Package: afni-atlases Source: afni-data Version: 0.20180120-1.1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 109419 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni-data/afni-atlases_0.20180120-1.1_all.deb Size: 98215048 SHA256: b7b30ce4345671d92cb08f939b76de42f81a6839abe3d47dba1db0620fe64e0c SHA1: 792d6506cc866acfa54fc71475f823e686f169f7 MD5sum: deaddf5e6992face9b5edeb62644187c Description: standard space brain atlases for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provide AFNI's standard space brain templates in HEAD/BRIK format. Package: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 224 Depends: neurodebian-popularity-contest, python3-datalad (= 0.17.5-1~nd+1), python3-argcomplete (>= 1.12.3), python3:any Suggests: datalad-container, datalad-crawler, datalad-neuroimaging Homepage: https://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.17.5-1~nd+1_all.deb Size: 187092 SHA256: dcfab5ab31ab85c685b4439648c3095efb236b34c92eb2f870fc1376dd0dbab1 SHA1: e8a088bc96e73f10444588eede93689410943c07 MD5sum: a4020bc221d05979fe1738d432660717 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) Package: 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: fail2ban Version: 0.8.13-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1012 Depends: neurodebian-popularity-contest, python (>= 2.4), python-central (>= 0.6.11), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: python-gamin, mailx, system-log-daemon Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.13-1~nd10.04+1_all.deb Size: 186358 SHA256: ca6cef81c93d0b00ee859af9b110742c30f109a0c4ea952e841be01ae21124b5 SHA1: 6be33fee4ff9339fa588de69265e9b650169a7fc MD5sum: 0c259bfa5627cd75ab1d27cba8bd1697 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Package: freeipmi Version: 1.1.5-3~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 0 Depends: neurodebian-popularity-contest, freeipmi-common, freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.1.5-3~nd10.04+1_all.deb Size: 934 SHA256: 3769cc9cc9bf0203401ad60daa0dc9078cd44b1321447232a60a7eed7611bbe3 SHA1: 41ae04f4b899d090a94761d388e16a26dd980eac MD5sum: 7f6d6e9e0cc4f5164d81767e45a16d1b 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 meta-package depends on all separate modules of freeipmi. Package: freeipmi-common Source: freeipmi Version: 1.1.5-3~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 472 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_1.1.5-3~nd10.04+1_all.deb Size: 296958 SHA256: ec43459f9eccaae6c872189adaa36713cc3c00ba13fe223049639ad58f875eb5 SHA1: 3dec137930af1b7b223d0a3c9c981a0fd853835b MD5sum: 72a459678ee1318d96957b9b1089594d 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: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: gmsl Version: 1.1.5-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd10.04+1_all.deb Size: 16572 SHA256: d6f9c0bd18163f7036d375d5b6e63d488e600c49d7537d0677641ac46589ce95 SHA1: 1c024694a374552c6ffc79a4275c5993ff8443ed MD5sum: 68290b3757dd84190cb7c7afe286d656 Description: extra functions to extend functionality of GNU Makefiles The GNU Make Standard Library (GMSL) is a collection of functions implemented using native GNU Make functionality that provide list and string manipulation, integer arithmetic, associative arrays, stacks, and debugging facilities. . Note that despite the name of this project, this library is NOT standard and is NOT written or distributed by the GNU project. Package: golang-github-ncw-rclone-dev Source: rclone Version: 1.41-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 2492 Depends: golang-bazil-fuse-dev, golang-github-aws-aws-sdk-go-dev, golang-github-mreiferson-go-httpclient-dev, golang-github-ncw-go-acd-dev, golang-github-ncw-swift-dev, golang-github-pkg-errors-dev, golang-github-pkg-sftp-dev, golang-github-rfjakob-eme-dev, golang-github-skratchdot-open-golang-dev, golang-github-spf13-cobra-dev, golang-github-spf13-pflag-dev, golang-github-stacktic-dropbox-dev, golang-github-stretchr-testify-dev, golang-github-tsenart-tb-dev, golang-github-unknwon-goconfig-dev, golang-github-vividcortex-ewma-dev, golang-golang-x-crypto-dev, golang-golang-x-net-dev, golang-golang-x-oauth2-google-dev, golang-golang-x-sys-dev, golang-golang-x-text-dev, golang-google-api-dev Homepage: https://github.com/ncw/rclone Priority: optional Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.41-1~ndall0_all.deb Size: 399416 SHA256: 528b53f3312375d31d5cebb95472a57272cf242e14a92cfdf99c45be2ff5511d SHA1: 75f8871fd668e815023267a857b37ad60b9d1c2f MD5sum: a87865eafe10185420838e2e4ffd7b55 Description: go source code of rclone Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers. . This package contains rclone's source code. Package: guacamole Version: 0.6.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 344 Depends: neurodebian-popularity-contest, guacd (>= 0.6), guacd (<< 0.7) Recommends: libguac-client-vnc0 Suggests: tomcat6 | jetty Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole_0.6.0-1~nd10.04+1_all.deb Size: 274886 SHA256: 1337d0da35ba8e576cb208bc912b42171d2c6da0dbeae513c2e094ec71c0f321 SHA1: 5b7c432c1ad5c30e843a1e1e93d3b020986f178e MD5sum: e088cc8eb882f6c9262bf9b2ba0dacd3 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 Version: 0.6.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, debconf, guacamole, tomcat6, libguac-client-vnc0, debconf (>= 0.5) | debconf-2.0 Homepage: http://guacamole.sourceforge.net/ Priority: extra Section: net Filename: pool/main/g/guacamole/guacamole-tomcat_0.6.0-1~nd10.04+1_all.deb Size: 3934 SHA256: 39859176349ffb1ea3f2e9492fda61e49e86eb8efb32d3ef436d203564aef909 SHA1: 06266d05d9c0c3c1601ea4af53734ba2de503815 MD5sum: 3c6de2e27be48cd990c9a62caf3f0210 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: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 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~nd10.04+1_all.deb Size: 9668 SHA256: 11171c867a557dccf1005f009ed4a6af97fb1d06146002c6c34cfe21894eec7c SHA1: 62f5fdd078c2f939b1bb20ca95b3669296a5a9b6 MD5sum: 9777e4ba6307e448ad7788652363f120 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: libfreenect-doc Source: libfreenect Version: 1:0.1.2+dfsg-6~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 548 Depends: neurodebian-popularity-contest Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.1.2+dfsg-6~nd10.04+1_all.deb Size: 85888 SHA256: eb7e328d32a3c95d598f79eeb7d2d7220060e1ff6d64cdc10006103ff31f05ff SHA1: 9d08af477dc490067cb014fa48899f7f817d8c29 MD5sum: 8d6e307534fdb0341a2b3d722b92aba5 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: libjs-underscore Source: underscore Version: 1.1.6-1+deb7u1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest Recommends: javascript-common, libjs-jquery Homepage: http://documentcloud.github.com/underscore/ Priority: optional Section: web Filename: pool/main/u/underscore/libjs-underscore_1.1.6-1+deb7u1~nd10.04+1_all.deb Size: 20850 SHA256: 8f95e1703483391c2dfaffc9394a2c47df845bd97ee8ec3fba417eaab778fb0f SHA1: c42eb031aa6502f24fab30de51ea54d2138efbb8 MD5sum: a64cd50baf73b559e2c773811016ff1c Description: JavaScript's functional programming helper library Underscore is a utility-belt library for JavaScript that provides a lot of the functional programming support that you would expect in Prototype.js (or Ruby), but without extending any of the built-in JavaScript objects. It's the tie to go along with jQuery's tux. . Underscore provides 60-odd functions that support both the usual functional suspects: map, select, invoke - as well as more specialized helpers: function binding, javascript templating, deep equality testing, and so on. It delegates to built-in functions, if present, so modern browsers will use the native implementations of forEach, map, reduce, filter, every, some and indexOf. Package: matlab-support-dev Source: matlab-support Version: 0.0.19~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16 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_0.0.19~nd10.04+1_all.deb Size: 7224 SHA256: ec770a463c5ca2a21e6b1f087ce8be15c7f7e2b077598acc7e842bf9dcc36bd1 SHA1: eb5dc30e951669dd2fbca1141620a2383dbfa83d MD5sum: 501fa4f720dc17c1f3ac1e3e7b9dfbb9 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: mricron-data Source: mricron Version: 0.20140804.1~dfsg.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1836 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~nd10.04+1_all.deb Size: 1665676 SHA256: a20e77d97bc0b03d72df0be8d601c22fec4ae02bc4b5053492c69687b4a5ea7c SHA1: 74cd5479b295e6fb04c8e050cad4b70797bc620c MD5sum: fd6317605806f37756af5d77ebfb1e80 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1220 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~nd10.04+1_all.deb Size: 740038 SHA256: 496ecc492f1844fbc7019aeb11c8502defbebaa392b332c21a31496660c260db SHA1: 06301cab777ac2d434f2cadfde30ebecc70c082c MD5sum: 11106b2d8badc137963e48b1f46c2854 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix-doc Source: mrtrix Version: 0.2.11-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3816 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.11-1~nd10.04+1_all.deb Size: 3321642 SHA256: 5acebf953aca1abf2809a3f199b2457b0798e501dda41cde4a5087bfe3c825d5 SHA1: 89907dc997509ae5a42ffc378837457e20232f5f MD5sum: 94e6c9e168d5c699f4edd17a3e890b6f Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 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~nd10.04+1_all.deb Size: 17854 SHA256: e77748a9b2febcd2c07ea881fae53f3cc2716dcb09a743bddc27990bdc0c6099 SHA1: a63e2825a9e1364cc1ee618c09257dc3317361bd MD5sum: 2a7980450f7a129d35f889235277a199 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.34~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 60 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.34~nd10.04+1_all.deb Size: 21418 SHA256: 0d2937c91bdf500f109599a7a696e4501766f8a9b27abb1bbb057b751d31de45 SHA1: 7a3dca26a7e81736f1a1bb3453820cd3ce4e2c3b MD5sum: b96136f287e1c94dc0d53ac061c979b7 Description: turnkey platform for the neuroscience The NeuroDebian project integrates and maintain a variety of neuroscience-oriented (such as AFNI, FSL, PsychoPy, etc.) and many generic computational (such as condor, pandas, etc.) software projects within Debian. . This package enables NeuroDebian repository on top of the stock Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.34~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.34~nd10.04+1_all.deb Size: 9404 SHA256: 2f948521a4ac9ab760dd6fbb19d3d9254b00c3f3df9f68725cc70389f8f4409a SHA1: 9282aa6a6136c4b8e19d5e5730c9985dd850d742 MD5sum: fcf8380ad66aec3281372382edf72a93 Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.34~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 284 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.34~nd10.04+1_all.deb Size: 117178 SHA256: be94d3e4fbdda3bea673ea6f439f5f813ff88072700f7068daebe1ed503f690b SHA1: 98174fead9b4d594c68d571e6cc423c81862d06c MD5sum: 9b27eadd1f2c48f1d8262d31e712eed5 Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.34~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 160 Depends: devscripts, cowbuilder, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.34~nd10.04+1_all.deb Size: 34240 SHA256: d2ad6252485f4f6de63f65cfac062e668ce42b47074de8d902d8493f46347ca5 SHA1: 7c66e467cb4c7f84c4981f5f7df93f50ef950c06 MD5sum: 4fdeef73c9c875fd9e2670f70030ba4d Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.32~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 148 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~nd10.04+1_all.deb Size: 15354 SHA256: 9a17ae368f4ece2b36928ffb264451bc74196a78ee2e0c28b5eacfafa41832d3 SHA1: 4948d35ec0692ef0949bad96200f7e4768027dbe MD5sum: 1360ad49b306375bc0437c4b3dcc0072 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd10.04+1_all.deb Size: 7622 SHA256: 41eae8898f31f56c685348c1c372495944048e2f0a7047ec41ad85583c736288 SHA1: 7bbcbd2321992758584d1b0bc319dced8d88ec88 MD5sum: 265970eed84a6e6d002e6b3910bb9537 Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.34~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.34~nd10.04+1_all.deb Size: 11492 SHA256: ee0a339aeebb282ab40c498eb0ec757b6b98eedb4d6182172e13b35c0bcaa26d SHA1: 10bab0627a51bbb9549b7991c02afde01e178d4f MD5sum: 6c236b5d22bffc5b2310de11a4cd8c5b Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: opensesame Version: 0.27.4-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27860 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~nd10.04+1_all.deb Size: 25359426 SHA256: f6354be8c92620069de720c5d4e225c1b20d2165133b5b8bf7be6557d294f1da SHA1: 3e9321b59e2e16d7e723bea319b2e5a2845d7ca8 MD5sum: 5a0fe42c0580fdbed610a3771f9d2ac7 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: 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: psychopy Version: 1.76.00.dfsg-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6252 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-pyo, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.76.00.dfsg-1~nd10.04+1_all.deb Size: 3177792 SHA256: c4e7d3fc69da0b4ff07c09dcc5c5bb4c15235dc36dfaffb6ac07927ec0ee9a18 SHA1: 9fd220b9adcc733670e292a7923b5e8590dc5481 MD5sum: 6fd8c638748809854de7c1f063db2040 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: 2.6 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2579.dfsg1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 53608 Depends: neurodebian-popularity-contest Recommends: subversion Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2579.dfsg1-1~nd10.04+1_all.deb Size: 19434404 SHA256: 1e0a6939d26a5debd944bf1acaece3dff5cbdbd14591a07ec90f6e5c3c1918ed SHA1: 8e3ba262934eff7f7568d77be4558b6156996bb4 MD5sum: afac568d1e1f06470c7b17554c57ec0c 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: python-joblib Source: joblib Version: 0.7.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.7.1-1~nd10.04+1_all.deb Size: 54816 SHA256: e518506fb5f8c0cca190d8f4cbde2a2bd57b92d598d1f2203f99f443c5c7fe8b SHA1: f961b25f9a24de893b901fdea8c9b4be503f6542 MD5sum: ee4acde1a264b8a0abc413964858b2d7 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-mvpa Source: pymvpa Version: 0.4.8-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4092 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.8-1~nd10.04+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 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.8-1~nd10.04+1_all.deb Size: 2195398 SHA256: 7429e8b63f838a1821b8f444ff85f95162caf21916382f9439b45b2ae1d0cb44 SHA1: c9795cc37ac3b277a8687a7b8e099f0ba776529c MD5sum: 3e21707251da18a094a5a7e40f37fc47 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 Package: python-mvpa-doc Source: pymvpa Version: 0.4.8-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41240 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~nd10.04+1_all.deb Size: 8772578 SHA256: 9d3dff72aee22b019c206e41988f805c39b2b972580a868baf56b828ca835aea SHA1: 11ea76c7b25370bd570dff4433e2eb9205f2b720 MD5sum: 16f6ef2ef23880e96db96360f11835cf 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-mvpa2 Source: pymvpa2 Version: 2.2.0-3~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4956 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-mvpa2-lib (>= 2.2.0-3~nd10.04+1), python-numpy Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, shogun-python-modular, liblapack-dev Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.6-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.2.0-3~nd10.04+1_all.deb Size: 2400448 SHA256: b90643c1185c5468ef601910ceba7f205c181b244bdf2f278ab4a512eab17a9a SHA1: 8bcc3fa4c727c0fcd41c3f9e68693d0aaec28385 MD5sum: c802046be9caa7220f8eb44e11914f42 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: 2.6 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.2.0-3~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26972 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_2.2.0-3~nd10.04+1_all.deb Size: 5255578 SHA256: 68e44eb7bba9154038faabb1e06b53b903ea0fe07c6019caac7471339dfcb0ff SHA1: 6dfeb7d5e151a12c93c91140d3e5b0a588fd1781 MD5sum: 9943c1e35b7f218651e794e0497f043f 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-nibabel Source: nibabel Version: 1.3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4472 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Provides: python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd10.04+1_all.deb Size: 1826272 SHA256: 6ce4559d731f23439c69646a9d807292fca810914ba1c6292f3cc21591c16e7d SHA1: 265bd0e5f0ed0494bbd73a864e282c488c966142 MD5sum: 634f7acdafeec977f061f19f4ee3451f Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Python-Version: 2.6 Package: python-nibabel-doc Source: nibabel Version: 1.3.0-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2848 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd10.04+1_all.deb Size: 421144 SHA256: cb99401a3ad44dd5d370f1e970511b3c82897997fd77bae769f35395ed7b2cc4 SHA1: 24926e49e4b87844448b28d578476116a601797b MD5sum: d7b77c1b09ba6bbd77af9cd14ac2be93 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-nitime Source: nitime Version: 0.4-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9444 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.4-2~nd10.04+1_all.deb Size: 3908878 SHA256: 5c8519c0b1fa888422578bcb17075de7c13a38f65625ce48602074f677b2f3bb SHA1: c894d1f792483ac1ea260e1aa5112f7a701a8e9f MD5sum: 4459d4a88c22652701e1b1f87ac59c42 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: 0.4-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7100 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.4-2~nd10.04+1_all.deb Size: 5284628 SHA256: 2896180e643badfa156225f11b0c16728e36ae11c18779e73b3ed684732f53d9 SHA1: d5aa42a09080577ed15ef1da6def38119e6e2a2b MD5sum: f164b9a242a718a9071d3e8cf2c56d13 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-openopt Source: openopt Version: 0.38+svn1589-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1612 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 Homepage: http://www.openopt.org Priority: extra Section: python Filename: pool/main/o/openopt/python-openopt_0.38+svn1589-1~nd10.04+1_all.deb Size: 245206 SHA256: fa59841cc93f8aca5496a7459a5901fd178766472cb795a9d0d29f42ba9ba8c4 SHA1: 872744e09191a35ef0b5c3a59c8cd2cf14a0908a MD5sum: 925ae988aa5c48249f2b1b47dc0d5066 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 Package: python-openpyxl Source: openpyxl Version: 1.7.0+ds1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 628 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose, python-pil, python-imaging Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.7.0+ds1-1~nd10.04+1_all.deb Size: 92724 SHA256: da1a093ef2dda5f7ad2587cb2c6c28e94a8eac6738258452c0b464164247b40d SHA1: f21d65f7692f8b6f812d11ecb3ba71ee89aa10cb MD5sum: 85271ced5ddd6c40368494be34d420ca 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-pp Source: parallelpython Version: 1.6.2-2~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 176 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~nd10.04+1_all.deb Size: 34278 SHA256: f872639b3b15097cde0fde900b19c3b0e65b501636696e44c96ec760483c236c SHA1: 38cc6e5fd9a9d83dd8e0434a7c05cc9687057908 MD5sum: bbaf50b3bb451b0ca5da6fb500dc662f 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 Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 884 Depends: neurodebian-popularity-contest, 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~nd10.04+1_all.deb Size: 108376 SHA256: b916e6c9a07dee9d3cb32e9b0caeaf10b4b5493d07a01006608ab2910c31e5a3 SHA1: 3daf37cd7ebe3c73a7838323b0923ea49880f923 MD5sum: a02fa140407db324bd9c5298e100a401 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: 2.6 Package: python-pyentropy Source: pyentropy Version: 0.4.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 108 Depends: neurodebian-popularity-contest, python-support (>= 0.90.0), python-numpy (>= 1.3) Recommends: python-scipy Suggests: python-nose Provides: python2.6-pyentropy Homepage: http://code.google.com/p/pyentropy Priority: extra Section: python Filename: pool/main/p/pyentropy/python-pyentropy_0.4.1-1~nd10.04+1_all.deb Size: 21328 SHA256: 518de5852d1a914ab56f7a20216d864d668c6f4a2130c4f70e591b6320da7a05 SHA1: cf065ff5510f94d8f139751429cfafac6f72b00c MD5sum: 89b8c06967692f897b588b1d7c33e0ce 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 Package: python-pynn Source: pynn Version: 0.7.5-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1024 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~nd10.04+1_all.deb Size: 192168 SHA256: 15882405bed89ceb6ca890dbf78b898c479c8a10b116f165f589a8f085e8e7ee SHA1: 7d0486ac94a092bafc7b57c234f92f723af055ef MD5sum: 566b33cb71745de3f95eb6021b8b95b0 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-pyxnat Source: pyxnat Version: 0.9.1+git39-g96bf069-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 672 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Provides: python2.6-pyxnat Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd10.04+1_all.deb Size: 107392 SHA256: 17b263b684448453c3295128104f29203f41280b5a30d4a6177f67ad28f6b15c SHA1: 021936b398a92d69d2c177f0d67498ff872ff401 MD5sum: c4ffbea49f1e0d704b4cbdec547892ed Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-scikits-learn Source: scikit-learn Version: 0.13.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 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_0.13.1-1~nd10.04+1_all.deb Size: 28610 SHA256: 8cad8f7d3cb89b38a5a3f6834201d9e4c6b47bb37a652f7c2831c5d479537a47 SHA1: d2c6d25f99c7f58cfe9926f2b28709bd5e3d62f8 MD5sum: 867979ebd80d50bfa9c4d3e1bd35c703 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-sklearn Source: scikit-learn Version: 0.13.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3628 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.13.1-1~nd10.04+1), python-joblib (>= 0.4.5) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.6-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.13.1-1~nd10.04+1_all.deb Size: 1012748 SHA256: e110fae6eeec57d58c30aac18f49040c00d68ca0b248853dbbb02b7897c2e47f SHA1: 605351dacccafc007b078774d28f833f3ad86436 MD5sum: 3ffc4c35ec1ddb5c438198268651682d 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: 0.13.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34132 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.13.1-1~nd10.04+1_all.deb Size: 18835492 SHA256: f36afddb680bffa17c86cce1dfeade56f314ffa59f51900cf75bb6feeb5cd3b7 SHA1: e151213bb8164c2ca097b277b6bd189e8a4edd56 MD5sum: 114816671f59ccc94f90ec2fe4b6281b Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-surfer Source: pysurfer Version: 0.3+git15-gae6cbb1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 156 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd10.04+1_all.deb Size: 28756 SHA256: 8f17d3b7caf6efc0dfa7f0622bdcf5b399256f2ada512960b391853484c6f6d8 SHA1: 9f00ab60dbcf3ee47da88bfdb20c9b253864e4a6 MD5sum: cb96e746ed2a7b8a09e52f137579457e 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: 2.6 Package: python3-datalad Source: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4665 Depends: neurodebian-popularity-contest, git-annex (>= 8.20200309~) | git-annex-standalone (>= 8.20200309~), patool, p7zip-full, python3 (>= 3.7), python3-annexremote, python3-distro, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners (>= 0.14~), python3-gitlab, python3-humanize, python3-importlib-metadata | python3 (>> 3.10), python3-iso8601, python3-keyring, python3-keyrings.alt | python3-keyring (<= 8), python3-mock, python3-msgpack, python3-pil, python3-platformdirs, python3-requests (>= 1.2), python3-secretstorage, python3-simplejson, python3-six, python3-tqdm, python3-chardet, python3-packaging, python3:any Recommends: python3-boto, python3-exif, python3-html5lib, python3-httpretty, python3-jsmin, python3-libxmp, python3-lzma, python3-mutagen, python3-pytest, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, datalad-container, datalad-crawler, datalad-neuroimaging, python3-bs4, python3-numpy Breaks: datalad-container (<< 1.1.2) Homepage: https://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.17.5-1~nd+1_all.deb Size: 958872 SHA256: 1f3e16c16863bab40ba92405109ab26c78f19e3e86e2b38733a035221c4e7744 SHA1: 873da190eb5ee83576ff519c2d564e1f841abe5b MD5sum: 7a97a6f55929cc103dd60d7783a9565e Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 22600 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~nd10.04+1_all.deb Size: 10735312 SHA256: f44c1e8b6f9eef9450d0b3b2550c42ab1290a24b381ea8f7c37a3535006ed868 SHA1: 3d0685a57ca9c2a2a28821fc8026efa4dd2f6cd0 MD5sum: 2eb3d5e70f032cfdff3fe5f809473f95 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73316 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd10.04+1_all.deb Size: 52170672 SHA256: 968f2a53b5fa70e478794ad691d2e9fe5519f5488568af40b3c6a7c131dc60ff SHA1: 8ca77e1962dd0b5955b0d80c91e0593e614ea281 MD5sum: cfcd3a37af57e4567a2571328a5c5eb7 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~nd10.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9428 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd10.04+1_all.deb Size: 8648784 SHA256: 89dc09dbcbb353f06172edca76e9fb04bc912fc4b16b21f0df9852d1ba2ae8b8 SHA1: 1813c2b2706202626e5fea3d8d43990ff2d1ec87 MD5sum: de8433f1d59f49a88a1adaca9cca5667 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: testkraut Version: 0.0.1-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 488 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~nd10.04+1_all.deb Size: 83982 SHA256: 213ac393acdb6f5f1f8dc583ba91c65233e8da3f39d884214ca244fa06cc9a06 SHA1: cb60f298ece55af21951268a3d320c1ce1ab4e69 MD5sum: ab1a6f4b6426785aa4fd88ff655410da 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 Package: vowpal-wabbit-doc Source: vowpal-wabbit Version: 7.3-1~nd10.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 71128 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~nd10.04+1_all.deb Size: 50202312 SHA256: 0943e4a36d862217208070bb9038af05bda8096bc4c4b91a6211361a5a7d1ad4 SHA1: 600e217196d2930b099c08ee90f87ee3be760bfb MD5sum: 051392dd21828f90ab453cd0e5562853 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: youtube-dl Version: 2021.12.17-1~nd110+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5937 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3:any Recommends: aria2 | wget | curl, ca-certificates, ffmpeg, mpv | mplayer, python3-pyxattr, rtmpdump, python3-pycryptodome Suggests: libfribidi-bin | bidiv, phantomjs Homepage: https://ytdl-org.github.io/youtube-dl/ Priority: optional Section: web Filename: pool/main/y/youtube-dl/youtube-dl_2021.12.17-1~nd110+1_all.deb Size: 1128692 SHA256: 75859d2f34a475fc0f199cd6d2b73e18c29cda44406530964890dcb790008eca SHA1: 09f85f2abc32eb5e9c2ccd6bfd1354ea332b6489 MD5sum: 6d04814be91bd9f85a7d3793ff2a2fb3 Description: downloader of videos from YouTube and other sites youtube-dl is a small command-line program to download videos from YouTube.com and other sites that don't provide direct links to the videos served. . youtube-dl allows the user, among other things, to choose a specific video quality to download (if available) or let the program automatically determine the best (or worst) quality video to grab. It supports downloading entire playlists and all videos from a given user. . Currently supported sites (or features of sites) are: . 1tv, 20min, 220.ro, 23video, 24video, 3qsdn, 3sat, 4tube, 56.com, 5min, 6play, 7plus, 8tracks, 91porn, 9c9media, 9gag, 9now.com.au, abc.net.au, abc.net.au:iview, abcnews, abcnews:video, abcotvs, abcotvs:clips, AcademicEarth:Course, acast, acast:channel, ADN, AdobeConnect, adobetv, adobetv:channel, adobetv:embed, adobetv:show, adobetv:video, AdultSwim, aenetworks, aenetworks:collection, aenetworks:show, afreecatv, AirMozilla, AliExpressLive, AlJazeera, Allocine, AlphaPorno, Amara, AMCNetworks, AmericasTestKitchen, AmericasTestKitchenSeason, anderetijden, AnimeOnDemand, Anvato, aol.com, APA, Aparat, AppleConnect, AppleDaily, ApplePodcasts, appletrailers, appletrailers:section, archive.org, ArcPublishing, ARD, ARD:mediathek, ARDBetaMediathek, Arkena, arte.sky.it, ArteTV, ArteTVEmbed, ArteTVPlaylist, AsianCrush, AsianCrushPlaylist, AtresPlayer, ATTTechChannel, ATVAt, AudiMedia, AudioBoom, audiomack, audiomack:album, AWAAN, awaan:live, awaan:season, awaan:video, AZMedien, BaiduVideo, Bandcamp, Bandcamp:album, Bandcamp:weekly, bangumi.bilibili.com, bbc, bbc.co.uk, bbc.co.uk:article, bbc.co.uk:iplayer:playlist, bbc.co.uk:playlist, BBVTV, Beatport, Beeg, BehindKink, Bellator, BellMedia, Bet, bfi:player, bfmtv, bfmtv:article, bfmtv:live, BibelTV, Bigflix, Bild, BiliBili, BilibiliAudio, BilibiliAudioAlbum, BiliBiliPlayer, BioBioChileTV, Biography, BIQLE, BitChute, BitChuteChannel, BleacherReport, BleacherReportCMS, blinkx, Bloomberg, BokeCC, BongaCams, BostonGlobe, Box, Bpb, BR, BravoTV, Break, brightcove:legacy, brightcove:new, BRMediathek, bt:article, bt:vestlendingen, BusinessInsider, BuzzFeed, BYUtv, Camdemy, CamdemyFolder, CamModels, CamTube, CamWithHer, canalc2.tv, Canalplus, Canvas, CanvasEen, CarambaTV, CarambaTVPage, CartoonNetwork, cbc.ca, cbc.ca:olympics, cbc.ca:player, cbc.ca:watch, cbc.ca:watch:video, CBS, CBSInteractive, CBSLocal, CBSLocalArticle, cbsnews, cbsnews:embed, cbsnews:livevideo, CBSSports, CCMA, CCTV, CDA, CeskaTelevize, CeskaTelevizePorady, channel9, CharlieRose, Chaturbate, Chilloutzone, chirbit, chirbit:profile, cielotv.it, Cinchcast, Cinemax, CiscoLiveSearch, CiscoLiveSession, CJSW, cliphunter, Clippit, ClipRs, Clipsyndicate, CloserToTruth, CloudflareStream, Cloudy, Clubic, Clyp, cmt.com, CNBC, CNBCVideo, CNN, CNNArticle, CNNBlogs, ComedyCentral, ComedyCentralTV, CommonMistakes, CondeNast, CONtv, Corus, Coub, Cracked, Crackle, CrooksAndLiars, crunchyroll, crunchyroll:playlist, CSpan, CtsNews, CTV, CTVNews, cu.ntv.co.jp, Culturebox, CultureUnplugged, curiositystream, curiositystream:collection, CWTV, DailyMail, dailymotion, dailymotion:playlist, dailymotion:user, daum.net, daum.net:clip, daum.net:playlist, daum.net:user, DBTV, DctpTv, DeezerPlaylist, defense.gouv.fr, democracynow, DHM, Digg, DigitallySpeaking, Digiteka, Discovery, DiscoveryGo, DiscoveryGoPlaylist, DiscoveryNetworksDe, DiscoveryVR, Disney, dlive:stream, dlive:vod, Dotsub, DouyuShow, DouyuTV, DPlay, DRBonanza, Dropbox, DrTuber, drtv, drtv:live, DTube, Dumpert, dvtv, dw, dw:article, EaglePlatform, EbaumsWorld, EchoMsk, egghead:course, egghead:lesson, ehftv, eHow, EinsUndEinsTV, Einthusan, eitb.tv, EllenTube, EllenTubePlaylist, EllenTubeVideo, ElPais, Embedly, EMPFlix, Engadget, Eporner, EroProfile, Escapist, ESPN, ESPNArticle, EsriVideo, Europa, EWETV, ExpoTV, Expressen, ExtremeTube, EyedoTV, facebook, FacebookPluginsVideo, faz.net, fc2, fc2:embed, Fczenit, filmon, filmon:channel, Filmweb, FiveThirtyEight, FiveTV, Flickr, Folketinget, FootyRoom, Formula1, FOX, FOX9, FOX9News, Foxgay, foxnews, foxnews:article, FoxSports, france2.fr:generation-what, FranceCulture, FranceInter, FranceTV, FranceTVEmbed, francetvinfo.fr, FranceTVJeunesse, FranceTVSite, Freesound, freespeech.org, FreshLive, FrontendMasters, FrontendMastersCourse, FrontendMastersLesson, FujiTVFODPlus7, Funimation, Funk, Fusion, Fux, Gaia, GameInformer, GameSpot, GameStar, Gaskrank, Gazeta, GDCVault, generic, Gfycat, 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