906d9033a6f5bb9a Description: Python interface to the Graphviz graph layout and visualization package (debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python-pygraphviz. Build-Ids: f0c016e993a72f1914abdad634299b949d2383fd Package: python-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 316 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pygraphviz.github.io/ Priority: optional Section: doc Filename: pool/main/p/python-pygraphviz/python-pygraphviz-doc_1.3.1-1~nd+1_all.deb Size: 68268 SHA256: d5e07fcdd236fd0c4eaf53f0006d03964386d7862fd6118efafcf3ef0438b75f SHA1: fb4510a060f5da5eddeb7f796e53a444484b820b MD5sum: 1574b28a58f374f740581b375c1a2ebc Description: Python interface to the Graphviz graph layout and visualization package (doc) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains documentation for python-pygraphviz. Package: python-pymc Source: pymc Version: 2.3.4+ds-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2752 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, libquadmath0 (>= 4.6), 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~nd+1_amd64.deb Size: 590908 SHA256: adbfa032de525b99784a673b2e145fdbe88ddf8c5e71d0eddd3b7df879c468cd SHA1: e8114923a50db2b3eb52f68bf70f105e37d2c4e8 MD5sum: a27f76476cebdbb5cd97addefee0d499 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1860 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~nd+1_all.deb Size: 839812 SHA256: 7b1065ed4bec2186333d05434ac2369fc6d0f67bc6b97416ea71a067b35c1674 SHA1: cf73784906e058cec17d8d2ba831d09b877bd10d MD5sum: 253948e97486b725a69427e9806b090c 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 777 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~nd+1_all.deb Size: 192126 SHA256: 4c25bbb4a6efbe9c9614c69977d255840ceb5469e917e9e42631963e11fa73b5 SHA1: 4d68ad72d900c06b6d482eaabab6847de44296f2 MD5sum: bb6a423667c3716a6baee943a4d73d50 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-pyoptical Source: pyoptical Version: 0.2-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~sid.nd1_all.deb Size: 6946 SHA256: 61b96afae4d2c43351ad598253b8b38fff6b0c2d99669f49f431b8d8678f89be SHA1: 8442b14c93a7d2c3718d78655dc85fef951bcfaf MD5sum: 1eaea3d3d51bcd440299d8aa65220111 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2447 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd+1_amd64.deb Size: 696592 SHA256: 4f99dc732e65ca48db83e94bf3c7fdfcc48a95a23a2d8b9e2686fac57af6ad71 SHA1: 767cb44f2b8b9c879cde0d5fcf22d1ab54b433f0 MD5sum: 02968878de2054dd29273780304b5333 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~sid.nd1_all.deb Size: 119482 SHA256: 047337422d8c671d1ca38e938384c985fc1fac566d178123b6cb5ee4d1fccc51 SHA1: 2fb56ca17ad07ee58955caf8de17a4cd24d3d85a MD5sum: 1790628c9012a2ae40aff02998bd9c41 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-pytest Source: pytest Version: 3.0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 649 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), 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_3.0.4-1~nd+1_all.deb Size: 181322 SHA256: cdfd679ecb7bfc48ae1c7898e0e78cea0d4662296e0dc5ad69b187bc3be4a268 SHA1: 4130c6041564a80cf302e4c742d9ec171349f6bf MD5sum: 51aa55e3d75f545ab5f4705bbf7ac372 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. . This package provides the Python 2 modules and the py.test script. Package: python-pytest-doc Source: pytest Version: 3.0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4029 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_3.0.4-1~nd+1_all.deb Size: 668172 SHA256: b12cc635cde03357d0246ddec2b894f21cc5a72f4a921ea2e9b18b0da502e0c3 SHA1: b0e9f47b222acd11ede6c7a982cb9daa93d67bcb MD5sum: 654469dfeecdaa21d6cff6de89919829 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~nd+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~nd+1_all.deb Size: 19198 SHA256: 2f64f1b2a625a270c68948df4a43096ab186027c6bd069c70269ecbcfdaf3624 SHA1: ab00c431d40fa8348c18a58c0caf96b243fbed45 MD5sum: a98bc5d4e1452d03901d3255e66ffa5f 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~nd+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~nd+1_all.deb Size: 5648 SHA256: e5920e43e010f58bc1e1330d50856b4bd7835295c5493ed9bc5de4dcdbee6700 SHA1: 5346fa774430224e768520a0c1d2a9ef999e9c4f MD5sum: 5b573689c8eec7d51ce53b18bcf26728 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-pyxid Source: pyxid Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 80 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Homepage: https://github.com/cedrus-opensource/pyxid Priority: optional Section: python Filename: pool/main/p/pyxid/python-pyxid_1.0-1~nd+1_all.deb Size: 11020 SHA256: 1031c0d69dd73cb38f3e0b826193211706a94bfd04da4287288418b257e54249 SHA1: 0f0d0524354e5d07eb89efcb11779d9acd9d57e2 MD5sum: 1f2a9bc07952b1f5c6b65fc5c092f75c Description: interface for Cedrus XID and StimTracker devices pyxid is a Python library for interfacing with Cedrus XID (eXperiment Interface Device) and StimTracker devices. XID devices are used in software such as SuperLab, Presentation, and ePrime for receiving input as part of stimulus/response testing experiments. . pyxid handles all of the low level device handling for XID devices in Python projects. Package: python-pyxnat Source: pyxnat Version: 0.9.1+git39-g96bf069-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1722 Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd+1_all.deb Size: 376516 SHA256: c44e63035749ea2429ed9f2aab12e3ce41aa533de51f0cf3ce9836f882e3a477 SHA1: 2baec2a6b0c311f22f1a6e685cea20ae7019dac7 MD5sum: 603bfa4501f120f7ca01ed5ed95293b0 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-quantities Version: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8), python-numpy (>= 1.4) Homepage: http://packages.python.org/quantities/ Priority: extra Section: python Filename: pool/main/p/python-quantities/python-quantities_0.10.1-1~nd+1_all.deb Size: 62610 SHA256: 24764ab44e8e2357cdb8d4882acce352d96b34ed6b3af8be217617eb51848f83 SHA1: 9367905e8af4cb696831c327b20e43a3e2d52616 MD5sum: d08b442a214c35f1e1f9fa595d311cf6 Description: Library for computation of physical quantities with units, based on numpy Quantities is designed to handle arithmetic and conversions of physical quantities, which have a magnitude, dimensionality specified by various units, and possibly an uncertainty. Quantities builds on the popular numpy library and is designed to work with numpy ufuncs, many of which are already supported. Package: python-requests Source: requests Version: 2.8.1-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 243 Depends: neurodebian-popularity-contest, python-urllib3 (>= 1.12), python:any (<< 2.8), python:any (>= 2.7.5-5~), ca-certificates, python-chardet Suggests: python-ndg-httpsclient, python-openssl, python-pyasn1 Breaks: httpie (<< 0.9.2) Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python-requests_2.8.1-1~bpo8+1~nd+1_all.deb Size: 68094 SHA256: eb91a7265a33845b9a7d111f5328560c3b3131e9799ff3e8a85118509163969c SHA1: 2230a4dbff6c7ddfdbf027b44be12c8bb9247408 MD5sum: 6a4d3e4142dc715bbb19a2f066163bfa Description: elegant and simple HTTP library for Python2, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts Package: python-requests-whl Source: requests Version: 2.8.1-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 353 Depends: neurodebian-popularity-contest, ca-certificates, python-urllib3-whl Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python-requests-whl_2.8.1-1~bpo8+1~nd+1_all.deb Size: 318990 SHA256: e7bdf804a4a112774d95c37d3dec8c74cc89e1dd097622ddc66fd3a4383a4056 SHA1: f6c61d789ccd724c608531946dcea388ea8345cb MD5sum: e7ba98f7af12e72068c7d563bd2059c5 Description: elegant and simple HTTP library for Python, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts . This package provides the universal wheel. Package: python-scikits-learn Source: scikit-learn Version: 0.18-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 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_0.18-3~nd+1_all.deb Size: 69554 SHA256: 7c4daec80806fe90ab14eac0f4c19581288c10f5515c3a938fc84822d1ab2eb3 SHA1: 2b18ad62eefdb1f83702f1068f6a589f7df21698 MD5sum: a5bd0a60ec0c4be283f9fdf82ffe5038 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scikits.statsmodels Source: statsmodels Version: 0.6.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, python-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: oldlibs Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.6.1-1~nd+1_all.deb Size: 5916 SHA256: 9bc5375614e5a8fe5d0971b590cc7418ed54ba3c13f74c19608f9f0bd942bcda SHA1: cf13e973da4b7e8bdc21f82a02a155afe465ee97 MD5sum: eb4bf6a7aa273d56602a55d601134c11 Description: transitional compatibility package for statsmodels migration Provides old namespace (scikits.statsmodels) and could be removed if dependent code migrated to use statsmodels for clarity of the namespace. Package: python-scrapy Version: 1.0.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 986 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-lxml, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python, python-openssl, python-service-identity, python-six, python-twisted, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: ipython, python-django, python-guppy, python-imaging, python-mysqldb, python-pygments, python-simplejson | python (>= 2.6) Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.3-1~nd+1_all.deb Size: 175798 SHA256: 6dc7f6e606591df2b833589c36efc783d5ced94cbb56de524e6b49eb8ce1106e SHA1: a6c48350ffdbdd0f2b364c5499c0a8bf4c6b767a MD5sum: 2b4bd67679a9e89b6695bedb4ebdd9cf 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: 1.0.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7133 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_1.0.3-1~nd+1_all.deb Size: 1540270 SHA256: 7df7413c2bf7b2719ad9909232e3cce4c32527fae7a1d3abf1d27028161977d3 SHA1: 58bf858628c0aa49dd7603e8b170de65105c1e69 MD5sum: 83e38127fe1d883c462951c0a8600788 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: 0.7.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 766 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_0.7.1-2~nd+1_all.deb Size: 128136 SHA256: 9b7286a9c5b491dd0e9187c25cfa30633be18731a0c359124088cfcd94e1ba3d SHA1: e1eddb400592de29535e0b7a87dc60030c4f5d57 MD5sum: 84bcead78cea6d9900aa75d6cd83f959 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-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 520 Depends: neurodebian-popularity-contest, python-pkg-resources (= 20.10.1-1.1~bpo8+1~nd+1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-setuptools-doc Provides: python-distribute Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python-setuptools_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 202886 SHA256: f75d02695f9b9a8ce273133bd2cd224cdcbd7defe2ac02a1d21a80462ea53057 SHA1: 1ee8a1b68aabe5d8ce93e32de45460af1c09ffbc MD5sum: f4322845a4f428a447adebe9a8c7e2e0 Description: Python Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: python-setuptools-doc Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1151 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: doc Filename: pool/main/p/python-setuptools/python-setuptools-doc_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 200410 SHA256: ce141310ed5a27a7c77a54302af242b1ad6b796013ce3b5d83ba4d0f49f822e1 SHA1: 35af707aa000d7a3cb2dc27d80c17a1116acbf4f MD5sum: 87c7cdf68fd72ec860414792cef121f0 Description: Python Distutils Enhancements (documentation) Extensions to the Python distutils for large or complex distributions. The package contains the documentation in html format. Package: python-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python-setuptools-scm_1.8.0-1~bpo8+1~nd+1_all.deb Size: 11454 SHA256: 2471d7fee8d771b29d6767532798cfa448170efbd1b52b756804f09bc238c6da SHA1: a00adfcd002ea4b8c101ba54564e67e573e85809 MD5sum: 139fa01be309df44565764efe6cf6ef9 Description: blessed package to manage your versions by scm tags for Python 2 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 2. Package: python-simplegeneric Source: simplegeneric Version: 0.7-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Provides: python2.6-simplegeneric, python2.7-simplegeneric Homepage: http://pypi.python.org/pypi/simplegeneric Priority: extra Section: python Filename: pool/main/s/simplegeneric/python-simplegeneric_0.7-1~nd+1_all.deb Size: 9802 SHA256: ccfadfca5d3a2796000fcc3d0ada9731e0f45258b365c0ee84591f3770427913 SHA1: b4bd46ca82b53ea624e1ffba0de0728089a89140 MD5sum: 0482bb6d6be4162e4e3e57a5a181d55c Description: Simple generic functions for Python The simplegeneric module lets you define simple single-dispatch generic functions, akin to Python's built-in generic functions like len(), iter() and so on. However, instead of using specially-named methods, these generic functions use simple lookup tables, akin to those used by e.g. pickle.dump() and other generic functions found in the Python standard library. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 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~nd+1_all.deb Size: 13788 SHA256: 953a2b0df284d7c3cee751384adc2920f8b2f89f963574ea7563780df9619af7 SHA1: 74034947c69b6b0151e894fa8573fbdc6ec5e451 MD5sum: e23399a91b6f44f46044ab7dec6970a2 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 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~nd+1_all.deb Size: 14068 SHA256: 2170b7f8588c9c50ffde947fe70ba7ee23e4a899dd7bcd4fdd8e4acf018b7aa0 SHA1: c9da3c5c5bc83e15932ce61841bee6534a6a3cb5 MD5sum: 11d3292a4ddb176dedd09264dc4d1420 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-skimage Source: skimage Version: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15134 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-six (>= 1.3.0), python-skimage-lib (>= 0.10.1-1~nd+1), python (>= 2.7), python (<< 2.8) Recommends: python-imaging, python-matplotlib (>= 1.0), python-nose, python-pil, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.10.1-1~nd+1_all.deb Size: 11929000 SHA256: 26a15e982952e9b25c3a01429758b7c907961ec356cca9752891db15ad8908aa SHA1: 08847ca24011d9e0f6628a01f29f0133981f7482 MD5sum: f526a0e7d0fb0fbd9aaf45f64a046ca5 Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21906 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.10.1-1~nd+1_all.deb Size: 17242376 SHA256: d2a4a015f0485af34b6b6f65092b9f09dc0cfa7176ba05d8679bbb0f91ed2ce4 SHA1: c47549b8d38b9b2e79035324d81121e63b6c344c MD5sum: 2abdd9cf6de3cb46714cb1a422bc3221 Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.10.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6924 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Recommends: python-skimage Provides: python2.7-skimage-lib Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.10.1-1~nd+1_amd64.deb Size: 1058042 SHA256: c727476e347c18ff17930a7603a6a181dda8793cb39135a71cd5e067512b0028 SHA1: 2dba1b1bd314f0243f1aacd71d98d069354a45c8 MD5sum: 6d09675221db98975f4e8cd63567d88a Description: Optimized low-level algorithms for scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 2 libraries. Python-Version: 2.7 Package: python-sklearn Source: scikit-learn Version: 0.18-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6545 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.18-3~nd+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_0.18-3~nd+1_all.deb Size: 1383310 SHA256: af80d604a8f0af9e58c3a8f36a6c0c7f615d10d777a865fb7c3d333f495897a8 SHA1: 4102c5fdcce369cd95e3ce3c70b99df5ab289b6c MD5sum: a2021b2a602ede208d13e01671aad25c 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: 0.18-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28671 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_0.18-3~nd+1_all.deb Size: 4682414 SHA256: 61cb82a30a804632df47d3d874ace272a161dbddc73333025861afd56fdbdc5e SHA1: 8769c3585c182a16867951dbc9c4610d99f424de MD5sum: 6d64ffb79f99a0a84cfbfa1557b18cf5 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: 0.18-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6651 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 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_0.18-3~nd+1_amd64.deb Size: 1540772 SHA256: df52f0c4058278e77b45bb44e233c7fca9ec166320664a7f015cf7f67b00bbec SHA1: 3f95ede4bcd72765b9f76056467dbaa8f903bd43 MD5sum: 7b8657acce6b47369d9bf99f99b60fb5 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. 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If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 2. Package: python-sphinx Source: sphinx Version: 1.0.7-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4188 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-docutils (>= 0.5), python-pygments (>= 0.8), python-jinja2 (>= 2.2), libjs-jquery Recommends: python (>= 2.6) | python-simplejson, python-imaging Suggests: jsmath Homepage: http://sphinx.pocoo.org/ Priority: optional Section: python Filename: pool/main/s/sphinx/python-sphinx_1.0.7-2~nd+1_all.deb Size: 1260238 SHA256: 6b0bdebb3903a4eb0a75440f121dde7c531d0b7b060d33223f1185d9e0a27ce9 SHA1: 555f959d260ce486fb4395838b0918eaf71fab5e MD5sum: c52dab199b31675ed95d4298586b8ed2 Description: tool for producing documentation for Python projects Sphinx is a tool for producing documentation for Python projects, using reStructuredText as markup language. . Sphinx features: * HTML, CHM, LaTeX output, * Cross-referencing source code, * Automatic indices, * Code highlighting, using Pygments, * Extensibility. Existing extensions: - automatic testing of code snippets, - including doctrings from Python modules. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 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~nd+1_all.deb Size: 117140 SHA256: 6c9a6db7304b5e89b7234974e577b9c57f42d4f363a8e84d2e29ec9f8a64616d SHA1: 9ce250a1f9b8fc1728058c2808026b47da96ebcc MD5sum: 185c9304fc5463f7488db9b1fd36e992 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-spyderlib Source: spyder Version: 2.2.5+dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4028 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libjs-sphinxdoc (>= 1.0), libjs-jquery, libjs-mathjax, python-qt4 Recommends: ipython-qtconsole, pep8, pyflakes (>= 0.5.0), pylint, python-matplotlib, python-numpy, python-psutil (>= 0.3.0), python-rope, python-scipy, python-sphinx Suggests: tortoisehg, gitk Breaks: spyder (<< 2.0.12-1) Replaces: spyder (<< 2.0.12-1) Provides: python2.7-spyderlib Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: python Filename: pool/main/s/spyder/python-spyderlib_2.2.5+dfsg-1~nd+1_all.deb Size: 1651710 SHA256: a848e076d4c5edb65fb283f745212616fcf9a34e60d9b1a8856567a394ba1107 SHA1: 50297650b3e49c95185c7857e668e4e21c720064 MD5sum: eabe7544210191b0f23c9a80a9065e86 Description: python IDE for scientists Originally written to design Spyder (the Scientific PYthon Development EnviRonment), the spyderlib Python library provides ready-to-use pure-Python widgets: source code editor with syntax highlighting and code introspection/analysis features, NumPy array editor, dictionary editor, Python console, etc. It's based on the Qt Python binding module PyQt4 (and is compatible with PySide since v2.2). Package: python-spykeutils Source: spykeutils Version: 0.4.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2096 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_0.4.3-1~nd+1_all.deb Size: 308836 SHA256: 0246c36a593a643572eac1c12920230c02b37799bd332843ac51d360b967051b SHA1: f8731b78bfc5462a11c7af4da709cae146e41e9d MD5sum: 4ac90d2bbf1755bd864efa79c691103a Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15862 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-numpy, python-scipy, python-statsmodels-lib (>= 0.8.0~rc1+git43-g1ac3f11-1~nd+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib, python-cvxopt Suggests: python-statsmodels-doc Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.8.0~rc1+git43-g1ac3f11-1~nd+1_all.deb Size: 3306422 SHA256: d6da6a2f6b88aedc73195dc53e5067d71aa32584c0120d428c4ce26cd033965b SHA1: 4a64383763b33327c885ab48eceb84a0ca1ea56c MD5sum: bb917d5fd1735ad6cb92ab5dd7cef467 Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53126 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: libjs-mathjax Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.8.0~rc1+git43-g1ac3f11-1~nd+1_all.deb Size: 8300808 SHA256: 3743fef8aebe65aea18d863d0e6cc429f9d0b38bfd10c1bdb0b1df9e4c05841a SHA1: 1f5510705fab93d5f9266ade7dde08e93ea04288 MD5sum: ca0cb7258abc0d6fd750448fd2aac3d8 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-statsmodels-lib Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1791 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.14) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.8.0~rc1+git43-g1ac3f11-1~nd+1_amd64.deb Size: 283662 SHA256: 8921ec8360f1fc41a1847bc2b9026f4718335e1e360f94c5e16344b8b4d2a12a SHA1: ce9717bc75707020eb521f1928304cf248689299 MD5sum: 456a57eee1b7a26177972b39ff105a04 Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-statsmodels-lib-dbgsym Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 627 Depends: python-statsmodels-lib (= 0.8.0~rc1+git43-g1ac3f11-1~nd+1) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: debug Filename: pool/main/s/statsmodels/python-statsmodels-lib-dbgsym_0.8.0~rc1+git43-g1ac3f11-1~nd+1_amd64.deb Size: 327808 SHA256: 62059af211b3bc23a42f08d01ef3616fa7957b378ee3f9baecb04bf9be86b7b9 SHA1: 12862107c1e8043200d2c13ec9dfbba7ed330772 MD5sum: c7098b19673387562d4356cd094c8534 Description: Debug symbols for python-statsmodels-lib Auto-Built-Package: debug-symbols Build-Ids: 2cdc9fcf9901af16e24d1f2621648a88fb24418b 648c57e6b66b6993ac784433e3f8db30c86c5251 96a92311ae99d29cc4a0f979c707c47f47382369 de0b7fa5ce6cd6c8de3bdc348e08686d8a9f2bea e4746c7a43755e3918af988590fa72f18a7a45a7 Package: python-stfio Source: stimfit Version: 0.15.4-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1413 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python:any (>= 2.6.6-7~), libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod3 (>= 4.5.2), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:3.0), libhdf5-100, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4), libsuitesparse-dev, zlib1g-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_0.15.4-1~nd+1_amd64.deb Size: 476102 SHA256: 5c5fa58878f204401a74aae1c7e07364fc9f2810352e9935aed51f46f2f9cca2 SHA1: d7a46cd1086770d2efdf9a9a61e62997a938b809 MD5sum: 100663dbe4ceee1d0498abcebbe44c3c 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 193 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~nd+1_all.deb Size: 43190 SHA256: acc7fbfc89d8c5200633705b40325ad457971313204c3f737aa4a49e645657ed SHA1: 0f70b1794d04389e6680c11ee2a98d4d98fc2227 MD5sum: 706f549c94471dfd7ac06207255436e8 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-sympy Source: sympy Version: 0.6.7-1.1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9268 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Recommends: python-imaging, python-ctypes, ipython Homepage: http://code.google.com/p/sympy/ Priority: optional Section: python Filename: pool/main/s/sympy/python-sympy_0.6.7-1.1~nd+1_all.deb Size: 1696300 SHA256: 65cc1db7a2ef35ab86aef147e04c6b2d8b7c2ca10e689a3e9767e3bce6291484 SHA1: b6182a46ed673beb7b3568356ac27cb73ca33585 MD5sum: 16047fa2cf0d90581ff5df51e1de35b1 Description: Computer Algebra System (CAS) in Python SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. Package: python-tables Source: pytables Version: 3.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2815 Depends: neurodebian-popularity-contest, python-numpy, python, python-numexpr, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-tables-lib (>= 3.2.1-1~nd+1), python-tables-lib (<< 3.2.1-1~nd+1.1~), python-tables-data (= 3.2.1-1~nd+1) Suggests: python-tables-doc, python-netcdf, vitables Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables_3.2.1-1~nd+1_all.deb Size: 344840 SHA256: 3493c792072ab913aef70030022c75ea4e63783024c7347848bec635dba5456c SHA1: 9a3a846299057d4f75db3e005ef2486fc1c34c67 MD5sum: 1d45c911dac8c853a81718c16e8eaed6 Description: hierarchical database for Python based on HDF5 PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This is the Python 2 version of the package. Package: python-tables-data Source: pytables Version: 3.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 957 Depends: neurodebian-popularity-contest Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables-data_3.2.1-1~nd+1_all.deb Size: 51248 SHA256: 37549f40bb3af4758ae9d9a456fec6902b07b257a0076264727c4398f3b5f393 SHA1: f0f3c1a62e58c989da869240aafc32f3b2f8a528 MD5sum: 9292011acdf9edc4d7988c5d9060f467 Description: hierarchical database for Python based on HDF5 - test data PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . This package includes daya fils used for unit testing. Package: python-tables-dbg Source: pytables Version: 3.2.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1540 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libbz2-1.0, libc6 (>= 2.14), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1v5, zlib1g (>= 1:1.1.4), python-tables (= 3.2.1-1~nd+1), python-tables-lib (= 3.2.1-1~nd+1), python-numpy-dbg, python-numexpr-dbg Suggests: python-tables-doc, python-netcdf Homepage: http://www.pytables.org Priority: extra Section: debug Filename: pool/main/p/pytables/python-tables-dbg_3.2.1-1~nd+1_amd64.deb Size: 451686 SHA256: 4b1483bc883ae7b1fc468f42b064b805578ff2f48e994dcfcd89a331968b3a23 SHA1: 15349b2e84806938128c0d16daf2a2f7e13f7c4a MD5sum: c4ee1433c9c9c3f3019f959bec23c7a5 Description: hierarchical database for Python based on HDF5 (debug extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 2 debug interpreter. Package: python-tables-doc Source: pytables Version: 3.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8931 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), libjs-jquery-cookie Suggests: xpdf | pdf-viewer, www-browser Homepage: http://www.pytables.org Priority: optional Section: doc Filename: pool/main/p/pytables/python-tables-doc_3.2.1-1~nd+1_all.deb Size: 4249302 SHA256: 0261a6906b3f11e19de72907f72181e28b0ceaa39ee09cc4f986a0aa37109618 SHA1: 4b89ae7eb63a55068fb800ce79157454b8067e4d MD5sum: 1110d75f3980e0431b8739c7d08c485a Description: hierarchical database for Python based on HDF5 - documentation PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . This package includes the manual in PDF and HTML formats. Package: python-tables-lib Source: pytables Version: 3.2.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1299 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libbz2-1.0, libc6 (>= 2.14), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1v5, zlib1g (>= 1:1.1.4) Recommends: python-tables (= 3.2.1-1~nd+1) Breaks: python-tables (<< 3.0.0-3) Replaces: python-tables (<< 3.0.0-3) Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables-lib_3.2.1-1~nd+1_amd64.deb Size: 356240 SHA256: 901e9000a760b5ff790cbcaa6b05d1a9855270908dbcd36849c6b42fb8d18752 SHA1: 29eb6de1415f92131a1257fbdb052b053c72f91a MD5sum: 68815ce9a802761253c6c5d5c4a822d3 Description: hierarchical database for Python based on HDF5 (extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 2 interpreter. Package: python-tornado Version: 2.1.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 944 Depends: neurodebian-popularity-contest, python2.6 | python2.7, python (>= 2.6.6-7~), python (<< 2.8), python-pycurl, ca-certificates Recommends: python-mysqldb Homepage: http://www.tornadoweb.org/ Priority: optional Section: python Filename: pool/main/p/python-tornado/python-tornado_2.1.0-1~nd+1_amd64.deb Size: 223238 SHA256: f16f34576ace01050b03588e92f1abfb6536e18c6aaa0c1d3bfdc277d1a73810 SHA1: bf5c2ed97b912a3b67a72385366197419673ec17 MD5sum: 2a925ea85f71a74584eedcc55a5a54b1 Description: scalable, non-blocking web server and tools Tornado is an open source version of the scalable, non-blocking web server and tools that power FriendFeed. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the underlying non-blocking infrastructure. Package: python-tqdm Source: tqdm Version: 4.4.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.4.1-1~nd+1_all.deb Size: 35302 SHA256: 629c9d5f35c9f7d4968f2eb73e7a97833f9e6a4b0b3dab24e504faec07b4df53 SHA1: 67d3d54caa5a1b741f851b78795451d6bcc2ddaa MD5sum: e692b1fa07764e640a2dd827a512901e Description: fast, extensible progress bar for Python 2 tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 2 version of tqdm . Package: python-tz Version: 2011h-0.1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 180 Depends: neurodebian-popularity-contest, tzdata, python, python-central (>= 0.6.11) Homepage: http://pypi.python.org/pypi/pytz/ Priority: optional Section: python Filename: pool/main/p/python-tz/python-tz_2011h-0.1~nd+1_all.deb Size: 46912 SHA256: 0e8fdcb7a39493961a0d36f489eb13080b7f1e52a6d8324fedeb2d9772af249a SHA1: b1818fcc06cc8630f2af4eb25229e441028a0d81 MD5sum: cdd882a56d74682e4229bc00421ee82b Description: Python version of the Olson timezone database python-tz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.3 or higher. It also solves the issue of ambiguous times at the end of daylight savings, which you can read more about in the Python Library Reference (datetime.tzinfo). Python-Version: all Package: python-urllib3 Version: 1.12-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-six Recommends: ca-certificates, python-ndg-httpsclient, python-openssl, python-pyasn1 Suggests: python-ntlm Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3_1.12-1~bpo8+1~nd+1_all.deb Size: 65356 SHA256: dd3c3e31a0d8bb5471cb1330d9bbe68a9a58e28e1ff5e4898405e1603b0c8474 SHA1: 800bd6128fc8a035a7afdcd5fe8a5c349017ff7f MD5sum: 2edc4725cb1341b7f9488733bd593694 Description: HTTP library with thread-safe connection pooling for Python urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. Package: python-urllib3-whl Source: python-urllib3 Version: 1.12-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, python-six-whl Recommends: ca-certificates Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3-whl_1.12-1~bpo8+1~nd+1_all.deb Size: 92820 SHA256: 21412c99d8b2a8b234f00ccd587610414c5bddb9eae3bd159e987d2730c44e2c SHA1: faf759e621b5fa423b40773db728fd823a5ea27a MD5sum: 08adec2012fd6895cfc8ce53ff7d6907 Description: HTTP library with thread-safe connection pooling urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. . This package contains the universal wheel. Package: python-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six (>= 1.5), python-wrapt, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python-vcr_1.7.3-1.0.1~nd+1_all.deb Size: 43522 SHA256: 77ab97cd48b87aa68889d39a235da7456510032690244b58d17debfd9668f851 SHA1: 21b51ade6789d7d502a864ce2d8b8720a19ca094 MD5sum: 64b0712a730827639201fdfc39e8f372 Description: record and replay HTML interactions (Python library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 2. Package: python-visionegg Source: visionegg Version: 1.2.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1743 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgl1-mesa-glx, python-numpy (>= 1:1.6.1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Homepage: http://www.visionegg.org Priority: optional Section: python Filename: pool/main/v/visionegg/python-visionegg_1.2.1-1~nd+1_amd64.deb Size: 671994 SHA256: 10d4d5c8d1d78fc4474b2483f9c076f3caed5f564535854c91577a99936ee024 SHA1: 5df4a22a3f55f4e1816ef73b1b1d356bff628af7 MD5sum: db957c831e6f4cc3df49f3cbaa62ba87 Description: Python library for 2D/3D visual stimulus generation The Vision Egg is a programming library that uses standard, inexpensive computer graphics cards to produce visual stimuli for vision research experiments. Package: python-vtk Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 29686 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), libavcodec53 (>= 4:0.8-1~) | libavcodec-extra-53 (>= 4:0.8-1~), libavformat53 (>= 4:0.8-1~) | libavformat-extra-53 (>= 4:0.8-1~), libavutil51 (>= 4:0.8-1~) | libavutil-extra-51 (>= 4:0.8-1~), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libopenmpi1.3, libpq5, libpython2.7 (>= 2.7), libstdc++6 (>= 4.2.1), libswscale2 (>= 4:0.8-1~) | libswscale-extra-2 (>= 4:0.8-1~), libvtk5.8, libx11-6, tcl-vtk, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc, mayavi2 Homepage: http://www.vtk.org/ Priority: optional Section: python Filename: pool/main/v/vtk/python-vtk_5.8.0-7+b0~nd+1_amd64.deb Size: 7300072 SHA256: 6d1499803e19e94b14399f3d715a403daafaea8817886680db844090f2c03f17 SHA1: 9a2da61d2bdc18f6513748154d496d9f382d3474 MD5sum: 06115cd96de6dcc96f625c57d6ed66cb Description: Python bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries that enable one to use VTK from Python scripts. You will need Python and vtk installed to use this. Some useful information may be available in /usr/share/doc/python-vtk/. Python-Version: 2.7 Package: python-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 518 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, libvtk5.8, 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~nd+1_amd64.deb Size: 95918 SHA256: 1a9b43ce0a2aae94b8d98230d41ec6b74c10e491ad32b3b7243c157735a356b2 SHA1: 69f64611ba2433ad4485a7cfde594b8ef4143ba5 MD5sum: c1d709f3c309378c607984dd35940123 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~nd+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~nd+1_all.deb Size: 14094 SHA256: b7160742d1d6655d949e6a11303b3d861d8a9ffe4cd2b5dc02b90e4690c25bcc SHA1: 619b171f50cf2fc3f8a3d0ae40681464f2bd2ab7 MD5sum: abfa0ccef999dae58e5894ffa4af82f9 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 765 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~nd+1_all.deb Size: 165572 SHA256: 7be4f3e227cb2aa792e79c5b7ccc6c3b878436e040471324db1dd284bc7ccdb6 SHA1: c0910fc03848e4825f9e1d276edd2a728981ce3e MD5sum: 35744ae66a39ca40f586d3da5dc66a57 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2709 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~nd+1_all.deb Size: 881836 SHA256: 23b0fda78028dc71c9645cce224cb3c01269827fc90c6429f94c3cb7ebc533dc SHA1: a9cbe941509ee644d02f93eff5076afb4dfcaf9d MD5sum: 6b2655fad599fafea5535c47d130fcc1 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: python-workqueue Source: cctools Version: 3.4.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 423 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python2.7 | python2.6, python (>= 2.6.6-7~), python (<< 2.8) Homepage: http://nd.edu/~ccl/software/ Priority: extra Section: python Filename: pool/main/c/cctools/python-workqueue_3.4.2-1~nd+1_amd64.deb Size: 135958 SHA256: f25a94860d449e6eb43bda3435629c83670c13461fba8e3724555eb563ae8a97 SHA1: 9b45d7df17c80cd8f3a55479bdd3ba25000b1b3f MD5sum: 64d0d32b9d3b9d6339b237b72757880b Description: cooperative computing tools work queue Python bindings CCTools's Work Queue is a system and API for building master-worker style programs that scale up to thousands of processors. This package provides bindings to access this system from Python. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 98 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd+1_all.deb Size: 22284 SHA256: 7ce1a8bc33d9665bdfca2e9f62fdba6e45b3cb152a185dc2d42e99b3fdc46bd3 SHA1: bb77b998936973e2f1724c1ee467037fb9582154 MD5sum: 709af60d648e61d95834e2b45a63c6f2 Description: bash tab completion for argparse (for Python 3) Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 3.x. Package: python3-boto3 Source: python-boto3 Version: 1.2.2-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 721 Depends: neurodebian-popularity-contest, python3-botocore, python3-jmespath, python3:any (>= 3.3.2-2~), python3-requests, python3-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python3-boto3_1.2.2-2~nd+1_all.deb Size: 63014 SHA256: 2b7f52391e596a78d603d278f48a14f1ddfad83c0541a1f52b9e92b8b8fdd57b SHA1: 9061d3b81293a1d88d33665d93cc4fe71ed3a7ad MD5sum: 43184c4f35a4b326d7e941de518ebab9 Description: Python interface to Amazon's Web Services - Python 3.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python3-citeproc Source: citeproc-py Version: 0.3.0-1~nd+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~nd+1_all.deb Size: 81822 SHA256: 397553ba2c393746e303667d70871e29928088f030709f71ddc1e9cf050b8ea8 SHA1: fa10008219f71e5bc589696cb6cde597b1111080 MD5sum: 2bedbc4c2743ffb36b7e764446621051 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~nd+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~nd+1_all.deb Size: 8722 SHA256: 0a491f030c8c742f313aaea5f9b006b37c1870c6e4005220ebf2afe9be397d1e SHA1: c244a752ad56c9b2156ffd09d8eb9724291b6161 MD5sum: 9ed808ffc27d17ac4c668f60131205d9 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-docker Source: python-docker Version: 1.7.2-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 150 Depends: neurodebian-popularity-contest, python3-requests (>= 2.5.3~), python3-six (>= 1.4.0), python3-websocket (>= 0.18.0~), python3:any (>= 3.3.2-2~) Homepage: https://github.com/dotcloud/docker-py/ Priority: optional Section: python Filename: pool/main/p/python-docker/python3-docker_1.7.2-1~bpo8+1~nd+1_all.deb Size: 27174 SHA256: 2bba5abed5c3488d76d40d11ffe6092063cbd6206eda1a27e44569976c49295d SHA1: 7ea0cc04691204a219624ca14828df341c783cf2 MD5sum: 3fa6848799867d77d3318a0e3a14bcfe Description: Python 3 wrapper to access docker.io's control socket This package contains oodles of routines that aid in controling docker.io over it's socket control, the same way the docker.io client controls the daemon. . This package provides Python 3 module bindings only. Package: python3-dockerpty Source: dockerpty Version: 0.4.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python3-dockerpty_0.4.1-1~nd+1_all.deb Size: 10966 SHA256: 6ef0c8fffb1650b53b6293e7a53ced450146d254a6e759ca6045c1c60b3c20ac SHA1: c47ba7ad5fdb1c05e405b09e4080c845cc3d71c5 MD5sum: c2afbb903ec7e0ac611037936de6edf5 Description: Pseudo-tty handler for docker Python client (Python 3.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 3.x version of dockerpty. Package: python3-duecredit Source: duecredit Version: 0.5.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 239 Depends: neurodebian-popularity-contest, python3-citeproc, python3-requests, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python3-duecredit_0.5.0-1~nd+1_all.deb Size: 52728 SHA256: 87f31dbf36c1fd52d00284cc46f6854ea5b66b8e2e17f6d13c2ae1f96c2e8f8f SHA1: e1bec41490051d24a2667f6f22fc90260e9928dc MD5sum: 723e8714947229ea08354dbcbd8051c8 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-funcsigs Source: python-funcsigs Version: 0.4-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python3-funcsigs_0.4-2~nd+1_all.deb Size: 13072 SHA256: 15fa59a1800b32094bf5f09458e09a7e14966957b6680c167e2e6fd75b2927e2 SHA1: d984c9873b79c7bc61b8ee3082591fdcc6e0283b MD5sum: 304a096119e3599f3c528b649e5e8caf Description: function signatures from PEP362 - Python 3.x funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 3.x module. Package: python3-future Source: python-future Version: 0.15.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1662 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python3.5:any, python3:any (>= 3.3.2-2~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python3-future_0.15.2-1~nd+1_all.deb Size: 346170 SHA256: bbc88a3bfe1da8b189ae590ddd8c9c5299b48a80a620427eb3098d39e48df52f SHA1: 6012b63a4e8c5ffba035de00a29c11492bade492 MD5sum: b618e2950a1d2b3acde7e2283e507420 Description: Clean single-source support for Python 3 and 2 - Python 3.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 3.x module. Package: python3-git Source: python-git Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1621 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 2), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.1.0-1~nd+1_all.deb Size: 298882 SHA256: a435ce5dd6b320b1bedad294e0229dc1766d9971f7db64f826808fffca3939e4 SHA1: 38eaeecdcc992819b67a6e237e71984c9cbccd89 MD5sum: 2241bcb66fc2360af34d9a739d3844b0 Description: Python library to interact with Git repositories - Python 3.x 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. . This package provides the Python 3.x module. Package: python3-gitdb Source: python-gitdb Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 214 Depends: neurodebian-popularity-contest, python-smmap, python3-smmap, python3:any (>= 3.3.2-2~) Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python3-gitdb_2.0.0-1~nd+1_amd64.deb Size: 46120 SHA256: 65e84c9603efb85a3377cc330f67966a1f5a9b3c6686e04ac812997897d5533a SHA1: 66dd7848a7863bb9e42193c004f999f96bcdb678 MD5sum: 250b8a934efa7bedcaea7f1e8f585521 Description: pure-Python git object database (Python 3) 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. . This package for Python 3. Package: python3-humanize Source: python-humanize Version: 0.5.1-2~nd+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~nd+1_all.deb Size: 12670 SHA256: eb53b7253b33997c80ef27e33d37519cf929e44eb64153d987a6b19d2833e7fd SHA1: 957dac3e198cfec8d7edb319555011c665550a83 MD5sum: a6f39e5b551bf6671a35dc023ffff692 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-hypothesis Source: python-hypothesis Version: 3.6.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 411 Depends: neurodebian-popularity-contest Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python3-hypothesis_3.6.0-1~nd+1_all.deb Size: 95334 SHA256: 2f943202622ba5112466988710b0317cbd9ab1987e0235918de6661e73e0b860 SHA1: 102c967f811e58126e257521deb404fde51e0a99 MD5sum: be41a236ff21346949742e1188a8d7c8 Description: advanced Quickcheck style testing library for Python 3 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 3 module. Package: python3-jdcal Source: jdcal Version: 1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest Homepage: https://github.com/phn/jdcal Priority: optional Section: python Filename: pool/main/j/jdcal/python3-jdcal_1.0-1~nd+1_all.deb Size: 7562 SHA256: 9f25374a1984cc55029085f0842ebcc556cb604d77ed5a3d9f2413d74d8d18db SHA1: 0b803e0c91b3084849b81ef4edebf8c82ba5a9b8 MD5sum: 9addeaab0579f0e325d2cc0be513923f Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python3-joblib Source: joblib Version: 0.10.3+git55-g660fe5d-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 483 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-pytest, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.10.3+git55-g660fe5d-1~nd+1_all.deb Size: 112788 SHA256: 7c0e3c043078b0c36fe283c7d6545e5b3a174fe920d7719dcf5511d4f328f304 SHA1: 57f81002f441f8c0cbcac4fc916a0c258973787c MD5sum: ffa40097ebd42bf2e0d7e87fe45edece 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-jsmin Source: python-jsmin Version: 2.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python3-jsmin_2.2.1-1~nd+1_all.deb Size: 21580 SHA256: a9c914e0e7d279672a487222e15f91575cc406f6276ed013cbd894c46b9bc435 SHA1: 522f5c43a921c02244542fca2fe4bd2ea43e7c06 MD5sum: 7785af8648130c52963347d743f25cc4 Description: JavaScript minifier written in Python - Python 3.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 3.x module. Package: python3-lda Source: lda Version: 1.0.2-9~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1238 Depends: neurodebian-popularity-contest, python3 (<< 3.5), 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~nd+1_amd64.deb Size: 234286 SHA256: fdcf7af933cf4efe0038f1d8ff9b59dda45cf3f660509d64c98610e71cb61603 SHA1: 8f1fd9e04cc8793f59a331d34988edd1169fb48b MD5sum: df32d468a508aced58ac87a60a761adb 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-mdp Source: mdp Version: 3.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1387 Depends: neurodebian-popularity-contest, python3-future, python3-numpy, python3:any (>= 3.3.2-2~), python-numpy, python-future Recommends: python3-pytest, python3-scipy, python3-joblib, python3-sklearn Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.5-1~nd+1_all.deb Size: 275288 SHA256: daea6afa80bd07e998e6619f4723b5e1e2481829971d83057bb823f82688cdad SHA1: 83c40cc3e9af5c666412136996bd5d5467086036 MD5sum: b7a08f083ad842fe1764419227f14c1d Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 3. Package: python3-mpi4py Source: mpi4py Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1443 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.10, python3 (<< 3.6), python3 (>= 3.5~) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_2.0.0-1~nd+1_amd64.deb Size: 340136 SHA256: 102454f3f8c1a98abb2d941203b198551580ea2da47a80da16cd920d72f9c2ea SHA1: 108c9870410cd04a4e964defa5fdf3752adbdc22 MD5sum: 2683d2d72ccffd6bc083cd7e14d6bc86 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 2.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6539 Depends: neurodebian-popularity-contest, python3-mpi4py (= 2.0.0-1~nd+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_2.0.0-1~nd+1_amd64.deb Size: 1187674 SHA256: 934c8195cea01e521214e90676aaf91bd026d492f70e02743853cbc50f99b399 SHA1: fb79e6b99ca4c3ac935720a4153f89ae47416691 MD5sum: 55eaa5e6ff4c82d5b874521006998f36 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python3-msgpack Source: msgpack-python Version: 0.4.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 181 Depends: neurodebian-popularity-contest, python3 (>= 3.4~), python3 (<< 3.5), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python3-msgpack_0.4.2-1~nd+1_amd64.deb Size: 52920 SHA256: e79cd13c2d68db75691ca81c581b2257b54633860fb9f525f9d6920e271fc930 SHA1: d07df8676341e80b5eab109f58878834cc652ed4 MD5sum: 9467cb9699b735394c4932768a6ac19a Description: Python 3 implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python 3 extension module implementing the MessagePack format. Package: python3-nibabel Source: nibabel Version: 2.1.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64194 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy Suggests: python-nibabel-doc, python3-dicom, python3-fuse, python3-mock Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.1.0-1~nd+1_all.deb Size: 2164702 SHA256: 6adfaa4b0f6be9196bcb1c7148e50a3df8e235e73c75e756a30eeba3a4a714aa SHA1: ba21150ee825b7932595fe49ff673c6110663a49 MD5sum: 28280bb7035801957d40ed3ca8eb26df 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-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2190 Depends: neurodebian-popularity-contest, python3-nibabel (>= 1.1.0), python3:any (>= 3.3.2-2~), python3-numpy (>= 1:1.6), python3-scipy (>= 0.9), python3-sklearn (>= 0.12.1) Recommends: python-matplotlib Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python3-nilearn_0.2.5~dfsg.1-1~nd+1_all.deb Size: 686336 SHA256: 359ecabd6ca6401141f095cac886ce63b0832feb791aecaba8d0a7764f95bd9d SHA1: 590eb8e987ec3e6d57c0fac7f96404d619663340 MD5sum: 57bfa80b7b9dd2829cacc28d4aa4782f Description: fast and easy statistical learning on neuroimaging data (Python 3) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 3 version. Package: python3-nosexcover Source: nosexcover Version: 1.0.10-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python3-coverage, python3-nose, python3:any (>= 3.3.2-2~), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python3-nosexcover_1.0.10-2~nd+1_all.deb Size: 5188 SHA256: 3bcb86b62cdd25a1ec6517f1ede04a23e9e3c6377da80877180ba8f6678f743b SHA1: 75aa68d8e79156378313cccd6c08dcf0cf211a03 MD5sum: 76f88c19868c3489c6271b1a7a4be9bb Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python3-numexpr Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 408 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~), python3:any (>= 3.3.2-2~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-pkg-resources Homepage: https://github.com/pydata/numexpr Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.6.1-2~nd+1_amd64.deb Size: 137032 SHA256: b1e68f268794a34be61d9103de35fd53a1d44992e05e09c5b609116c6172a4bb SHA1: f27a60b05aa2edb174a037a0ee5fcae681995878 MD5sum: 60b5c2aa22da9df694c86e23e99a5fab 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: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 287 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3-dbg (<< 3.6), python3-dbg (>= 3.5~), python3-dbg:any (>= 3.2~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.6.1-2~nd+1), python3-numpy-dbg Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.6.1-2~nd+1_amd64.deb Size: 110428 SHA256: 64617ff03821739f7ee46c4e065df6afc48f1f0105128820c1c2fdda00751761 SHA1: cd3929f2f2c662f418553c18e1a3d9f97839f2d3 MD5sum: 2a75a7873726af98d1415a46fcfac5be 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-numexpr-dbg-dbgsym Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 239 Depends: python3-numexpr-dbg (= 2.6.1-2~nd+1) Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg-dbgsym_2.6.1-2~nd+1_amd64.deb Size: 221472 SHA256: 6368e1d15861c002fac2fa2d0dec4ae3fe021dae3caeef5373518f01e08de5ea SHA1: 5a737b9ff96d52074fe530875ca47d4abc5de61a MD5sum: 4f90bd76a511b0b15e51b78eeafb287b Description: Debug symbols for python3-numexpr-dbg Auto-Built-Package: debug-symbols Build-Ids: ea626e98a00c7ec04cc5c0cda3310c3628b63dde Package: python3-numexpr-dbgsym Source: numexpr Version: 2.6.1-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 237 Depends: python3-numexpr (= 2.6.1-2~nd+1) Homepage: https://github.com/pydata/numexpr Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbgsym_2.6.1-2~nd+1_amd64.deb Size: 220078 SHA256: ed64139d1c50e9aa9b83f3abd470fa2578ba03608bf81769e704f2e8bd2e03f7 SHA1: dc495f657943e0aae4de94d9372bdf5ba576d830 MD5sum: 77fd90e1cce535bfd3627bfee03823e6 Description: Debug symbols for python3-numexpr Auto-Built-Package: debug-symbols Build-Ids: 1b068fac3a8745e60281cf525808d94bd5b7edcf Package: python3-openpyxl Source: openpyxl Version: 2.3.0-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, python3-jdcal, python3:any (>= 3.3.2-2~), python3-lxml (>= 3.3.4) | python3-et-xmlfile Recommends: python3-pytest, python3-pil Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0-2~nd+1_all.deb Size: 198354 SHA256: 36c997296bd6c1975e92fb180ad39a2f5f383bfdf07f06b433f1292c3c8d97da SHA1: 3099ed364ad6152430e60073610a752ab7611f2b MD5sum: 7a2cb6c8af7df65c8ca66c25feaa7811 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-packaging Source: python-packaging Version: 16.2-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 85 Depends: neurodebian-popularity-contest, python3-pyparsing, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://pypi.python.org/pypi/packaging Priority: optional Section: python Filename: pool/main/p/python-packaging/python3-packaging_16.2-2~nd+1_all.deb Size: 17286 SHA256: a147fcff55f750bc7b8b992bf795e9cf38490231fa5276c97036dd340b62ad8c SHA1: 7c08b0dc58f1c9f02768d848848efbcafc80a4d8 MD5sum: 6568daac84251afcef7f916f40d4e2d7 Description: core utilities for python packages These core utilities currently consist of: - Version Handling (PEP 440) - Dependency Specification (PEP 440) Package: python3-pandas Source: pandas Version: 0.19.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25227 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.19.2-1~nd+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.19.2-1~nd+1_all.deb Size: 2614206 SHA256: ce29c0d0e222cb92b80183474a12794aa89b590ca0ace2a86dcc4e57a2bb5de5 SHA1: 2da7542563c0c01102e329581e8ca0b1d5de51cd MD5sum: 6c600d758b1e3eb7f4c9b3c479b73c6a 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: 0.19.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8373 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~), python3:any (>= 3.2~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.19.2-1~nd+1_amd64.deb Size: 2223840 SHA256: 3ae77eae2f18649dd4dc5b838fc1ff14f8a9c667c5b0c262011c3ff4d00bc56e SHA1: 16963979599b1bf1a29c0a7ad6f18b856a1d5ac3 MD5sum: 4890ab7c2b6b1ce3636a0ecfd17cb207 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-pandas-lib-dbgsym Source: pandas Version: 0.19.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9450 Depends: python3-pandas-lib (= 0.19.2-1~nd+1) Homepage: http://pandas.sourceforge.net Priority: extra Section: debug Filename: pool/main/p/pandas/python3-pandas-lib-dbgsym_0.19.2-1~nd+1_amd64.deb Size: 8743202 SHA256: 1264d61d5bd9c34d8fd3edf62d7f92d20d4d2f024d183ad3994505256877797a SHA1: 7144e0efccdc9361e4293dd1cfe2de700f16ebf0 MD5sum: 03db69fa298e5dea119ecae09d619720 Description: Debug symbols for python3-pandas-lib Auto-Built-Package: debug-symbols Build-Ids: 04bbf38e73bd3c276eb4dacf1dca66bacc150c2c 04db49932bbff0a278bd4773ee3435c462244091 1d4897f0b5e70948212fc0a2e840c463467dee4c 3a6f420ad1f6d7e41b3366a7eb4234d20757bcfa 3ea72fee9538a1eb5a37126998a6c17c2257eeb6 a6183819c2ff5c188679ce92d50ed7bf8ad4b247 a8ffe13e35ffb1b577e4baadf88c819a9a67f0d2 a986e925e7dd35e1ce1c6ff7a2aa2b1cdfdc527b b67d544c3f5f5121662a01254880e82d0901d365 cbec1119b15d8f255a9e88d7c6a85dd2bb12765a cdf82b16b48214fce37aee3318d64a8ad0935951 e543224e94a157905c5e87bfbc7d9e4302f40c5b ebca7f83ecfcd2602370844a4db4dce2975cb579 ebf2ad80c29acad1dd134e24cf0f12f7f5c12dfa eeb80a004683986c173a641a1a73ed6f1a734218 fae18b608e11fe1774fe8cfca54dabd7f6a340c7 Package: python3-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 782 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+git34-ga5b54c2-1~nd+1_all.deb Size: 171540 SHA256: fd0bf2f3ad1e6adf5b9b2cdcda74f3624d10f55420ae6303fc6f9ad90fe838a3 SHA1: e0abe996099891aefddd1dbfa60bc72cbfccb974 MD5sum: d9543939758554f197f0397a58af7885 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-pkg-resources Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-setuptools Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python3-pkg-resources_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 111978 SHA256: 36a64437ff69d22a329972aefeb1317472c003cf880e151757932245370e5972 SHA1: bfb67674ced9d86162dcb2899fbcc613be113a2f MD5sum: ce4fa06bc2f539f762ef488dfb9fb14e Description: Package Discovery and Resource Access using pkg_resources The pkg_resources module provides an API for Python libraries to access their resource files, and for extensible applications and frameworks to automatically discover plugins. It also provides runtime support for using C extensions that are inside zipfile-format eggs, support for merging packages that have separately-distributed modules or subpackages, and APIs for managing Python's current "working set" of active packages. Package: python3-prov Source: python-prov Version: 1.4.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1235 Depends: neurodebian-popularity-contest, python3-dateutil, python3-lxml, python3-networkx (>= 1.10), python3-six (>= 1.9.0), python3:any (>= 3.3.2-2~) Suggests: python-prov-doc, python3-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python3-prov_1.4.0-1~nd+1_all.deb Size: 70164 SHA256: eb3b5a75434c818231aa350501a0c794046e1da39f8bfcff6b7ba206cf522c7f SHA1: d450e242d7e966eb82ac27bce407520dfacf0197 MD5sum: bccacf307043a31ed94436083233acf5 Description: W3C Provenance Data Model (Python 3) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 3. Package: python3-psutil Source: python-psutil Version: 2.1.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 248 Depends: neurodebian-popularity-contest, libc6 (>= 2.13), python3 (>= 3.4~), python3 (<< 3.5) Homepage: http://code.google.com/p/psutil/ Priority: optional Section: python Filename: pool/main/p/python-psutil/python3-psutil_2.1.1-1~nd+1_amd64.deb Size: 60024 SHA256: 84d876d7f325fd95942e19672a2c956fbe8e84439e75b29b733dafc86c666c54 SHA1: 54e90759a70bd567a858fe3c7569d32c6607306e MD5sum: 39dd7ef0afd677c857c7a26b53837539 Description: module providing convenience functions for managing processes (Python3) psutil is a module providing an interface for retrieving information on running processes and system utilization (CPU, memory) in a portable way by using Python, implementing many functionalities offered by tools like ps, top and Windows task manager. . It currently supports Linux, OS X, FreeBSD and Windows. . This package contains the Python 3 version of psutil. Package: python3-py Source: python-py Version: 1.4.31-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 320 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_1.4.31-2~nd+1_all.deb Size: 82268 SHA256: 65bc42d600c55da39ffd1381f8cdc4a732996142758881f068c6fe9a14221a13 SHA1: 38d97058b9accd5b06929df289ccc3ac6450dc9a MD5sum: d30561ac4dc95895b7d705e28fb85820 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-pydotplus Source: python-pydotplus Version: 2.0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python3-pyparsing (>= 2.0.1), python3:any (>= 3.3.2-2~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python3-pydotplus_2.0.2-1~nd+1_all.deb Size: 20262 SHA256: 6fa7cc65f60e53673a95ac0b7710158035358804412728addc9c01ce7eee4fbd SHA1: 0e8c34d5118c421ba3d472f8225ba7cbb62a0e86 MD5sum: 0d7c20a842addf30fd582fdf688cf0eb Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-pygraphviz Source: python-pygraphviz Version: 1.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3:any (>= 3.3.2-2~), libc6 (>= 2.14), libcdt5, libcgraph6, graphviz (>= 2.16) Suggests: python-pygraphviz-doc Homepage: https://pygraphviz.github.io/ Priority: optional Section: python Filename: pool/main/p/python-pygraphviz/python3-pygraphviz_1.3.1-1~nd+1_amd64.deb Size: 74178 SHA256: 0b442e8e5abebf189e8ea7351a2e047ff8666d525bba9103073a442a7b93e890 SHA1: a9a0681cb2ceb87e5dd118cb33049ac8ceead321 MD5sum: a57c8c7900e819414a9a3df5be49ac68 Description: Python interface to the Graphviz graph layout and visualization package (Python 3) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the Python 3 version of python-pygraphviz. Package: python3-pygraphviz-dbg Source: python-pygraphviz Version: 1.3.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 309 Depends: neurodebian-popularity-contest, python3-pygraphviz (= 1.3.1-1~nd+1), python3-dbg, libc6 (>= 2.14), libcdt5, libcgraph6 Homepage: https://pygraphviz.github.io/ Priority: extra Section: debug Filename: pool/main/p/python-pygraphviz/python3-pygraphviz-dbg_1.3.1-1~nd+1_amd64.deb Size: 112804 SHA256: 9b470c1ef0e247725d26a5b79137009c9a3a4b291b7ee3901065ddbfa8088f46 SHA1: c3653e12845fce79ce20e11898b35b76421557f3 MD5sum: a1bbb7dd6823ce37f8a4b20c67e23d81 Description: Python interface to the Graphviz graph layout and visualization package (py3k debug extension) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains the debug extension for python3-pygraphviz. Build-Ids: 7d50c8a87011eda56b077feee168d5fa50943389 Package: python3-pytest Source: pytest Version: 3.0.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 648 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3:any (>= 3.3.2-2~) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_3.0.4-1~nd+1_all.deb Size: 181276 SHA256: fe3f6152bfc2cd968b3589c896fb3df5276213b8cda7405a9d67b6a0ed25ebc8 SHA1: 10539b671cab14e268dbf1ad05d15d69ffefda4e MD5sum: 51e85dd49f028a65ddb9657707ea3b5a 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 py.test-3 script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd+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~nd+1_all.deb Size: 19274 SHA256: 97a7b78b2e02d5065ec6804cb7d890befc54aeeeccf4eb28e6cf3b60287ac3de SHA1: 39e1d74dd953692835179b37f5b8f1cf1455813c MD5sum: 4e985d26f70005cc1d1f4cddded2fe4e 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~nd+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~nd+1_all.deb Size: 5724 SHA256: d1d4de5834aedf07c5048c0240c07b6b48ccad80957e7d656bf0773326b9cdc0 SHA1: a878173779a4f9651dd416792ef1c446d0aad9ee MD5sum: 30ba6a3d4ecfa3acc9d387e1fb338a6d 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-requests Source: requests Version: 2.8.1-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 240 Depends: neurodebian-popularity-contest, python3-urllib3 (>= 1.12), python3:any (>= 3.3.2-2~), ca-certificates, python3-chardet Suggests: python3-ndg-httpsclient, python3-openssl, python3-pyasn1 Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python3-requests_2.8.1-1~bpo8+1~nd+1_all.deb Size: 67920 SHA256: 85db1db645bfe5f6d02bde57c8c8df004f026b94e237011d2b44ad3ce52db677 SHA1: 345e61d12fa61e9a0cc4e3274652ee7d3f94d8dc MD5sum: bd062c8c6c8e61e5fd5435079bcfab9d Description: elegant and simple HTTP library for Python3, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts . This package contains the Python 3 version of the library. Package: python3-seaborn Source: seaborn Version: 0.7.1-2~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 766 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-pandas, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.7.1-2~nd+1_all.deb Size: 128254 SHA256: 88da7abdee1e8ed2c7cd24662994acfafe422547ac306dc4b9dcb82c9eaaf8f7 SHA1: 8429767031471ceeca21eeca0044f53294f93286 MD5sum: ecf7b4b1c636f94376c9e1beca400565 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-setuptools Source: python-setuptools Version: 20.10.1-1.1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 431 Depends: neurodebian-popularity-contest, python3-pkg-resources (= 20.10.1-1.1~bpo8+1~nd+1), python3:any (>= 3.3.2-2~) Suggests: python-setuptools-doc Homepage: https://pypi.python.org/pypi/setuptools Priority: optional Section: python Filename: pool/main/p/python-setuptools/python3-setuptools_20.10.1-1.1~bpo8+1~nd+1_all.deb Size: 121934 SHA256: d36543b92692f75fd41013a92eb7b83804f31efa3e2fa2e8dba0286be5e67f66 SHA1: 89da5ed3ef4930101f70601d1027b86e8b638eb2 MD5sum: 18756da7c9bda50df0d48df6bf417b55 Description: Python3 Distutils Enhancements Extensions to the python-distutils for large or complex distributions. Package: python3-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python3-setuptools-scm_1.8.0-1~bpo8+1~nd+1_all.deb Size: 11504 SHA256: 18ecb5022d4c925922743c9be93a67d14d46299c444fc16cd44886a062f714b9 SHA1: f3863998d2b04d2a9c86e558aedd803eb211f799 MD5sum: b02bc4c26bc7a1acddbc97da381c5cf9 Description: blessed package to manage your versions by scm tags for Python 3 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 3. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 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~nd+1_all.deb Size: 13864 SHA256: 04e34cf5aa7ccee58a9ad967bdba4aea42566f635f61cdf6210cefd6a835d984 SHA1: ba8c5074dad26145c72e90ded5311486da064efb MD5sum: bfaaee600a2763c6130dfbde60a41e0f 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-skimage Source: skimage Version: 0.10.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15115 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-six (>= 1.3.0), python3-skimage-lib (>= 0.10.1-1~nd+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-matplotlib (>= 1.0), python3-nose, python3-pil Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.10.1-1~nd+1_all.deb Size: 11915866 SHA256: cd53b6ec9524fc904a752a41f025002dff4be06130bd005bef04287cfcd8cf84 SHA1: 158f4ec9919b03f9c936cfa6f281c86e97091041 MD5sum: 3ad25fc688fff35b82afb80ef9667383 Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-skimage-lib Source: skimage Version: 0.10.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6497 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.14) Recommends: python3-skimage Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.10.1-1~nd+1_amd64.deb Size: 997110 SHA256: 18c783b0a88107cfb74100fed5e2c21229db1959d81f9f0cb8725961a6daf9e4 SHA1: 4e859f1cb6d52bea40c20c8de644ed71ce90151a MD5sum: 6cc91322439d90b71a1a09629a7ff96c Description: Optimized low-level algorithms for Python 3 scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 3 libraries. Package: python3-sklearn Source: scikit-learn Version: 0.18-3~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6544 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.18-3~nd+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_0.18-3~nd+1_all.deb Size: 1383136 SHA256: b3650281172485ff0df9a86ca0f930360b09ba4e26cfd208a8404f337dcd4309 SHA1: ace5ea9fc8bc2c50288a4eb36e2febfaec9d18dd MD5sum: d88dcf1339a706f2270a1d5a6d6ba395 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: 0.18-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6129 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.18-3~nd+1_amd64.deb Size: 1454314 SHA256: eeb032c80cbcd29d350662a0269e480ab08fe0774b73f39c22ef2a4d3173710f SHA1: 4ffe09af9e9cdb509cb40245fa96ea6e7fd58dfd MD5sum: ac9e4ad18564e2bbd11530412ecd2bf3 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-sklearn-lib-dbgsym Source: scikit-learn Version: 0.18-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6965 Depends: python3-sklearn-lib (= 0.18-3~nd+1) Homepage: http://scikit-learn.sourceforge.net Priority: extra Section: debug Filename: pool/main/s/scikit-learn/python3-sklearn-lib-dbgsym_0.18-3~nd+1_amd64.deb Size: 6089480 SHA256: fcde2e5409419139f9adb31c2b44aa5f6575ec9309543da2ec2189ea67f02687 SHA1: e91c0e63da397b170a1081e07a894ac7f5db7e09 MD5sum: ead132cb41b9d947ccb360d5c403dd37 Description: Debug symbols for python3-sklearn-lib Auto-Built-Package: debug-symbols Build-Ids: 0431bbacaef20c412a9f1ef91cec052d0ea9910c 177f45814ae6e566351c44893827d7f07dc897c3 18694d8b6ee01d376a42c6c63c8e75aa290fff11 189a4d8872613a417dc14267fe85aaf4a60dcbdd 20013705eae9e40da43ebb1fcb2b3d745f8d53b9 206e9189417f3bf9698c5f8fc327cd2e6974a4f0 2cca3948bee0822a0d70e737892c25788b00a397 2e37f20bdb23ea8be2318048e0abbe4a8e5785db 31d0bae9ecd51c11ca6569796594c3cbcd5ccb9b 398e5b01e7d6eaadd8cd08a3fc16e79381cfacdc 3a05eb8e6a4fcac017a2ca3b8cfef6bff631a48a 3c95419fd8de967bb6b58040b63d8e621b233bae 4274f70f5d0474afce0ec4d0d3660cf937514515 48decb0884c5a4b1861a985c9b81490900ec945a 4ab42be7a9035bb81b7b9b724fc29432cb7ce4a1 4b72058cc6fe6481374b3bacb4a857c65e73b8c8 4fa2047a48a72d0763b3ea018048195a64b28cc5 5873b9743f1aa28a2afcddccf69457c0d698c558 58ba9d10a39c65b952bdc2e48ff71b59120faf33 5a9b8d462b6e23abf89f45b2bc29e146509be54a 6893df56b298584e6cf109375599c4744c49b2c6 6eb335ec8e5035e881b31ae3d5692819ae425486 6f3ddca947a59ef30939b87115a9aa881997a9df 7219da1c7cbd3352678649c335123a65c339d607 7567809d1daa95707b3715723587811a515008a0 8b5b2862bb214990ac599450ea3ad49937657602 9e8cf453f4d58e848120eb30ad1833ae4c5814b3 a89417c75f3e7f9bad29d75a615da8af8d84031d ab5034db68f4a9792c088974e204acbe873e66c7 b15e8ac16866c6b4f9f931b18e862fbc278fbf01 b49586e84cbadff9f19241a86f84614d14a29c20 b557351222699b054e60fcad6e142e1247f816b6 c43ae99ec66750a3f14f2a079d9041f43a44c872 c7e8be6caf188736c7e3c4721f0b9da91b9bff79 cad4ba70a27a21edfecc3ef7d4180290cc9b2e79 ccd37d2236ad29ba27b78e2ce576d207bc0f8120 d11acc3159943c1ac3d3969c41565ff8d21f6e8e d8ebfa92eb11f9f2d7353798fc77d7db6264b5e2 e9b154046d9d979d1c3dfa3afcf325c66157e76c ec94468a985480579f03f695f173961dc2b475dc f9a2ff83d15442badf7f1a9d2b285f3f776add9e Package: python3-smmap Source: python-smmap Version: 2.0.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-nose Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python3-smmap_2.0.1-1~nd+1_all.deb Size: 20132 SHA256: f0f59f24b9277b123ffe71a3dcb868376278e911ac405607d5b982ab93716b68 SHA1: 5ccbbbb6dd7df149254420ba3a507434646e6fed MD5sum: 3ab5b2131263549f011c1af0b491aacd 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. . This package for Python 3. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 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~nd+1_all.deb Size: 117236 SHA256: c18c9383781a8fc99ff2f1cd1b24c00c37c27553b34cf97bc8386a80e1063a8a SHA1: e5bb14868d4e0ccad143c02bc7f8f791491c74ea MD5sum: da5e186dfba00386b91466258fee5c75 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-tables Source: pytables Version: 3.2.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2791 Depends: neurodebian-popularity-contest, python3-numpy, python3-numexpr, python3:any (>= 3.3.2-2~), python3-tables-lib (>= 3.2.1-1~nd+1), python3-tables-lib (<< 3.2.1-1~nd+1.1~), python-tables-data (= 3.2.1-1~nd+1) Suggests: python-tables-doc, python-netcdf, vitables Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python3-tables_3.2.1-1~nd+1_all.deb Size: 334588 SHA256: 852f700742c25b047d53d4e8b6808ef62ed049dab623c996ac54cbcb53ae0a74 SHA1: b45f903684c952b6e6a622786be10b1291903da6 MD5sum: 5a897064e93c5b23d1edabb8f7aea48b Description: hierarchical database for Python3 based on HDF5 PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This is the Python 3 version of the package. Package: python3-tables-dbg Source: pytables Version: 3.2.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1533 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.5), python3-dbg (>= 3.4~), libbz2-1.0, libc6 (>= 2.14), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1v5, zlib1g (>= 1:1.1.4), python3-tables (= 3.2.1-1~nd+1), python3-tables-lib (= 3.2.1-1~nd+1), python3-numpy-dbg, python3-numexpr-dbg Suggests: python-tables-doc, python-netcdf Homepage: http://www.pytables.org Priority: extra Section: debug Filename: pool/main/p/pytables/python3-tables-dbg_3.2.1-1~nd+1_amd64.deb Size: 448738 SHA256: 0902f2802e2b033e201f482ea07cd2f2d0b4194eb322e42386fa8def0ad5ba3b SHA1: 2a91280202fb29551bc6fb09ef28e1894acdae9c MD5sum: 1b9dc5c6ad5c91e3f0dff37c6c54d880 Description: hierarchical database for Python 3 based on HDF5 (debug extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-tables-lib Source: pytables Version: 3.2.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1297 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libbz2-1.0, libc6 (>= 2.14), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1v5, zlib1g (>= 1:1.1.4) Recommends: python3-tables (= 3.2.1-1~nd+1) Breaks: python3-tables (<< 3.0.0-3) Replaces: python3-tables (<< 3.0.0-3) Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python3-tables-lib_3.2.1-1~nd+1_amd64.deb Size: 353888 SHA256: a7e7110cff9b573a60195f4bd373ba74750dff2749a04f636274160afeb7e494 SHA1: 974ee2b950361f6ef26002b027fd2f05438c3bb3 MD5sum: 1ade1a094fca12e4f8910fe5947b4432 Description: hierarchical database for Python3 based on HDF5 (extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 3 interpreter. Package: python3-tqdm Source: tqdm Version: 4.4.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.4.1-1~nd+1_all.deb Size: 35578 SHA256: 20841b07903a47e58de945f91493665d0f4f4bc6f24a3367683454fd1e8e8a80 SHA1: 971c2021a1b3141d2db92bff81406f74e19a8bfc MD5sum: a2d3e272177312d2b7b2e0668b121524 Description: fast, extensible progress bar for Python 3 and CLI tool tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 3 version of tqdm and its command-line tool. Package: python3-urllib3 Source: python-urllib3 Version: 1.12-1~bpo8+1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-six Recommends: ca-certificates Suggests: python3-ndg-httpsclient, python3-openssl, python3-pyasn1 Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python3-urllib3_1.12-1~bpo8+1~nd+1_all.deb Size: 65488 SHA256: 1ada7f90b1ab3d41825cb89accbc80c06e6b6566653e8a0c8b95dd9226fac74f SHA1: f6d02f35691c66648412cb7fbd9048ce55c92864 MD5sum: 3279cd2b1b5ec0b3f754a3dc9da02a6d Description: HTTP library with thread-safe connection pooling for Python3 urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. . This package contains the Python 3 version of the library. Package: python3-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python3-six (>= 1.5), python3-wrapt, python3-yaml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python3-vcr_1.7.3-1.0.1~nd+1_all.deb Size: 43584 SHA256: 03bf642db456d3b20d1126ed18400c9e268ae3e23f4016f0e007864528343114 SHA1: 8a45187f301eb74e3b892703c43e0216b9cd2581 MD5sum: aa1eb1d97032c236712fa2c291c3e7ef Description: record and replay HTML interactions (Python3 library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 3. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd+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~nd+1_all.deb Size: 14200 SHA256: 3a79d12f832d860e8feada19fd1443aec07c08d35e6df6b83e0d5a194d085789 SHA1: f6171c53aab3128a336c59d832f146ea1e10cf65 MD5sum: 6cebff033f0e6809d210f716e0b5bf83 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~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 765 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~nd+1_all.deb Size: 165542 SHA256: 36285a90f4bee14c4e98680c74ebdaa3bee13755c8f55fbbb161933926a38a20 SHA1: a3c8437f41a567a54d24841aa7111b15141547f8 MD5sum: 2e29700478a2d7c595cff6aa001cfd7a 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: qnifti2dicom Source: nifti2dicom Version: 0.4.11-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3126 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdcm2.6, libinsighttoolkit4.9, libqt5core5a (>= 5.0.2), libqt5gui5 (>= 5.0.2), libqt5widgets5 (>= 5.0.2), libstdc++6 (>= 5.2), libvtk6.2, libvtk6.2-qt, nifti2dicom (= 0.4.11-1~nd+1), nifti2dicom-data (= 0.4.11-1~nd+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.11-1~nd+1_amd64.deb Size: 466660 SHA256: ef230c4d8c523d56cab58591fd3cee33eee475e371bc0ff22d5f27a602e87479 SHA1: b60c17d4915bf76e3f24f12e43ec44934698b047 MD5sum: e8c616011bc2621bce6587adebdc8e8e Description: convert 3D medical images to DICOM 2D series (gui) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the Qt4 GUI. Package: remake Version: 4.1+dbg1.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 317 Depends: neurodebian-popularity-contest, guile-2.0-libs, libc6 (>= 2.17), libgc1c2 (>= 1:7.2d), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_4.1+dbg1.1+dfsg-1~nd+1_amd64.deb Size: 152064 SHA256: c67c35ff2ad0de4038c830a6397fd790b162fb7e6c403e7f64e2180c949dbec0 SHA1: a84a3a328c7f5d85a7e0733e6992784de03d41a2 MD5sum: fd612d8ebf1b714b66762f59f98f56ca Description: GNU make fork with improved error reporting and debugging Modernized version of GNU make utility that adds improved error reporting, the ability to trace execution in a comprehensible way, and a debugger. Some of the features of the debugger are: * see the target call stack * set breakpoints on targets * show and set variables * execute arbitrary "make" code * issue shell commands while stopped in the middle of execution * inspect target descriptions * write a file with the commands of the target expanded Package: remake-dbgsym Source: remake Version: 4.1+dbg1.1+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 313 Depends: remake (= 4.1+dbg1.1+dfsg-1~nd+1) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: debug Filename: pool/main/r/remake/remake-dbgsym_4.1+dbg1.1+dfsg-1~nd+1_amd64.deb Size: 276690 SHA256: 0334961d135b5a134d402dda087892298ee59fa5e622b75f252e2aced9b51040 SHA1: 50b7af936a0b213432f62fe1c0933c0e43bef76f MD5sum: a9011f8f348081def7a17168cb048b0f Description: Debug symbols for remake Auto-Built-Package: debug-symbols Build-Ids: 4be9beff88ba61d4eab641530ad14fcf66a548d8 Package: sigviewer Version: 0.5.1+svn556-3~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 972 Depends: neurodebian-popularity-contest, libbiosig1, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.6) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.5.1+svn556-3~nd+1_amd64.deb Size: 332790 SHA256: ee1181eaed0be734402bf4e833a5d19f952510fcdb4e407bd153a0f33be6b7a2 SHA1: 454b489979cafce986facb873487e3386376a67e MD5sum: 6021186a96ec85a9450c2047bd93ef47 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of 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 . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: singularity-container Version: 2.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 962 Depends: neurodebian-popularity-contest, libc6 (>= 2.16), python Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.2-1~nd+1_amd64.deb Size: 136820 SHA256: 57315259dc6af832607d0cbe06ce02447f023b74d3110d7b14f420dde1aed847 SHA1: df3654db6c16a97dfdfb2877a8481f37a677f858 MD5sum: 3a27b8fc3c39f72b830c514bfa4e2c2c Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: singularity-container-dbgsym Source: singularity-container Version: 2.2-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: singularity-container (= 2.2-1~nd+1) Homepage: http://gmkurtzer.github.io/singularity Priority: extra Section: debug Filename: pool/main/s/singularity-container/singularity-container-dbgsym_2.2-1~nd+1_amd64.deb Size: 225342 SHA256: 51712d5db41525066a05f8421c9c84fd1f9a2077f348d422f73271bd543deff3 SHA1: 316f3344e009d608f239ddbe1bb9d5fd61ac1172 MD5sum: f7e4fe6cd1c82f9ad45d7486ea90b50c Description: Debug symbols for singularity-container Auto-Built-Package: debug-symbols Build-Ids: 1b6ed7b80a6d2a9025a90b7072a2aaed9f2cdf06 2d186d68fe2e742580e4b18a8a85e3b5171ef6e3 721b13e3e3d0e66dc9f841aad9321a51c76b124c 8d59593a97a420330d2e87b54b01a7c51856c06a a0460f285697a7303cf3fb0f3f83c4bf7f390483 a66fbfc71d95393f16f82843a45c8466645266c5 d080dfb41809a0e2d8ea62d20a07adcbeb1a1d5b e2175dc8d8a06ef7b2d29c2871e7945971867a19 Package: solar-eclipse Version: 8.1.1+git0-g8f32b4b-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12255 Depends: neurodebian-popularity-contest, libc6 (>= 2.23), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), libnifti2, libquadmath0 (>= 4.6), libstdc++6 (>= 5.2), libtcl8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4), tcl8.5 Recommends: python Homepage: http://solar-eclipse-genetics.org/ Priority: optional Section: science Filename: pool/main/s/solar-eclipse/solar-eclipse_8.1.1+git0-g8f32b4b-1~nd+1_amd64.deb Size: 1683530 SHA256: 13380be86e1da84d099173887b092a52a4d22b850e778f261c8e4d0c1b841c7e SHA1: 872e02389c96018cdd8e70cce636982adc47affc MD5sum: 80afb6a25bf5fc68ba47fe703ae8f772 Description: genetic variance components analysis software SOLAR-Eclipse is an extensive, flexible software package for genetic variance components analysis, including linkage analysis, quantitative genetic analysis, SNP association analysis (QTN and QTLD), and covariate screening. Operations are included for calculation of marker-specific or multipoint identity-by-descent (IBD) matrices in pedigrees of arbitrary size and complexity, and for linkage analysis of multiple quantitative traits and/or discrete traits which may involve multiple loci (oligogenic analysis), dominance effects, household effects, and interactions. Additional features include functionality for mega and meta-genetic analyses where data from diverse cohorts can be pooled to improve statistical significance. Package: solar-eclipse-dbgsym Source: solar-eclipse Version: 8.1.1+git0-g8f32b4b-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 347 Depends: solar-eclipse (= 8.1.1+git0-g8f32b4b-1~nd+1) Homepage: http://solar-eclipse-genetics.org/ Priority: extra Section: debug Filename: pool/main/s/solar-eclipse/solar-eclipse-dbgsym_8.1.1+git0-g8f32b4b-1~nd+1_amd64.deb Size: 193604 SHA256: 4b1d82b79b2438a500aac8174b5ea44290fa921e7f147472d0865bad7154be3d SHA1: bce986f8a062191825ad4b0e29f16151f8ad3d1f MD5sum: 4b5cdc7906f86dc77f1671bf5af288f6 Description: Debug symbols for solar-eclipse Auto-Built-Package: debug-symbols Build-Ids: 4fdf0dc9c5cb079f727ff1f3d0d96480d5611223 9154ec1ff2fcd2c9667e0ff4b142facdaede0327 a948a55758d98d5e0a3652ba8512a6b84fb74b4f Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18626 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~nd+1_all.deb Size: 10737524 SHA256: b6a893c9b80b40421f5d12d9a135bdc12fb17f3fab59e0106ef1fc24ad3e77af SHA1: 235814d62d21157760fbae3cf4401cc6d48cf555 MD5sum: 33cd04a3593f6f216ac68a3fc0ea82a4 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~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73046 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd+1_all.deb Size: 52180218 SHA256: 92b31d00b8ee13b7bcdf249cff509ec988cc2fc0703e301eed662571b89135f3 SHA1: 6540ca3feacd1d7efd53733b78fde41c7defb2c2 MD5sum: 973ce7224b20331a4ccfde26eba8acbe 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~nd+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9273 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd+1_all.deb Size: 8991072 SHA256: a10f23addd5b16acad8feabb200ab8fda604f9ea177e7c32053ab0c60a768d9b SHA1: 65a715c185007eaccc71513dcad03da43d23cbdc MD5sum: 890e9a307f742f1573165ce80a18032f Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: spyder Version: 2.2.5+dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 113 Depends: neurodebian-popularity-contest, python:any, python-spyderlib (= 2.2.5+dfsg-1~nd+1) Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: devel Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd+1_all.deb Size: 52982 SHA256: eddafac432df7d273ddf59837b6ff169aa3ec1776348d59dec5add709bdab935 SHA1: fb37bcc12d9ed07c06c79368f8da3b195323ecaf MD5sum: 96c4abda1f6c31f93c1b3b88f4771106 Description: python IDE for scientists Spyder (previously known as Pydee) is a free open-source Python development environment providing MATLAB-like features in a simple and light-weighted software Package: spykeviewer Version: 0.4.4-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1962 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.4-1~nd+1_all.deb Size: 1291144 SHA256: 18e37d83ec7009a425bd2e555c51862c1be29603896bade502678c236dba81e8 SHA1: 379613ed9f79ab4816a97724522fd8e3d446518e MD5sum: 14c2106d870bad90b4c86bc5971f9eff Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stabilitycalc Version: 0.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd+1_all.deb Size: 28590 SHA256: c50f821d6eb4b0afe501c575de1b66aa196ac7745f412ca7c3064eed3f4d3c43 SHA1: 8002f08bea6021c1fa12d9e2de8b2e2482fcd799 MD5sum: aa37bec3c54a92373aeb2871266f1e77 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.6, 2.7 Package: stimfit Version: 0.15.4-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3263 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod3 (>= 4.5.2), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:3.0), libhdf5-100, 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), zlib1g (>= 1:1.1.4), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python2.7, python2.7:any, python:any (>= 2.6.6-7~), libsuitesparse-dev, zlib1g-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_0.15.4-1~nd+1_amd64.deb Size: 895932 SHA256: c4212a32813cae0974f86bcca77c90495f8be8051a8893b59b8a1e9e6ce10721 SHA1: ffb349ec5fcd9a925eb3d878255058ef55c36bff MD5sum: 5dfab7c6192ac2aebfaa132f5e647280 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: 0.15.4-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 31825 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_0.15.4-1~nd+1_amd64.deb Size: 6990962 SHA256: c88b0b42cb4a4a1de204c40848533a81254ed6bb53c4f714f14b367847c442df SHA1: dce045af5640d660e213d76dbcc8ea0336a2880b MD5sum: 4542125bdf7f2a160033965d1cc40d58 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: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: tcl-vtk Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 16157 Depends: neurodebian-popularity-contest, libvtk5.8 (= 5.8.0-7+b0~nd+1), libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libmysqlclient16 (>= 5.1.50-1), libpq5, libstdc++6 (>= 4.1.1), libx11-6, tcl8.5 (>= 8.5.0), tk8.5 (>= 8.5.0), zlib1g (>= 1:1.1.4) Suggests: vtk-examples, vtk-doc Replaces: vtk, vtk-tcl Homepage: http://www.vtk.org/ Priority: optional Section: interpreters Filename: pool/main/v/vtk/tcl-vtk_5.8.0-7+b0~nd+1_amd64.deb Size: 5322596 SHA256: a801f1f77b9b884aec2241c5853690cdc3d1259fa3dd61b83f2d803fac1a6618 SHA1: f5e938e36e1853d16271315aeff4017a0eba2ec1 MD5sum: 779aa32fabf451857131374c44c8fa5b Description: Tcl bindings for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This provides the shared libraries and executable that enable one to use VTK from Tcl/Tk scripts. You will need Tcl/Tk and vtk installed to use this. Package: testkraut Version: 0.0.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 358 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~nd+1_all.deb Size: 100016 SHA256: 5ea3d436c473902040c138cb6100770fc3d0969e891ce84eabf2f644ee367a5a SHA1: b29570908455d37b7397bd9eed303b13e59b090b MD5sum: eafa9781d2a05681ca03188015f96302 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: 2.6, 2.7 Package: tigervnc-common Source: tigervnc Version: 1.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libgnutls-deb0-28 (>= 3.3.0), libice6 (>= 1:1.0.0), libjpeg62-turbo (>= 1.3.1), libpam0g (>= 0.99.7.1), libsm6, libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6 (>= 2:1.4.99.1), libxext6, zlib1g (>= 1:1.1.4) Conflicts: tigervnc-server (<< 1.1.90), tigervnc-viewer (<< 1.1.90) Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-common_1.5.0-1~nd+1_amd64.deb Size: 61856 SHA256: 52c5892a3b090e930e4caedac06433a1dc84ae2809280e428c29aded69859844 SHA1: 6d3b294a9fe86d3ae9b6513d512a925a1acf0c79 MD5sum: 1da903a01053a231c2773ea49ee7fb8b Description: Virtual network computing; Common software needed by clients and servers VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It is implemented in a client/server model. This package provides the common software for both client and server. Package: tigervnc-scraping-server Source: tigervnc Version: 1.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 505 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libgnutls-deb0-28 (>= 3.3.0), libice6 (>= 1:1.0.0), libjpeg62-turbo (>= 1.3.1), libpam0g (>= 0.99.7.1), libsm6, libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxdamage1 (>= 1:1.1), libxext6, libxtst6, zlib1g (>= 1:1.1.4) Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-scraping-server_1.5.0-1~nd+1_amd64.deb Size: 180930 SHA256: 67278543e560cbbb00867b06cf435dd3a009dda774c24fbff285951422583f98 SHA1: 6f43231bd1e173e42ea84f49b18554b9e4169f95 MD5sum: 345d40db358bc874e52de5fa4f851715 Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . This package provides a vncserver which uses screen scraping of an already running X server to provide its VNC desktop. The VNC desktop can be viewed by any vncviewer even on other operating systems. . Note: If you only want to scrap your local X11 server, you should consider the tigervnc-xorg-extension package. This package provides the vnc extension for your local X11 server. The usage of this extension is more efficient than a scraping vnc server. Package: tigervnc-standalone-server Source: tigervnc Version: 1.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2510 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libaudit1 (>= 1:2.2.1), libc6 (>= 2.17), libgcc1 (>= 1:4.1.1), libgcrypt20 (>= 1.6.1), libgl1-mesa-glx | libgl1, libgnutls-deb0-28 (>= 3.3.0), libjpeg62-turbo (>= 1.3.1), libpam0g (>= 0.99.7.1), libpixman-1-0 (>= 0.30.0), libselinux1 (>= 2.0.82), libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxau6, libxdmcp6, libxfont1 (>= 1:1.4.2), libxshmfence1, zlib1g (>= 1:1.1.4), perl Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-standalone-server_1.5.0-1~nd+1_amd64.deb Size: 960552 SHA256: f0b3a728e4f5450e052f5e6de0c734b98334865d6fc445329a3f81bb0cfad927 SHA1: 3b0a6ac794697da448ce5af68fd87475b83115c5 MD5sum: 29438ba0653069c96f659345456fd592 Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . This package provides a standalone vncserver to which X clients can connect. The server generates a display that can be viewed with a vncviewer. . Note: This server does not need a display. You need a vncviewer to see something. This viewer may also be on a computer running other operating systems. Package: tigervnc-viewer Source: tigervnc Version: 1.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 422 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), tigervnc-common, libc6 (>= 2.15), libfltk-images1.3 (>= 1.3.3), libfltk1.3 (>= 1.3.3), libfontconfig1 (>= 2.11), libgcc1 (>= 1:4.1.1), libgnutls-deb0-28 (>= 3.3.0), libjpeg62-turbo (>= 1.3.1), libpam0g (>= 0.99.7.1), libstdc++6 (>= 4.6), libwrap0 (>= 7.6-4~), libx11-6, libxcursor1 (>> 1.1.2), libxext6, libxfixes3, libxft2 (>> 2.1.1), libxinerama1, libxrender1, zlib1g (>= 1:1.1.4) Provides: vnc-viewer Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-viewer_1.5.0-1~nd+1_amd64.deb Size: 154894 SHA256: 761ddbacc4ab5073b432434767bdecb6ebf39e4815b35a13e8bcd31f63aa6830 SHA1: f2d92e7afd8a8c6665e7ea9607c204b93bbeae5e MD5sum: 7668a114710bf3bac1626501d3b19a01 Description: Virtual network computing client software for X VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It is implemented in a client/server model. This package provides a vncclient for X, with this you can connect to a vncserver somewhere in the network and display its content in a window. There are vncservers available for other operating systems. Package: tigervnc-xorg-extension Source: tigervnc Version: 1.5.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 602 Depends: neurodebian-popularity-contest, xserver-common (>= 2:1.7.7), keyboard-configuration, udev (>= 149), tigervnc-common, libaudit1 (>= 1:2.2.1), libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libpam0g (>= 0.99.7.1), libstdc++6 (>= 4.6) Recommends: libgl1-mesa-dri (>= 7.1~rc1) Suggests: xfonts-100dpi | xfonts-75dpi, xfonts-scalable Breaks: tigervnc-server (<< 1.1.90) Replaces: tigervnc-server (<< 1.1.90) Provides: vnc-server, vnc-xorg-extension Homepage: http://www.tigervnc.org Priority: optional Section: x11 Filename: pool/main/t/tigervnc/tigervnc-xorg-extension_1.5.0-1~nd+1_amd64.deb Size: 201374 SHA256: 8d6a5bef08b2825cf19419499b9d48660e74b676cdd80a6a53b0ae0f86a38029 SHA1: b94e1ef6efd5b62ff6b8e9b1f73220a67c5a5481 MD5sum: 67e367700f216c76e1bcf9c4b7a1fe22 Description: Virtual network computing server software VNC stands for Virtual Network Computing. It is, in essence, a remote display system which allows you to view a computing `desktop' environment not only on the machine where it is running, but from anywhere on the Internet and from a wide variety of machine architectures. . It contains an X server connector so clients can connect to your local X desktop directly. Package: ubuntu-keyring Version: 2010.+09.30~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd+1_all.deb Size: 11788 SHA256: 87608e20a998b8cb9799d0613e97f0b4f592a26c1433b383ddd813aa69365155 SHA1: e943e925a1106701b6e0c160fd9c06a04490355d MD5sum: 24b363866e0f915e14ecd5ed541ee822 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: utopia-documents Version: 3.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18290 Depends: neurodebian-popularity-contest, libboost-atomic1.62.0, libboost-chrono1.62.0, libboost-date-time1.62.0, libboost-python1.62.0, libboost-system1.62.0, libboost-thread1.62.0, libc6 (>= 2.14), libexpat1 (>= 2.0.1), libfontconfig1 (>= 2.11), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libpcre3, libpcrecpp0v5 (>= 7.7), libpoppler64 (>= 0.48.0), libpython2.7 (>= 2.7), libqt5concurrent5 (>= 5.0.2), libqt5core5a (>= 5.7.0), libqt5gui5 (>= 5.3.0), libqt5network5 (>= 5.4.0), libqt5opengl5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5script5 (>= 5.6.0~beta), libqt5svg5 (>= 5.6.0~beta), libqt5webkit5 (>= 5.6.0~rc), libqt5widgets5 (>= 5.6.0~beta), libqt5xml5 (>= 5.0.2), libssl1.1 (>= 1.1.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4), python2.7, python:any (>= 2.7.5-5~), python-imaging, python-lxml (<< 3.0.0) | python-cssselect, python-lxml, xdg-utils, python-suds Homepage: http://utopiadocs.com Priority: optional Section: science Filename: pool/main/u/utopia-documents/utopia-documents_3.0.0-1~nd+1_amd64.deb Size: 5510316 SHA256: dc21ae91cd3a142e9c6b92eaf84e0a15efd74d7a41ffaf4c6f7f616aadd22885 SHA1: a4087762c7976decf93ee6c4fac878e39ff2c148 MD5sum: 5fe1573639bd5195a22e5242ed868444 Description: PDF reader that displays interactive annotations on scientific articles Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. It makes it easy to explore an article's content and claims, and investigate other recent articles that discuss the same or similar topics. . Get immediate access to an article's metadata and browse the relationship it has with the world at large. Generate a formatted citation for use in your own work, follow bibliographic links to cited articles, or get a document's related data at the click of a button. . Various extensions provide links to blogs, online data sources and to social media sites so you can see what other researchers have been saying about not only the article you're reading but its subject matter too. Package: utopia-documents-dbg Source: utopia-documents Version: 3.0.0-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 56956 Depends: neurodebian-popularity-contest, utopia-documents (= 3.0.0-1~nd+1) Homepage: http://utopiadocs.com Priority: extra Section: debug Filename: pool/main/u/utopia-documents/utopia-documents-dbg_3.0.0-1~nd+1_amd64.deb Size: 55997062 SHA256: 9d2e52da5103ec35e6da7031b45c77e1243af099555767ef90b4038a75869459 SHA1: 193760ace3517a8045dca3e1f7e97de4c084c17c MD5sum: 12f0004b57613c9cf55329d42538c07f Description: debugging symbols for utopia-documents Utopia Documents is a free PDF reader that connects the static content of scientific articles to the dynamic world of online content. . This package contains the debugging symbols for utopia-documents. Build-Ids: 1fea2662b67d1708549c43c1bc82ddd3cac51fdb 262c66b8f0d306e9845b7b01d0d4b7f082ece18d 2e5e39f0b3e1232f6f539d96b2e1f605ff20edca 3e5c8a664c726533691efd7a1882a0db2c0e912c 4179f092e0c874ccf9d836ae89587cb61384d72f 4275ef06ca6ce5608acecc689b521093c6484eb2 5d97fe870a2802a5437511fef50d7a40db597b79 60bb81f2d6fee7021914239ad716c1e5c1831f58 658b2f5437a40b170f0f59c36d76ddfeaad3fe96 65d259d95babe0dc5e4fe19e17fc1727f84d0286 681047856221b30bf0dc00b98179d74cad29e547 6f8918eac76361e132a534d3da6550529de77a0d 7194a67a47884e63d295fae1d6577d24ac2ca922 75f04c48657544bb86f5bd2849a6610288af712d 76c786870ae6ab4dd532c31017886e561102697c 77f542a83777d24f4a3c4b0bc40b27216b112763 803369dd26c04107043fbab0e90a5c400019b0ae 80555a0411fa3833e043283599ab3392ce8c8da1 83df84bf1f4f82f9bf968ddcc84e89a7f9347923 8f2b1232f9f0b6bbe183c03f5eb72bfdfb79aadb 8f8af4b6171f16ee358e856cea1835ca5446a322 918c1cf35a8fd9c77bf2f8afdd2132021f695a96 988a1387a7f8a92ad4d679674e267d9d0cc2c254 9f6f9e10358d0f05ec6ed400f656d5e615e0b3f1 a12529d1fd390f2e747ddbe9ab12d5ffb5cf31f9 a663ad4726869da4a525eefb8d3aacbc7f9e5eba b6e30e5b7f7d35bb0572168955a9e64d6d8b550a c504c14d4daa8ba506f8bcc40da69b6f0ce9862a cf13826efa828656cd6e18c9d594ee777d332152 d5eeb962f1d885e73d92cbd1a7492f83cfa52506 d912011aab4e658fbe2f1ac5a942f9b101235048 d92b8ede401bb874690387dcaad65d31e825c554 db332f9541561ea8fbfaa380093cab6df7fdab6c dd5984b49a415680344d81777a820b1ce0e81e0e e166633f261d9a254a5770f85f66e23a653b87d5 e3b44cfab8dc32f8175e17b04c5fcda782490b22 ee407c0cb4c53346ee2f370bd92d4febf3a7033d f08d98d1ca7b8808d355a7ebc777b34c2ac6564c fa61c2bf75bf9f8276df79d52ecd9f8543c319bc Package: via-bin Source: via Version: 2.0.4-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 628 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libatlas3gf-base, libc6 (>= 2.7), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia2, libx11-6, libxext6, libxmu6, libxt6 Recommends: libvia-doc Conflicts: via, via-utils Replaces: via-utils Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/v/via/via-bin_2.0.4-2~nd+1_amd64.deb Size: 180800 SHA256: 3e1b56a8674466344351554c7bd737ef6a0589fb7b5e7e1e6fdd3e7de3dbb098 SHA1: 78779de019bdbcbd8121f503a2ef160e2dca794a MD5sum: 9bc7639e77d12d05ce260743fff1223b Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: vowpal-wabbit Version: 7.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 51 Depends: neurodebian-popularity-contest, libboost-program-options1.49.0 (>= 1.49.0-1), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0), libvw0 (= 7.3-1~nd+1), zlib1g (>= 1:1.1.4) Suggests: vowpal-wabbit-doc Homepage: http://hunch.net/~vw/ Priority: optional Section: science Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit_7.3-1~nd+1_amd64.deb Size: 17816 SHA256: cd9bca9a2e5e4b53256c6fc6d1f0ae96e0de906db07478b2d4be3fb47251fbcf SHA1: 12b338ec1b7c31f8931afb8c14c75fb4386ea210 MD5sum: 00a3b533483076b89d01cafd6f047eb3 Description: fast and scalable online machine learning algorithm Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing Package: vowpal-wabbit-dbg Source: vowpal-wabbit Version: 7.3-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8286 Depends: neurodebian-popularity-contest, vowpal-wabbit (= 7.3-1~nd+1) Homepage: http://hunch.net/~vw/ Priority: extra Section: debug Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-dbg_7.3-1~nd+1_amd64.deb Size: 1684158 SHA256: b55733ea0a1222b3b90dfbbbeb575bb30b113a570a0f2ba5bb1bccc808281e2a SHA1: 33933ce82e8b85c919597f2a64ff7978c63b0cb8 MD5sum: 052c16ff2b4913a2a20788e018f49a38 Description: fast and scalable online machine learning algorithm - debug files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains debug symbols for the binaries shipped by vowpal-wabbit packages. Package: vowpal-wabbit-doc Source: vowpal-wabbit Version: 7.3-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70918 Depends: neurodebian-popularity-contest Recommends: vowpal-wabbit Homepage: http://hunch.net/~vw/ Priority: optional Section: doc Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-doc_7.3-1~nd+1_all.deb Size: 46989872 SHA256: 451a2f7f540a9cf2f8c276fbb575156845d0cd996733c38a7e11c5da17ac8ce8 SHA1: 18bac3730e0836a77d5f83cb380856e65a1e873b MD5sum: 87ceda4a59e22e74b68c7758551cb4b2 Description: fast and scalable online machine learning algorithm - documentation Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains examples (tests) for vowpal-wabbit. Package: voxbo Version: 1.8.5~svn1241-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10100 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti, matlab-spm8 Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1241-1~nd+1_amd64.deb Size: 3697908 SHA256: a735afd3c8f426cd89fb51297cea9bda046d678c0af61dee46504217920561b7 SHA1: 9d8efb5cdcccd907e9bbd45590a188bf70556f03 MD5sum: 288ff5ad6ddc9be4f4e248a18b49821a Description: processing, statistical analysis, and display of brain imaging data This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others. Package: vrpn Version: 07.30+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 386 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd+1_amd64.deb Size: 113444 SHA256: 0aaa97f744cbb025e34c5db39ac2e55b3e9ae058e23c2ea038a7d45a69e634a1 SHA1: 6912a2794034e07ff04854957818f08a4be10e9c MD5sum: 79fa3076a31ec72d74d582770d95594d Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5779 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1), vrpn (= 07.30+dfsg-1~nd+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd+1_amd64.deb Size: 1811096 SHA256: 2da4b718e8dd1865219cfe2a88dbc2e75f20549b2ca27b86693784a45fe0fb07 SHA1: 91e840b304d38fa96671e130ffdda8448cb69236 MD5sum: c94eaa51b75274d50ab65b5bf1e7a528 Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 282 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), libvtk-dicom0.5, libvtk5.8 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd+1_amd64.deb Size: 72942 SHA256: 2ff31cf1393e58da7315647b546643bf8d9fe1845cc56380f531de19b07777a9 SHA1: 21ef092a777e7bff84916294fc7d31845ddcc026 MD5sum: f0aa358e8fbae4c609294dce20a58074 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 Package: vtk-doc Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 342007 Depends: neurodebian-popularity-contest, doc-base Suggests: libvtk5-dev, vtk-examples, vtkdata Homepage: http://www.vtk.org/ Priority: optional Section: doc Filename: pool/main/v/vtk/vtk-doc_5.8.0-7+b0~nd+1_all.deb Size: 66710216 SHA256: ef2921e37681f7364119b79457483cd3ca7da8cd063a96438cffe23aeba52938 SHA1: abc4b1ccf35fd6c0cc20f67836fb7ffcbfc69161 MD5sum: b7ef2d7972fe60ad7ce2f891faac4205 Description: VTK class reference documentation The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains exhaustive HTML documentation for the all the documented VTK C++ classes. The documentation was generated using doxygen and some excellent perl scripts from Sebastien Barre et. al. Please read the README.docs in /usr/share/doc/vtk-doc/ for details. The documentation is available under /usr/share/doc/vtk/html. Package: vtk-examples Source: vtk Version: 5.8.0-7+b0~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2521 Depends: neurodebian-popularity-contest Suggests: libvtk5-dev, tcl-vtk, python-vtk, vtk-doc, python, tclsh, libqt4-dev Homepage: http://www.vtk.org/ Priority: optional Section: graphics Filename: pool/main/v/vtk/vtk-examples_5.8.0-7+b0~nd+1_all.deb Size: 578892 SHA256: fab181213376a1077411077e48a5640af76ceb2868302e2e03b18e4e6a0859fd SHA1: e0087beef829cbfd4d09abfd52a4e526b2b11963 MD5sum: efe0f5b35bccb7b5f9d251a25970a0ac Description: C++, Tcl and Python example programs/scripts for VTK The Visualization Toolkit (VTK) is an object oriented, high level library that allows one to easily write C++ programs, Tcl, Python and Java scripts that do 3D visualization. . This package contains examples from the VTK source. To compile the C++ examples you will need to install the vtk-dev package as well. Some of them require the libqt4-dev package. . The Python and Tcl examples can be run with the corresponding packages (python-vtk, tcl-vtk). Package: xmhtml1 Source: xmhtml Version: 1.1.7-17~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 528 Depends: neurodebian-popularity-contest, lesstif2 (>= 1:0.94.4), libc6 (>= 2.7), libjpeg8 (>= 8c), libpng12-0 (>= 1.2.13-4), libxpm4 Priority: optional Section: libs Filename: pool/main/x/xmhtml/xmhtml1_1.1.7-17~nd+1_amd64.deb Size: 256340 SHA256: 1ef9b098b951867437f3968e4cb909f13902a663a6b327de6fca40c8d496137b SHA1: 98a07da5ae2516bba1552291554d49e7c07e615e MD5sum: 3f856aa777a181b4e45cab7b804a6a2f Description: A Motif widget for display HTML 3.2 XmHTML is a high performance Motif Widget capable of displaying HTML 3.2 confirming text. Graphics support, lesstif compatibility and extensive documentation are amongst its many features. . This package provides the runtime shared library. The xmhtml-dev package provides the header files, and the static library. Package: xmhtml1-dev Source: xmhtml Version: 1.1.7-17~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 985 Depends: neurodebian-popularity-contest, xmhtml1, lesstif2-dev | libmotif-dev, libc6-dev Conflicts: xmhtml-dev Provides: xmhtml-dev Priority: optional Section: devel Filename: pool/main/x/xmhtml/xmhtml1-dev_1.1.7-17~nd+1_amd64.deb Size: 345488 SHA256: 3a4f50c3b41329d8353d52de915d28d238b2804247daaff7a9ddfcf31450cf6a SHA1: 8ebb1fe2b8e6bbd177c366e8cd1bd3ddd327e7c2 MD5sum: d3c9a90450d6ab9af50a2d6e7b773a6a Description: A Motif widget for display HTML 3.2 XmHTML is a high performance Motif Widget capable of displaying HTML 3.2 confirming text. Graphics support, lesstif compatibility and extensive documentation are amongst its many features. . This is the development kit, containing static libraries and header files necessary to build programs that use xmhtml. The runtime library is provided by the xmhtml package. Package: xppaut Version: 6.11b+1.dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5809 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libx11-6 Homepage: http://www.math.pitt.edu/~bard/xpp/xpp.html Priority: optional Section: science Filename: pool/main/x/xppaut/xppaut_6.11b+1.dfsg-1~nd+1_amd64.deb Size: 4187322 SHA256: 02c241864594f340d32e17d2b3e227b7fe4b3f2a9ce2b6c3b77e8c47dc818c50 SHA1: a12429e18f0a9fcc6567b2a07952a8756d729340 MD5sum: bd13b8e18168d04137f946da0b75993e Description: Phase Plane Plus Auto: Solves many kinds of equations XPPAUT is a tool for solving * differential equations, * difference equations, * delay equations, * functional equations, * boundary value problems, and * stochastic equations. . The code brings together a number of useful algorithms and is extremely portable. All the graphics and interface are written completely in Xlib which explains the somewhat idiosyncratic and primitive widgets interface.