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: bats Version: 0.4.0-1~nd13.10+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~nd13.10+1_all.deb Size: 15354 SHA256: ae4634d77dfe177a9a368f801a38fdfd84e9404aac5835747f325ea48737e89b SHA1: f844d01d0f13b583aae83e490c55f3d65387b749 MD5sum: b25a913883a598e2af29dca3ae5940ad 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: 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: dh-systemd Source: init-system-helpers Version: 1.18~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, perl, debhelper Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/dh-systemd_1.18~nd13.10+1_all.deb Size: 14620 SHA256: 764af1394bd240e76a81f7edf1fa53c0571563069f81d5118ef533300c64b3af SHA1: 8a2c4f6ea21ca972598fdc38018f79b6f38f890d MD5sum: d51c9ea06e5f89f86c845ad6db79e371 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: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 7224862 SHA256: b676b82109d135052588444785b36d65fe3e96cd7199cbbb0bd7c2c07d3cd801 SHA1: f9190f6dbe6d6596884363f4aeadd7181991eb43 MD5sum: 06ebb1802f177f2a117f1d51a2213ec5 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: fail2ban Version: 0.8.13-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 563 Depends: neurodebian-popularity-contest, python:any (>= 2.7.1-0ubuntu2), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: python-gamin, mailx, system-log-daemon Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.13-1~nd13.10+1_all.deb Size: 185412 SHA256: 7aca02dc39e8e4f3d329df9ff00c0d51ab86c72659881e2444979dc88f15a865 SHA1: 92b0c1141a129ac89a10183bcdc409ff3803eaab MD5sum: 4cf05f3ab6d0f452cd63330a22625ec4 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Package: fis-gtm Version: 6.0-003-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, fis-gtm-6.0-003 Provides: mumps Homepage: http://sourceforge.net/projects/fis-gtm Priority: optional Section: database Filename: pool/main/f/fis-gtm/fis-gtm_6.0-003-2~nd13.10+1_all.deb Size: 15110 SHA256: 9ba6618261224b166bce34cecda0b2fb0136b7983a6b39f7f2dc22a62e546f7b SHA1: 84321d76c4d3d513ceea2e595d43da5b0d18fc4d MD5sum: 0cb05e1971635c11d9d845e656892905 Description: metapackage for the latest version of FIS-GT.M database GT.M is a database engine with scalability proven in large real-time transaction processing systems that have thousands of concurrent users, individual database file sizes to the Terabyte range (with virtually unlimited aggregate database sizes). Yet the light footprint of GT.M allows it to also scale down for use in small applications and software appliances (virtual machines). . The GT.M data model is hierarchical associative memory (i.e., multi-dimensional array) that imposes no restrictions on the data types of the indexes or content - the application logic can impose any schema, dictionary or data organization suited to its problem domain. (Database engines that do not impose schemas, but which allow layered application software to impose and use whatever schema that is appropriate to the application are popularly referred to as "document oriented", "schemaless" or "schema-free" databases.) . GT.M's compiler for the standard M (also known as MUMPS) scripting language implements full support for ACID (Atomic, Consistent, Isolated, Durable) transactions, using optimistic concurrency control and software transactional memory (STM) that resolves the common mismatch between databases and programming languages. Its unique ability to create and deploy logical multi-site configurations of applications provides unrivaled continuity of business in the face of not just unplanned events, but also planned events, including planned events that include changes to application logic and schema. . This metapackage always depends from the default fis-gtm version. Package: freeipmi Version: 1.4.5-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.5-2~nd13.10+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.5-2~nd13.10+1_all.deb Size: 1124 SHA256: a8dedbddf90977a92eda7569dcec52bcddddaa614d11f4d2ed08bd7af415b2ba SHA1: 6ab1c5f608a41982c7f3258886e2028cc1dd6b03 MD5sum: 63c1aaa5972ba12840783bceeed06c8d 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-common Source: freeipmi Version: 1.4.5-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 304 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_1.4.5-2~nd13.10+1_all.deb Size: 195598 SHA256: 8ba05324d87f6d9c5c681294b9d9eee1cee6c8b1221e72c8569e240c00a35115 SHA1: 6e161d97de75d8028ce8e1f90e600cad2d39a225 MD5sum: e9cca2c1959981b23ffa97b6677bd641 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: fslview-doc Source: fslview Version: 4.0.1-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2874 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-2~nd13.04+1+nd13.10+1_all.deb Size: 2346584 SHA256: d18c868829872ad3b67c0902b9dba50a49c1b221a498c79efda662247520d444 SHA1: 0eee7201a822e7f6e330c233f732e29df7e2cfa1 MD5sum: 1fbf262f0226c131b9096afe8705b64b Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: gmsl Version: 1.1.5-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 78 Depends: neurodebian-popularity-contest, make Homepage: http://gmsl.sourceforge.net/ Priority: optional Section: devel Filename: pool/main/g/gmsl/gmsl_1.1.5-1~nd13.10+1_all.deb Size: 16572 SHA256: e77e8b0cf5aa8f3268acd7dac0ff46ae45601861b5930c7d9837916d100a4d9f SHA1: 1c4d0c34ad85f1e9a824b5d3fe3825fc661b5e45 MD5sum: c608e38f4291221800b37cbcdde548f4 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: impressive Version: 0.10.5-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 331 Depends: neurodebian-popularity-contest, python-opengl, python-pygame, python-imaging, poppler-utils | xpdf-utils (>= 3.02-2) Recommends: pdftk, perl Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.10.5-1~nd13.10+1_all.deb Size: 163114 SHA256: 8b2e8f8626086d76a50da1553472b14434423592095801193de4a52e9878706d SHA1: e902bda102a4c304618d5cdd18d0161498247081 MD5sum: a7ca008ac60d8e7c1babcb0c0e892d28 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 9792 SHA256: 0b9a6311f3505e3617a06a6c9c484f2d75b0c5d72c8399f677eda471fc8d0acd SHA1: 68241f8405acc62727278602c524900998fa8dc4 MD5sum: 27174485f0fac376de0ebe388d427929 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: init-system-helpers Version: 1.18~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29 Depends: neurodebian-popularity-contest, perl Breaks: systemd (<< 44-12) Multi-Arch: foreign Priority: extra Section: admin Filename: pool/main/i/init-system-helpers/init-system-helpers_1.18~nd13.10+1_all.deb Size: 14308 SHA256: f8dea42aca6f6a46079f4fe2a03522a57b153b62680d795ad48db7a031e0b80c SHA1: 646528203732c0596be00f4765535f4c7213d319 MD5sum: be8566f16d760a30154a9aa852fa3068 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: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+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), python:any (>= 2.7.1-0ubuntu2) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython1x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython1x/ipython1x_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 4486488 SHA256: 6016a44c2c4ebb56d8df6ce5cc15cc7c12ab6d093667f1910829fc12ca964581 SHA1: 7a208528c1a006209745efb2e691c3b1b6770b0a MD5sum: 313e52e500fd07fe87d6e12893fa7fde Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-doc Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10391 Depends: neurodebian-popularity-contest, libjs-jquery, ipython1x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython1x/ipython1x-doc_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 4192434 SHA256: 6c1ed43bf785fc0278365207e66311c6cace48f4631178de5fcdc15fea6431cf SHA1: bd3d87ffc7b305c9db0ca716ad99fdc3c9949ede MD5sum: 120527fda1c679b4b209ed795f3c3a52 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython1X module thus not conflicting with system-wide installed IPython Package: ipython1x-notebook Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-notebook_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 908 SHA256: 937c26f74dc38685ccda4a8278e7953f3b6c80aaebd36947fd876785a6429e68 SHA1: 34d85abfe2a419d600769382228b62f121a76b9d MD5sum: af008fba904dd966354b267c7819efb8 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython1x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython1x-parallel Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython1x/ipython1x-parallel_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 836 SHA256: d031b9d628624c792764afb15e2e0c0f4f663064bef7b0045edb641106d09310 SHA1: e894ddc3eb3662df68d481f510b7a8251f29be93 MD5sum: 8a22a6f641780b0b77f58a614c4d26f0 Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython1x-qtconsole Source: ipython1x Version: 1.1.0+git7-gf5891e9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython1x/ipython1x-qtconsole_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb Size: 924 SHA256: 71f4ce8327f6abb548302e1b70ed8d1ea0c824b0bee5f6b65b8e7d0b19c678a4 SHA1: 89622b1042ff646e64e3334bebb09e4418c144ec MD5sum: 7aefa70e0eeab5e8034b8d0230e5551c 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: libfreenect-doc Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 584 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~nd13.10+1_all.deb Size: 112720 SHA256: 4e9ecaec616ba60fe143fa29653a947288293f3044e7c351d6429253418d0db5 SHA1: 26c7eb6da9c8f125263885149505ef431a3b20b0 MD5sum: 0e21194874596fc9d9d733818b61ad5c 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: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12967 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd13.10+1_all.deb Size: 778516 SHA256: 8f06393aff92f185a6042cb6ee47d7532d96fea914144e46e225de1cd319cfe8 SHA1: 0c1c712090e2a7174b0f2e606620c99256ee1583 MD5sum: 37bf01632536165ffdc215df44a41d86 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-doc Source: libmialm Version: 1.0.7-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Depends: neurodebian-popularity-contest Suggests: devhelp Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/libm/libmialm/libmialm-doc_1.0.7-2~nd13.10+1_all.deb Size: 25096 SHA256: b7b29df26ec96b31768f300bebd2b4616dc2e174950f6f14bf168096ba314b2e SHA1: ed8644c567cca132ab21734276601a89020a6296 MD5sum: f2251ecb3e69794ac1f0273c4235b849 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: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44757 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1_all.deb Size: 5084534 SHA256: 1be94d45b7591bb19c297d36d49b4953d52d2937871d562b5e7458949a61ff24 SHA1: 1d0c85322ff24b919cd67238547fa7f127840206 MD5sum: 7b2d3c92c8eab3f2d8277ccb55636874 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: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1115 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd13.10+1_all.deb Size: 71552 SHA256: b358de7b7f71a7702ea79fe831464a5190173de8dab6003a959fc39e4d85351b SHA1: e640fd3016c96cf4103de522a7b298b5d44c9d8c MD5sum: 729a93c34c1b29e8223bdd9de4a8dba4 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: mricron-data Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1678 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1664274 SHA256: 68ce273dcde27c573053b0978397336aee2bd4bd411278f9950e11a9aac27989 SHA1: 3e484323149fadfcff8ba1c124dc23cb188c9cf6 MD5sum: 895c3045ff8a360f730cb00692214f7f Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 980 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 735992 SHA256: e5a580a7bae121b13d1e22d622c6de9466ca7e01fe5abc460fe3285906c721f5 SHA1: f39199a65bb18cded064d3123319184a4c9e6878 MD5sum: 92dbcb21cb1674db34d549b65a2c61d7 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: 0.2.12-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3522 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.12-1~nd13.10+1_all.deb Size: 3316736 SHA256: a7f885637a8ef080c2c53cf5e8860460c1bebd5400cb6a33ae3d54327f30897a SHA1: 601ce804b0a5c1cd62112f98bca8bcdfad2940d6 MD5sum: 8558e8dd95501ddf5513c6276946d5b0 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~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd13.10+1_all.deb Size: 17872 SHA256: b5dd3b1f3de6be4de25c7fb80155dac1cf0685f4492161e88805fe0a8413bb03 SHA1: c41f13298848516a7423e2376c3362c3a0ec91d5 MD5sum: 15959b1f643cff952664a481f21a62e3 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: 0.36~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.36~nd13.10+1_all.deb Size: 21782 SHA256: e7e1a3c041a41fa419493ee124c7a6c314ed2e58f9a3bd765481fca55aa462df SHA1: 8cecf1301da557af04784b57954063e58f664b68 MD5sum: 0f3a1f64ef2247415e1d62bc5d46bfad 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: 0.36~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.36~nd13.10+1_all.deb Size: 9680 SHA256: a30fb5dbc908db54cbcbff30262a5663244ca028e713ed5a19f75ada95bf94e6 SHA1: 806d0a8d1ef0c7078424637a4b53cd129d6f4667 MD5sum: e222e05da73988a1d61f54a57c5f1e5e 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: 0.36~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.36~nd13.10+1_all.deb Size: 117854 SHA256: aaa2c0634db9ad3c67e2c2acd2caaf8c92a4998c5125cd76c417b754cc77f5b6 SHA1: 6d4c121bd4df19b5005b592e88482da2ce2c410f MD5sum: 914fdd26181da10307dfdb1334f9a724 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: 0.36~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 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_0.36~nd13.10+1_all.deb Size: 34692 SHA256: 94a5e035cb98398d7b79f9224bc1f16a26f3364489ffa9f0c7f33bd7dcb82128 SHA1: 7f71c6a9beb050d28e72c9462d290942a0817e17 MD5sum: 490a4ac8a8387d0ccb7717259aeee5a9 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd13.10+1_all.deb Size: 15362 SHA256: 87323f095aec2a104af3633b311a231531765476441b4e34dd49f40c426537cc SHA1: 6204775b5aee5af8692750f2011b1311cb16c0d5 MD5sum: 3473a9e49831da14507f033d87a05481 Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.32~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd13.10+1_all.deb Size: 7626 SHA256: 971b8c7f9c290670165b5b4480681aa056ad296d0a66d4b7f5b13699f898dcf3 SHA1: 4520e7bcbbdedcf856195ca443fef0bc0e14a99f MD5sum: 84091b28d29885a610724d371af9321c 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: 0.36~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.36~nd13.10+1_all.deb Size: 11772 SHA256: c0fc64bbe2be7271e78baaa71ab853b4252584dbe50f882ac5373496ec209aac SHA1: 82ffc7f76d029829f14460ea203888f4fc8a8495 MD5sum: e55180ae39ee51d69fc1b78330b38a0b Description: Helper for NeuroDebian popularity contest submissions This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 606 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.9-1~nd13.10+1_all.deb Size: 615602 SHA256: 6cc30036ea61bc7259d9e53fcafb8362a8f40bd05a1a41d31aeedfa1dc5b3bde SHA1: 61370124480b61469e6c31219b2cbf2743c67207 MD5sum: ca4bed6e18112c749e83a3e195b7ecb5 Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nuitka Version: 0.5.13+ds-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2405 Depends: neurodebian-popularity-contest, g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.1-0ubuntu2) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.13+ds-1~nd13.10+1_all.deb Size: 647254 SHA256: aad9144a66b62fab281e23eb3250be2fbc9a98e60435c3e8026f37a7684839ba SHA1: 28d34afba43dc80f4128b9846241cebb1c86981d MD5sum: 32965c940aa6af73a26cdcc1ea19bf78 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: opensesame Version: 0.27.4-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26639 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd13.04+1+nd13.10+1_all.deb Size: 25359292 SHA256: 7eb6ad30eac4d0899910debe19d8f7d67bc93d31570781782b9c297f0ed84053 SHA1: 1f09336470b48636de42f67e545284e24f6b15ef MD5sum: 076b71a8a142d25cbc32e85c9e11720f 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: patool Version: 1.7-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 162 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: file Suggests: arj, bzip2 | lbzip2 | pbzip2, cabextract | lcab, ncompress, cpio | bsdcpio, lzop, p7zip-full, rar | unrar | unrar-nonfree, zip | unzip, rpm2cpio, binutils, lha, unace | unace-nonfree, arc | nomarch, unalz, lrzip (>= 0.551), tar (>= 1.26) | star | bsdtar, rzip, zoo, xdms, orange, lzip | plzip | clzip | pdlzip, sharutils, flac, shorten, unadf, archmage, genisoimage, python-argcomplete Homepage: http://wummel.github.io/patool/ Priority: optional Section: utils Filename: pool/main/p/patool/patool_1.7-1~nd13.10+1_all.deb Size: 33444 SHA256: 1fe954a0c4dab1d0f0c99de1831ebce10e0609366e08111527cb20850f16e1de SHA1: 4b969ad8c92d118a935f2204153f4debdce9a30c MD5sum: c648536d9fe6202cfe65618d09737c86 Description: command line archive file manager Various archive formats can be created, extracted, tested, listed, compared, searched and repacked by patool. The archive format is determined with file(1) and as a fallback by the archive file extension. . patool supports 7z (.7z), ACE (.ace), ADF (.adf), ALZIP (.alz), AR (.a), ARC (.arc), ARJ (.arj), BZIP2 (.bz2), CAB (.cab), compress (.Z), CPIO (.cpio), DEB (.deb), DMS (.dms), FLAC (.flac), GZIP (.gz), ISO (.iso), LZH (.lha, .lzh), LZIP (.lz), LZMA (.lzma), LZOP (.lzo), RAR (.rar), RPM (.rpm), RZIP (.rz), SHAR (.shar), SHN (.shn), TAR (.tar), XZ (.xz), ZIP (.zip, .jar) and ZOO (.zoo) formats. . It relies on helper applications to handle those archive formats (for example bzip2 for BZIP2 archives). . The archive formats TAR, ZIP, BZIP2 and GZIP are supported natively and do not require helper applications to be installed. Package: psychopy Version: 1.79.00+git16-g30c9343.dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12186 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-pyo, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.79.00+git16-g30c9343.dfsg-1~nd13.10+1_all.deb Size: 8109686 SHA256: f4fc3b7b26f014866bf47413c9221078562fa0655004f2cd266f64918f2491ce SHA1: 614193806aefe60e2b8ef707465a2f2810b6932a MD5sum: 331d341dbfee01cfe41c80e209b37fb6 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: 3.0.12.20150316.dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 214787 Depends: neurodebian-popularity-contest Recommends: subversion Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.12.20150316.dfsg-1~nd13.10+1_all.deb Size: 30549150 SHA256: 0bc889358e8581b17a04cd29622e3981530e6133d809f213c9cd5721abb25ea1 SHA1: 17ce75e4c03c80ec2073e5e9821e7b0ed2ba8d65 MD5sum: 1e22cb16d5c3d87e510277de8678460a 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-brian Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2336 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.1-1~nd13.04+1+nd13.10+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 549212 SHA256: 988ae070c4a1f6ff509598736733a666ccf337407b9f1b54fe51dcc41f453071 SHA1: c0d825559c7fa6cc94df99326cd0bf135b9af3d2 MD5sum: 19b10c71f6878e6e0ca5eea1637284fe Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6810 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 2247326 SHA256: 02613c13a722df13156e9ae18dfaa9328810fca303950ba19a1356da2a77a3a7 SHA1: 4341f8754a618702eb2f745017fc50c57b88b2e6 MD5sum: 90d9953badd70e123284cef6b7fb2904 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-dicom Source: pydicom Version: 0.9.9-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1553 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) 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~nd13.10+1_all.deb Size: 427518 SHA256: 8e43d606453b9e57ff2ee8b58ffa0d3ef298ac9922551bd723e2d837fe48789f SHA1: 4617141922743520684a00e96b387af5b66a3f46 MD5sum: 7973e4e6c677a23b852df69161388ea4 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.9.2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4661 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-dipy-lib (>= 0.9.2-1~nd13.10+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.9.2-1~nd13.10+1_all.deb Size: 2501476 SHA256: 190f5e5c241e1265886220dc21cefe626969b42fd7aa3ea2996eb37a8f5d513d SHA1: 031546cf12db080c0bd099d68905f79395884de4 MD5sum: 0680d2ba656e682c10dfa70ab2225762 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.9.2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12493 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.9.2-1~nd13.10+1_all.deb Size: 11079492 SHA256: 99737968f363b8c7b0cbb1b202a5213a9a6ab19e0b0c77a09aedbcc155bb9b06 SHA1: 79ada6ef2efe248cfb2f8a0c3ae03aec64f3d7e4 MD5sum: e3379fdb2e65923b2a4820929a323531 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-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2413 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd13.10+1_all.deb Size: 838766 SHA256: ab74cda18df44bd6541469e7ca79f7d0c07d9c1e4d17583b43e00852686423c7 SHA1: 19b576f1fc211585db1dd05738f8d49f31dfeaa4 MD5sum: ce52d710356c354d40f488953a2fa0e7 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-git Version: 0.3.6+git28-g88f3dc2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1209 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-gitdb (>= 0.6.4), git (>= 1:1.7) | git-core (>= 1:1.5.3.7), libjs-jquery Suggests: python-smmap Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_0.3.6+git28-g88f3dc2-1~nd13.10+1_all.deb Size: 374856 SHA256: 63644e0b8d3aaecb574aaf36995da72427ee4beaa21af936004df83124cd97fc SHA1: e81c4cb9f2a491a4469093362e30e43e02a3042e MD5sum: f1b61a12ce2b8d2f64feffa7f79c2f09 Description: Python library to interact with Git repositories python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. Python-Version: 2.7 Package: python-jdcal Source: jdcal Version: 1.0-1~nd13.10+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~nd13.10+1_all.deb Size: 8314 SHA256: e788d4836be933dcee222c07b78bcddd6b0002a1e40f37cddc8ec3c84260449f SHA1: 7b21e530f59b1cbc57322c2c8a95ac2c6296b9e3 MD5sum: a65cf080362286bcb8595f265a2247ba 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: 0.8.4-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 265 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.8.4-1~nd13.10+1_all.deb Size: 75878 SHA256: 2d8b87163ec630baa12189e47c1ca48135a313ef7eb22d587813e59f9a3aaa48 SHA1: 0030dd68bc428b6ee5fd12191ea12469090f5e0d MD5sum: 76df833a0c91fe8393626ca9e078cb03 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 2 version. Package: python-mdp Source: mdp Version: 3.3+git19-g4ec2f29-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1519 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-scipy, python-libsvm, python-joblib, python-scikits-learn | python-sklearn, python-pp Suggests: python-py, shogun-python-modular Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.3+git19-g4ec2f29-1~nd13.10+1_all.deb Size: 494700 SHA256: b44f1d0804531268393ffa869220941afe3bd83807f7aad26c5eb831fa5d25d3 SHA1: 43f70e4c445fd4d606be21714711ca28bbf5b6c8 MD5sum: ba2f90941b4354477ed78260cfdc72d1 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: 0.8.6+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7247 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui Recommends: python-nose, mayavi2 Suggests: python-dap, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.8.6+dfsg-1~nd13.10+1_all.deb Size: 4380056 SHA256: 512510b96025b7f8671aa927693039e9549f72396d40628e21e149bad25d1fcf SHA1: fe62ac2232e6f1b113040462389362bcc2267f8f MD5sum: d710cdddf9665a0d9ea52267a67a69b8 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-doc Source: mpi4py Version: 1.3.1+hg20131106-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 256 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.3.1+hg20131106-1~nd13.10+1_all.deb Size: 73120 SHA256: 0b134f816eac4329b2752f7b2e16c6956ecd2ffc949074ee1c9eb390675b9e18 SHA1: 81d29c74376e92ec5c3386727d44258ffba85f8a MD5sum: d041dee2f5707ed612450c5d7b65f545 Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-mvpa2 Source: pymvpa2 Version: 2.3.1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6541 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.7.1-0ubuntu2), python-mvpa2-lib (>= 2.3.1-1~nd13.10+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, shogun-python-modular, liblapack-dev, python-pprocess Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.3.1-1~nd13.10+1_all.deb Size: 3907244 SHA256: 5e1707f0313bb9d981828aab7d64ff660e736d76c8ebb2ebc62c70b0c17b376c SHA1: 211b202803e85d349bacdc99700984dc936532fc MD5sum: 179923a6f4ce38d5500e1a4753067b88 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.3.1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27416 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.3.1-1~nd13.10+1_all.deb Size: 6495502 SHA256: 120fe1db1396a3e5ac5036899f7420681226557c330098e03c43379148d320c3 SHA1: 71f2bbcaa462eb22d64c2d219e3e45ce8a9a9127 MD5sum: 87c22e7d12342b934333e9ed090dd4c0 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-neo Source: neo Version: 0.3.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2913 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Suggests: python-nose Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.3.3-1~nd13.10+1_all.deb Size: 1503984 SHA256: 668a8a19ca6d89550b880413cee169d8727d89081ed0d02bbd0a9d4c483b8be5 SHA1: 8a212cb80c2fcacfed0171546bb94d520cc51b3a MD5sum: 51c356fce152a7618dc7e0dd9fd3ec90 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-neuroshare-doc Source: python-neuroshare Version: 0.9.2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 283 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~nd13.10+1_all.deb Size: 167186 SHA256: 4eb6cf0dc8663bb47bf6e7d8a9033c3138d972bc7fa40016ead51ee0b2fb6e2e SHA1: 12bdc8e657a8ec715171d0af414e8b2f67da5c09 MD5sum: 3a65cfb8dd17fdebc8bbdd51788d70a5 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~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd13.04+1+nd13.10+1_all.deb Size: 32584 SHA256: e38eecc0a3733f22718924755061092da20b4ce592bc1f0044cc0fcd3b5d946e SHA1: acb8d58022eca092a686c7665b5225fca8074794 MD5sum: 3eedb70c2ed5b4a73f58c6b2981af4f0 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Provides: python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 1816464 SHA256: 1e268bf6e0aedbb094d99515235bca7859435018effc35b32c1ad61bc8f45576 SHA1: b446856aaabf44b569c5fb168697b97baafc6fb2 MD5sum: 9fc3310c254316621359200032f71b23 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Python-Version: 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2446 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 441902 SHA256: 024cc31c57fad25b7ece5bf111183562ed9f306c69b9c615ada8252c8ae51f5f SHA1: 34c515cf5d1ec4eda26a1be813c65d420e3f22a0 MD5sum: 282caebc75ef0933a993491196a60143 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-nipy Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3059 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-nibabel, python-nipy-lib (>= 0.3.0+git262-gbb838d7-1~nd13.10+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.3.0+git262-gbb838d7-1~nd13.10+1_all.deb Size: 892602 SHA256: 164d55f79194f7ef5f08e30ce03c1ecfebd14183aefa3a3768b38398a6a70e5b SHA1: a794f99c8543689eecdc5667665d16c8cdd26fbe MD5sum: 2b0a6ab7e1b690cf9981df32e9bdae78 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7903 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.3.0+git262-gbb838d7-1~nd13.10+1_all.deb Size: 1545496 SHA256: f9aa259a8b46915dbb0e2a2d57fc9c6332e2e057f955b513f61cbeb58c3462d8 SHA1: 012a15c3034aa7fa451794ebb1e5129b8cb452e9 MD5sum: adb0d61276ab27f26f1849ac95c98d3c 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-nipype Source: nipype Version: 0.10.0-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4728 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, 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_0.10.0-1~nd13.10+1_all.deb Size: 1390990 SHA256: 2654102906ad09f0c64a687387fd2e4419e32b4f1fc8b27e8418daed18646f3a SHA1: 136d852cad724b2340b570176b52c0948a074a97 MD5sum: 6aa9a0ba6d4f75b7308d693fab8b96c4 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: 0.10.0-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20510 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_0.10.0-1~nd13.10+1_all.deb Size: 10679360 SHA256: aee6a94568595a1ce8483d25dc995f83118e6ac30ed6e41a003437be44f4bafc SHA1: 4aec83953357822f98df0013ebc16699e48ecd61 MD5sum: 5bfc112ef4ec87bbc2eebd04725a48a6 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.5-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9348 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.5-1~nd13.10+1_all.deb Size: 3927934 SHA256: f560f816d3f6fe2849a682edc12979d0bbf786d38285dc0a4b1708bd1ec2e02d SHA1: d8da089190eb3ba3115e444658bc4b1e45cc8431 MD5sum: 8b64db0fbae6ad10c21a3a91626ca4fe Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.5-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7692 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.5-1~nd13.10+1_all.deb Size: 6058328 SHA256: a46819cdf6285281ae4236c15810c387608ee91c2e20ab1c839a34790df77c49 SHA1: b7d5456b0fa7a840f13097986358597a155d31ee MD5sum: ec64853946628ff5f62943aad6712f64 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-openpyxl Source: openpyxl Version: 1.7.0+ds1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 452 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose, python-pil, python-imaging Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.7.0+ds1-1~nd13.10+1_all.deb Size: 91942 SHA256: 45e03738ea43ee24a77af63a0910957f19fed443bdb9fa5f0fbf8d0505002c43 SHA1: bb8bbd20152df002810b7998237cdb1ef04c7a73 MD5sum: 5dc3c2964ab771ebebbd199b4b15c60e Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.14.1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8987 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-dateutil, python-tz, python-numpy (>= 1:1.6~), python-pandas-lib (>= 0.14.1-1~nd13.10+1), python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.14.1-1~nd13.10+1_all.deb Size: 1666436 SHA256: 43385fc04d45e34152f88b59651f69885104f4d758b17027ae8e94ea2a495919 SHA1: 82e4b70898986ac9fa176e42aee709c3245bdce4 MD5sum: 0e094f40123c118a00308f27eba239d6 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-patsy Source: patsy Version: 0.3.0-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 725 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.3.0-3~nd13.10+1_all.deb Size: 215600 SHA256: ff4859f3ee84308c62e1bff3cbf797df70717c1a37b2d0f2ec087aeee4684b3b SHA1: 76933d6a81fb64027e31a15581c62203d890dd4a MD5sum: 41bb3257f29609bd78947aa53ab04c28 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.3.0-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1243 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.3.0-3~nd13.10+1_all.deb Size: 551306 SHA256: 01ec3c662edd665a7085c4004971664b4fb5800a23e2842ebe4a0cc2a2fa77e2 SHA1: 8d5ee5785fcafedbaf30dfb453b7221ac445aefd MD5sum: 73f7ed9bca5fb2011773e072f2c2b4ed Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd13.10+1_all.deb Size: 108524 SHA256: 6863d435af5ce596a0c72b364554a770c973cba83366040ef4fbac75dfe7d10e SHA1: 6682b6167e7dd6e38f64c42424826b3a405f7aed MD5sum: e1e4d04b3eda579ec673bbeb8de8b557 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1_all.deb Size: 818248 SHA256: 9ce8e6041a5deeccea8c28454166623b53d9a571d442a63bc8844c07dd698293 SHA1: 90dc97067b797c017c9da331c41ed24072f8d156 MD5sum: d3ec7da2336f2e9e5ab0cff98c32ebaf Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 175892 SHA256: 0490096bb6a4e6d5ed2ec0e77261346c947d46d28d86acd3bb617c35ad3f10d2 SHA1: 0573a0e1d66e53f5af548774aae5578cc3346cc3 MD5sum: 908111812c3b5221360aff3852de45a8 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~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 862 Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 190426 SHA256: 5854904257cb3119ee3d4389a93ef91f6d0b09cb8761ad8202ad2871c93c79b5 SHA1: ab34bd5639fc33e6891167d65f60d00d368405b5 MD5sum: 3e607b3d81f724a53cce9d8e07b15a74 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-scikits-learn Source: scikit-learn Version: 0.15.2-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.15.2-3~nd13.10+1_all.deb Size: 41458 SHA256: 3d26528c00f8823e9882328fbe4a2fb7729b8e53b678288c14a200c1a7792231 SHA1: dc241399047f70bc16c885f36cbaaa38fa1f0bb8 MD5sum: ad44944d4f5d87f40edbab8aefd43d9c Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scikits.statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, python-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: oldlibs Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 5690 SHA256: 32c363d5c9c614e8dc79f3e4416b5f5f130a1a14bc01a655340725b9debc7732 SHA1: 31cc26d464f24154400ac5af0077098c538e3903 MD5sum: a0418afa93e68377deca41d04268bd03 Description: transitional compatibility package for statsmodels migration Provides old namespace (scikits.statsmodels) and could be removed if dependent code migrated to use statsmodels for clarity of the namespace. Package: python-skimage Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6267 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-skimage-lib (>= 0.9.3-1~nd13.10+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-imaging, python-pil, python-matplotlib (>= 1.0), python-nose, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.9.3-1~nd13.10+1_all.deb Size: 4538212 SHA256: 38ce12bcda96fb048603a041bf97348639c933fe350844078531e0b0b0325e8a SHA1: 1326d280a0d3bd379aeabf6d2fea67d8384b150e MD5sum: ffd316ff9cf30d8cd16d769688403f46 Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 17726 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.9.3-1~nd13.10+1_all.deb Size: 14620090 SHA256: 01aafb0fe1ee85f69bd722c23a4b72f003261bd8511eacfc811590bb5249b116 SHA1: f049087ae92a499a52955ad443bbe99b6e0344af MD5sum: 1f9af2c36987770895b8dc2ca67b25ac Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-sklearn Source: scikit-learn Version: 0.15.2-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4068 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn-lib (>= 0.15.2-3~nd13.10+1), python-joblib (>= 0.4.5) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.15.2-3~nd13.10+1_all.deb Size: 1210366 SHA256: 1169c8c5ab075a2761fae3ab74c6fc66d47c3d345a1b84b5d3a5b5973991d6b2 SHA1: 08e73244104e2f56374fe5a00123666a36126b86 MD5sum: eea5e26b3d0ac584e38be1b5db157192 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.15.2-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 66674 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.15.2-3~nd13.10+1_all.deb Size: 51276970 SHA256: 049c5c9ba4712d146a18591f86b7155cfc2c8a6d95b80f0e2d4e83e9309fd0de SHA1: 39a6ad858985ab429c838361ae89b6003ce6a602 MD5sum: d5920eeac35626adee5ff13c2ba14706 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-smmap Version: 0.8.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.8.3-1~nd13.10+1_all.deb Size: 22282 SHA256: 95a22f4b00c2fbd3ef11939c2d77594b3a6cd0b26a6df2ad76208e56f1fe4a35 SHA1: 5539d1b8d7969300e76895a28000255cc3bce1aa MD5sum: 33948d84f80611e89c929dfd2ce0f3f1 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. Package: python-spyderlib Source: spyder Version: 2.2.5+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4009 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), libjs-sphinxdoc (>= 1.0), libjs-jquery, libjs-mathjax, python-qt4 Recommends: ipython-qtconsole, pep8, pyflakes (>= 0.5.0), pylint, python-matplotlib, python-numpy, python-psutil (>= 0.3.0), python-rope, python-scipy, python-sphinx Suggests: tortoisehg, gitk Breaks: spyder (<< 2.0.12-1) Replaces: spyder (<< 2.0.12-1) Provides: python2.7-spyderlib Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: python Filename: pool/main/s/spyder/python-spyderlib_2.2.5+dfsg-1~nd13.10+1_all.deb Size: 1847912 SHA256: 5901bcb679c7ab73afcc6a5ba4e91c7d8e5f0b26e89da7dfc808ebd2efa321dc SHA1: fd5f1fc3a2f2efdd2910acf381322602cd2ae029 MD5sum: 50f033bac3cde622865ed80cb0137101 Description: python IDE for scientists Originally written to design Spyder (the Scientific PYthon Development EnviRonment), the spyderlib Python library provides ready-to-use pure-Python widgets: source code editor with syntax highlighting and code introspection/analysis features, NumPy array editor, dictionary editor, Python console, etc. It's based on the Qt Python binding module PyQt4 (and is compatible with PySide since v2.2). Package: python-spykeutils Source: spykeutils Version: 0.4.1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2019 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-quantities, python-neo (>= 0.2.1), python-nose, python-sphinx Recommends: python-guidata, python-guiqwt, python-tables, libjs-jquery, libjs-underscore, python-sklearn (>= 0.11), python-joblib (>= 0.4.5) Provides: python2.7-spykeutils Homepage: https://github.com/rproepp/spykeutils Priority: extra Section: python Filename: pool/main/s/spykeutils/python-spykeutils_0.4.1-1~nd13.10+1_all.deb Size: 401734 SHA256: 5045b99793335d19dd18e573d0bd9a99341947e8fdb140789f0d775f66608f82 SHA1: 22b9659a98b9e1b194517e4fafd9d143cbe6a2fb MD5sum: 96eee236b77fbf99499628eb811b1a0e Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20496 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd13.04+1+nd13.10+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 4690538 SHA256: 38a545728cb1df2d44d1fc3579354ddfe8b89c5f207ece0cd3b2b68175730d29 SHA1: 95347b8acb0ef160eea8eb223ef7ec8d4d46f0ed MD5sum: d7b2743076ae1cc2f1aadfa920e3b4ec Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31202 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 9240594 SHA256: afc8c22ea8bad165091cb11c971caaf688a39748726afc7430379266cbd8220a SHA1: d7f880340bf05c73be55fe618e1ce0706681724a MD5sum: 8a8961c09b31992954ac76ce98daf033 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-surfer Source: pysurfer Version: 0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28156 SHA256: 50ddfd6a338724eef65c70fdf5accda6cb4138a4a880812d575a3a24c82e0f4e SHA1: 3dd5e53ea0d12307cf09854ee4857f26557ed6e5 MD5sum: 5e15b6ff76d04fb48b8d45537ef67a97 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: python3-datalad Source: datalad Version: 0.17.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4665 Depends: neurodebian-popularity-contest, git-annex (>= 8.20200309~) | git-annex-standalone (>= 8.20200309~), patool, p7zip-full, python3 (>= 3.7), python3-annexremote, python3-distro, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners (>= 0.14~), python3-gitlab, python3-humanize, python3-importlib-metadata | python3 (>> 3.10), python3-iso8601, python3-keyring, python3-keyrings.alt | python3-keyring (<= 8), python3-mock, python3-msgpack, python3-pil, python3-platformdirs, python3-requests (>= 1.2), python3-secretstorage, python3-simplejson, python3-six, python3-tqdm, python3-chardet, python3-packaging, python3:any Recommends: python3-boto, python3-exif, python3-html5lib, python3-httpretty, python3-jsmin, python3-libxmp, python3-lzma, python3-mutagen, python3-pytest, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, datalad-container, datalad-crawler, datalad-neuroimaging, python3-bs4, python3-numpy Breaks: datalad-container (<< 1.1.2) Homepage: https://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.17.5-1~nd+1_all.deb Size: 958872 SHA256: 1f3e16c16863bab40ba92405109ab26c78f19e3e86e2b38733a035221c4e7744 SHA1: 873da190eb5ee83576ff519c2d564e1f841abe5b MD5sum: 7a97a6f55929cc103dd60d7783a9565e Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python3-jdcal Source: jdcal Version: 1.0-1~nd13.10+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~nd13.10+1_all.deb Size: 7972 SHA256: 83c1cfb2253d0ccc26cc2fed00871290d3636ec967c0c97d4fe6b37fa94cc69e SHA1: a382f4536b4a37752c2faf9df38cfdfafd1c77cc MD5sum: a3bf83e3519613ea31f497d28bc12763 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: 0.8.4-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 251 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.8.4-1~nd13.10+1_all.deb Size: 71436 SHA256: 1f8f5d1563912fc6b367fecaccd92c68a1677281669ede4891e95fad88923073 SHA1: 3d7024a99a7a50532744475e7a482f6c5176cb7f MD5sum: f715096f6b0b18e8d20906a8c3904581 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 3 version. Package: python3-mdp Source: mdp Version: 3.3+git19-g4ec2f29-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1482 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.3+git19-g4ec2f29-1~nd13.10+1_all.deb Size: 489828 SHA256: 48719aa4ed429c2270bfc1404648b2bc52c7c5f6fde945a6339926f5374adfbe SHA1: 24b78fa8168b6a16f842788bc0e08ee5e57f7ced MD5sum: ac2082426fde7dc6e182007a1de2a66e 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-pandas Source: pandas Version: 0.14.1-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8903 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.6~), python3:any (>= 3.3.2-2~), python3-tz, python3-pandas-lib (>= 0.14.1-1~nd13.10+1) Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-six Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.14.1-1~nd13.10+1_all.deb Size: 1658564 SHA256: 5604f528884f1187979768c41c1134ee2494b0d74de267b7f1905dc2cb7698df SHA1: 49b9fa4900ef729d02c47cd2ff13791a95d40dde MD5sum: d546d6900bb4ba44d7227ba7288e8a6d 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-patsy Source: patsy Version: 0.3.0-3~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 717 Depends: neurodebian-popularity-contest, python3-numpy, 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_0.3.0-3~nd13.10+1_all.deb Size: 213588 SHA256: e8797a21547805c016219ac6b3cf0892907f194d8ef8f2ade86afe982e9c1ed0 SHA1: 6584862989dfdc0e4f0010a91e2be1d5f078dd52 MD5sum: 253395ebf543e7cd656b9f350c91bdca Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-skimage Source: skimage Version: 0.9.3-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6161 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-skimage-lib (>= 0.9.3-1~nd13.10+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-pil, python3-matplotlib (>= 1.0), python3-nose Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.9.3-1~nd13.10+1_all.deb Size: 4529352 SHA256: 1954d095c5dda861a9a16d40bc290dd87d9c62b5a3ebffed61bca0b3940dc3be SHA1: fec0293ba0f1d43be9dc26b2a221cc88fddb4397 MD5sum: ecd693c691939be0476ffd23dda19fa6 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: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 10744052 SHA256: 05f7ef0de3af1f49c7f7dafba91b9d8f5f082bd48ad7acd365a89a105fcd6c71 SHA1: 829ef9f220b3a9595b3acdb7ada1bedcdfdbc378 MD5sum: 137a219ff42452e9439fe275cb949cc3 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 52166702 SHA256: 85b2c5e9081fd7cf506defb5327413d0222f01f3b7e6fd959e5e2ccf8d83000c SHA1: 8a53b81d37062647c56fac6117a589fb776bbac5 MD5sum: 9d6cae39f3455ec2cc5a2f3ccf8b002d Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 8990912 SHA256: a35cf1eaaf17c77bc2c148da711ed2d386131f25f4ea98c326b36ee3a0867e07 SHA1: a21337c1d47d0ae2b39bcabb477ecbdf0fdff4f0 MD5sum: e7247d37c03ce8eafa3ae5e619c752a2 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: spyder Version: 2.2.5+dfsg-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python:any, python-spyderlib (= 2.2.5+dfsg-1~nd13.10+1) Homepage: http://code.google.com/p/spyderlib/ Priority: extra Section: devel Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd13.10+1_all.deb Size: 36094 SHA256: 9b421cf2dd4baf6337fee59f8d4de941497d7c115ba7a078fbf22c0adda8a839 SHA1: e2fd2c04cce115e7fa8cdbb9005c75039af9f1fa MD5sum: 140f3abee79c6f9f3d6469c93b721c9a Description: python IDE for scientists Spyder (previously known as Pydee) is a free open-source Python development environment providing MATLAB-like features in a simple and light-weighted software Package: spykeviewer Version: 0.4.2-1~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1128 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.2-1~nd13.10+1_all.deb Size: 577514 SHA256: 20515a233f5c7060704fe5b8d6b54a8576a51748161d95c756ad872508c1681d SHA1: 0c29b2de9a4c53b16db004a289b4deae6dc70726 MD5sum: 25b502d35adabf84dbb50a7f1931e473 Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28850 SHA256: 2885d99daf2891a6f2fe488f25d5f54002ff6d6df0252f5e946ceff1f20e452b SHA1: a9e67198cec5f15cc2bc910b9a9fdbb90f7f40ac MD5sum: 505b20b36e42d72d4d7ca1bc051d90b5 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 99698 SHA256: 40b0868fbb47a9758a535769ae6eaac9e3ec55f0c3b39557f43303f5fe8dd0b3 SHA1: 3ca2b3698fcbc13058665807cb8ffc9ad4fd25d9 MD5sum: a6c94efec638cee547260e58486ee71a Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: youtube-dl Version: 2021.12.17-1~nd110+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5937 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3:any Recommends: aria2 | wget | curl, ca-certificates, ffmpeg, mpv | mplayer, python3-pyxattr, rtmpdump, python3-pycryptodome Suggests: libfribidi-bin | bidiv, phantomjs Homepage: https://ytdl-org.github.io/youtube-dl/ Priority: optional Section: web Filename: pool/main/y/youtube-dl/youtube-dl_2021.12.17-1~nd110+1_all.deb Size: 1128692 SHA256: 75859d2f34a475fc0f199cd6d2b73e18c29cda44406530964890dcb790008eca SHA1: 09f85f2abc32eb5e9c2ccd6bfd1354ea332b6489 MD5sum: 6d04814be91bd9f85a7d3793ff2a2fb3 Description: downloader of videos from YouTube and other sites youtube-dl is a small command-line program to download videos from YouTube.com and other sites that don't provide direct links to the videos served. . youtube-dl allows the user, among other things, to choose a specific video quality to download (if available) or let the program automatically determine the best (or worst) quality video to grab. It supports downloading entire playlists and all videos from a given user. . Currently supported sites (or features of sites) are: . 1tv, 20min, 220.ro, 23video, 24video, 3qsdn, 3sat, 4tube, 56.com, 5min, 6play, 7plus, 8tracks, 91porn, 9c9media, 9gag, 9now.com.au, abc.net.au, abc.net.au:iview, abcnews, abcnews:video, abcotvs, abcotvs:clips, AcademicEarth:Course, acast, acast:channel, ADN, AdobeConnect, adobetv, adobetv:channel, adobetv:embed, adobetv:show, adobetv:video, AdultSwim, aenetworks, aenetworks:collection, aenetworks:show, afreecatv, AirMozilla, AliExpressLive, AlJazeera, Allocine, AlphaPorno, Amara, AMCNetworks, AmericasTestKitchen, AmericasTestKitchenSeason, anderetijden, AnimeOnDemand, Anvato, aol.com, APA, Aparat, AppleConnect, AppleDaily, ApplePodcasts, appletrailers, appletrailers:section, archive.org, ArcPublishing, ARD, ARD:mediathek, ARDBetaMediathek, Arkena, arte.sky.it, ArteTV, ArteTVEmbed, ArteTVPlaylist, AsianCrush, AsianCrushPlaylist, AtresPlayer, ATTTechChannel, ATVAt, AudiMedia, AudioBoom, audiomack, audiomack:album, AWAAN, awaan:live, awaan:season, awaan:video, AZMedien, BaiduVideo, Bandcamp, Bandcamp:album, Bandcamp:weekly, bangumi.bilibili.com, bbc, bbc.co.uk, bbc.co.uk:article, bbc.co.uk:iplayer:playlist, bbc.co.uk:playlist, BBVTV, Beatport, Beeg, BehindKink, Bellator, BellMedia, Bet, bfi:player, bfmtv, bfmtv:article, bfmtv:live, BibelTV, Bigflix, Bild, BiliBili, BilibiliAudio, BilibiliAudioAlbum, BiliBiliPlayer, BioBioChileTV, Biography, BIQLE, BitChute, BitChuteChannel, BleacherReport, BleacherReportCMS, blinkx, Bloomberg, BokeCC, BongaCams, BostonGlobe, Box, Bpb, BR, BravoTV, Break, brightcove:legacy, brightcove:new, BRMediathek, bt:article, bt:vestlendingen, BusinessInsider, BuzzFeed, BYUtv, Camdemy, CamdemyFolder, CamModels, CamTube, CamWithHer, canalc2.tv, Canalplus, Canvas, CanvasEen, CarambaTV, CarambaTVPage, CartoonNetwork, cbc.ca, cbc.ca:olympics, cbc.ca:player, cbc.ca:watch, cbc.ca:watch:video, CBS, CBSInteractive, CBSLocal, CBSLocalArticle, cbsnews, cbsnews:embed, cbsnews:livevideo, CBSSports, CCMA, CCTV, CDA, CeskaTelevize, CeskaTelevizePorady, channel9, CharlieRose, Chaturbate, Chilloutzone, chirbit, chirbit:profile, cielotv.it, Cinchcast, Cinemax, CiscoLiveSearch, CiscoLiveSession, CJSW, cliphunter, Clippit, ClipRs, Clipsyndicate, CloserToTruth, CloudflareStream, Cloudy, Clubic, Clyp, cmt.com, CNBC, CNBCVideo, CNN, CNNArticle, CNNBlogs, ComedyCentral, ComedyCentralTV, CommonMistakes, CondeNast, CONtv, Corus, Coub, Cracked, Crackle, CrooksAndLiars, crunchyroll, crunchyroll:playlist, CSpan, CtsNews, CTV, CTVNews, cu.ntv.co.jp, Culturebox, CultureUnplugged, curiositystream, curiositystream:collection, CWTV, DailyMail, dailymotion, dailymotion:playlist, dailymotion:user, daum.net, daum.net:clip, daum.net:playlist, daum.net:user, DBTV, DctpTv, DeezerPlaylist, defense.gouv.fr, democracynow, DHM, Digg, DigitallySpeaking, Digiteka, Discovery, DiscoveryGo, DiscoveryGoPlaylist, DiscoveryNetworksDe, DiscoveryVR, Disney, dlive:stream, dlive:vod, Dotsub, DouyuShow, DouyuTV, DPlay, DRBonanza, Dropbox, DrTuber, drtv, drtv:live, DTube, Dumpert, dvtv, dw, dw:article, EaglePlatform, EbaumsWorld, EchoMsk, egghead:course, egghead:lesson, ehftv, eHow, EinsUndEinsTV, Einthusan, eitb.tv, EllenTube, EllenTubePlaylist, EllenTubeVideo, ElPais, Embedly, EMPFlix, Engadget, Eporner, EroProfile, Escapist, ESPN, ESPNArticle, EsriVideo, Europa, EWETV, ExpoTV, Expressen, ExtremeTube, EyedoTV, facebook, FacebookPluginsVideo, faz.net, fc2, fc2:embed, Fczenit, filmon, filmon:channel, Filmweb, FiveThirtyEight, FiveTV, Flickr, Folketinget, FootyRoom, Formula1, FOX, FOX9, FOX9News, Foxgay, foxnews, foxnews:article, FoxSports, france2.fr:generation-what, FranceCulture, FranceInter, FranceTV, FranceTVEmbed, francetvinfo.fr, FranceTVJeunesse, FranceTVSite, Freesound, freespeech.org, FreshLive, FrontendMasters, FrontendMastersCourse, FrontendMastersLesson, FujiTVFODPlus7, Funimation, Funk, Fusion, Fux, Gaia, GameInformer, GameSpot, GameStar, Gaskrank, Gazeta, GDCVault, generic, Gfycat, GiantBomb, Giga, GlattvisionTV, Glide, Globo, GloboArticle, Go, GodTube, Golem, google:podcasts, google:podcasts:feed, GoogleDrive, Goshgay, GPUTechConf, Groupon, hbo, HearThisAt, Heise, HellPorno, Helsinki, HentaiStigma, hetklokhuis, hgtv.com:show, HiDive, HistoricFilms, history:player, history:topic, hitbox, hitbox:live, HitRecord, hketv, HornBunny, HotNewHipHop, hotstar, hotstar:playlist, Howcast, HowStuffWorks, HRTi, HRTiPlaylist, Huajiao, HuffPost, Hungama, HungamaSong, Hypem, ign.com, IGNArticle, IGNVideo, IHeartRadio, iheartradio:podcast, imdb, imdb:list, Imgur, imgur:album, imgur:gallery, Ina, Inc, IndavideoEmbed, InfoQ, Instagram, instagram:tag, instagram:user, Internazionale, InternetVideoArchive, IPrima, iqiyi, Ir90Tv, ITTF, ITV, ITVBTCC, ivi, ivi:compilation, ivideon, Iwara, Izlesene, Jamendo, JamendoAlbum, JeuxVideo, Joj, Jove, JWPlatform, Kakao, Kaltura, Kankan, Karaoketv, KarriereVideos, Katsomo, KeezMovies, Ketnet, khanacademy, khanacademy:unit, KickStarter, KinjaEmbed, KinoPoisk, KonserthusetPlay, KrasView, Ku6, KUSI, kuwo:album, kuwo:category, kuwo:chart, kuwo:mv, kuwo:singer, kuwo:song, la7.it, laola1tv, laola1tv:embed, lbry, lbry:channel, LCI, Lcp, LcpPlay, Le, Lecture2Go, Lecturio, LecturioCourse, LecturioDeCourse, LEGO, Lemonde, Lenta, LePlaylist, LetvCloud, Libsyn, life, life:embed, limelight, limelight:channel, limelight:channel_list, LineTV, linkedin:learning, linkedin:learning:course, LinuxAcademy, LiTV, LiveJournal, LiveLeak, LiveLeakEmbed, livestream, livestream:original, livestream:shortener, LnkGo, loc, LocalNews8, LoveHomePorn, lrt.lt, lynda, lynda:course, m6, mailru, mailru:music, mailru:music:search, MallTV, mangomolo:live, mangomolo:video, ManyVids, Markiza, MarkizaPage, massengeschmack.tv, MatchTV, MDR, MedalTV, media.ccc.de, media.ccc.de:lists, Medialaan, Mediaset, Mediasite, MediasiteCatalog, MediasiteNamedCatalog, Medici, megaphone.fm, Meipai, MelonVOD, META, metacafe, Metacritic, mewatch, Mgoon, MGTV, MiaoPai, minds, minds:channel, minds:group, MinistryGrid, Minoto, miomio.tv, MiTele, mixcloud, mixcloud:playlist, mixcloud:user, MLB, Mms, Mnet, MNetTV, MoeVideo, Mofosex, MofosexEmbed, Mojvideo, Morningstar, Motherless, MotherlessGroup, Motorsport, MovieClips, MovieFap, Moviezine, MovingImage, MSN, mtg, mtv, mtv.de, mtv:video, mtvjapan, mtvservices:embedded, MTVUutisetArticle, MuenchenTV, mva, mva:course, Mwave, MwaveMeetGreet, MyChannels, MySpace, MySpace:album, MySpass, Myvi, MyVidster, MyviEmbed, MyVisionTV, n-tv.de, natgeo:video, NationalGeographicTV, Naver, NBA, nba:watch, nba:watch:collection, NBAChannel, NBAEmbed, NBAWatchEmbed, NBC, NBCNews, nbcolympics, nbcolympics:stream, NBCSports, NBCSportsStream, NBCSportsVPlayer, ndr, ndr:embed, ndr:embed:base, NDTV, NerdCubedFeed, netease:album, netease:djradio, netease:mv, netease:playlist, netease:program, netease:singer, netease:song, NetPlus, Netzkino, Newgrounds, NewgroundsPlaylist, Newstube, NextMedia, NextMediaActionNews, NextTV, Nexx, NexxEmbed, nfl.com (CURRENTLY BROKEN), nfl.com:article (CURRENTLY BROKEN), NhkVod, NhkVodProgram, nhl.com, nick.com, nick.de, nickelodeon:br, nickelodeonru, nicknight, niconico, NiconicoPlaylist, Nintendo, njoy, njoy:embed, NJPWWorld, NobelPrize, NonkTube, Noovo, Normalboots, NosVideo, Nova, NovaEmbed, nowness, nowness:playlist, nowness:series, Noz, npo, npo.nl:live, npo.nl:radio, npo.nl:radio:fragment, Npr, NRK, NRKPlaylist, NRKRadioPodkast, NRKSkole, NRKTV, NRKTVDirekte, NRKTVEpisode, NRKTVEpisodes, NRKTVSeason, NRKTVSeries, NRLTV, ntv.ru, Nuvid, NYTimes, NYTimesArticle, NYTimesCooking, NZZ, ocw.mit.edu, OdaTV, Odnoklassniki, OktoberfestTV, OnDemandKorea, onet.pl, onet.tv, onet.tv:channel, OnetMVP, OnionStudios, Ooyala, OoyalaExternal, OraTV, orf:burgenland, orf:fm4, orf:fm4:story, orf:iptv, orf:kaernten, orf:noe, orf:oberoesterreich, orf:oe1, orf:oe3, orf:salzburg, orf:steiermark, orf:tirol, orf:tvthek, orf:vorarlberg, orf:wien, OsnatelTV, OutsideTV, PacktPub, PacktPubCourse, pandora.tv, ParamountNetwork, parliamentlive.tv, Patreon, pbs, PearVideo, PeerTube, People, PerformGroup, periscope, periscope:user, PhilharmonieDeParis, phoenix.de, Photobucket, Picarto, PicartoVod, Piksel, Pinkbike, Pinterest, PinterestCollection, Pladform, Platzi, PlatziCourse, play.fm, player.sky.it, PlayPlusTV, PlaysTV, Playtvak, Playvid, Playwire, pluralsight, pluralsight:course, podomatic, Pokemon, PolskieRadio, PolskieRadioCategory, Popcorntimes, PopcornTV, PornCom, PornerBros, PornHd, PornHub, PornHubPagedVideoList, PornHubUser, PornHubUserVideosUpload, Pornotube, PornoVoisines, PornoXO, PornTube, PressTV, prosiebensat1, puhutv, puhutv:serie, Puls4, Pyvideo, qqmusic, qqmusic:album, qqmusic:playlist, qqmusic:singer, qqmusic:toplist, QuantumTV, Qub, Quickline, QuicklineLive, R7, R7Article, radio.de, radiobremen, radiocanada, radiocanada:audiovideo, radiofrance, RadioJavan, Rai, RaiPlay, RaiPlayLive, RaiPlayPlaylist, RayWenderlich, RayWenderlichCourse, RBMARadio, RDS, RedBull, RedBullEmbed, RedBullTV, RedBullTVRrnContent, Reddit, RedditR, RedTube, RegioTV, RENTV, RENTVArticle, Restudy, Reuters, ReverbNation, RICE, RMCDecouverte, RockstarGames, RoosterTeeth, RottenTomatoes, Roxwel, Rozhlas, RTBF, rte, rte:radio, rtl.nl, rtl2, rtl2:you, rtl2:you:series, Rtmp, RTP, RTS, rtve.es:alacarta, rtve.es:infantil, rtve.es:live, rtve.es:television, RTVNH, RTVS, RUHD, RumbleEmbed, rutube, rutube:channel, rutube:embed, rutube:movie, rutube:person, rutube:playlist, RUTV, Ruutu, Ruv, safari, safari:api, safari:course, SAKTV, SaltTV, Sapo, savefrom.net, SBS, schooltv, screen.yahoo:search, Screencast, ScreencastOMatic, ScrippsNetworks, scrippsnetworks:watch, SCTE, SCTECourse, Seeker, SenateISVP, SendtoNews, Servus, Sexu, SeznamZpravy, SeznamZpravyArticle, Shahid, ShahidShow, Shared, ShowRoomLive, Sina, sky.it, sky:news, sky:sports, sky:sports:news, skyacademy.it, SkylineWebcams, skynewsarabia:article, skynewsarabia:video, Slideshare, SlidesLive, Slutload, Snotr, Sohu, SonyLIV, soundcloud, soundcloud:playlist, soundcloud:search, soundcloud:set, soundcloud:trackstation, soundcloud:user, SoundcloudEmbed, soundgasm, soundgasm:profile, southpark.cc.com, southpark.cc.com:español, southpark.de, southpark.nl, southparkstudios.dk, SpankBang, SpankBangPlaylist, Spankwire, Spiegel, sport.francetvinfo.fr, Sport5, SportBox, SportDeutschland, spotify, spotify:show, Spreaker, SpreakerPage, SpreakerShow, SpreakerShowPage, SpringboardPlatform, Sprout, sr:mediathek, SRGSSR, SRGSSRPlay, stanfordoc, Steam, Stitcher, StitcherShow, Streamable, streamcloud.eu, StreamCZ, StreetVoice, StretchInternet, stv:player, SunPorno, sverigesradio:episode, sverigesradio:publication, SVT, SVTPage, SVTPlay, SVTSeries, SWRMediathek, Syfy, SztvHu, t-online.de, Tagesschau, tagesschau:player, Tass, TBS, TDSLifeway, Teachable, TeachableCourse, teachertube, teachertube:user:collection, TeachingChannel, Teamcoco, TeamTreeHouse, TechTalks, techtv.mit.edu, ted, Tele13, Tele5, TeleBruxelles, Telecinco, Telegraaf, TeleMB, TeleQuebec, TeleQuebecEmission, TeleQuebecLive, TeleQuebecSquat, TeleQuebecVideo, TeleTask, Telewebion, TennisTV, TenPlay, TestURL, TF1, TFO, TheIntercept, ThePlatform, ThePlatformFeed, TheScene, TheStar, TheSun, TheWeatherChannel, ThisAmericanLife, ThisAV, ThisOldHouse, TikTok, TikTokUser (CURRENTLY BROKEN), tinypic, TMZ, TMZArticle, TNAFlix, TNAFlixNetworkEmbed, toggle, ToonGoggles, tou.tv, Toypics, ToypicsUser, TrailerAddict (CURRENTLY BROKEN), Trilulilu, Trovo, TrovoVod, TruNews, TruTV, Tube8, TubiTv, Tumblr, tunein:clip, tunein:program, tunein:shortener, tunein:station, tunein:topic, TunePk, Turbo, tv.dfb.de, TV2, tv2.hu, TV2Article, TV2DK, TV2DKBornholmPlay, TV4, TV5MondePlus, tv5unis, tv5unis:video, tv8.it, TVA, TVANouvelles, TVANouvellesArticle, TVC, TVCArticle, TVer, tvigle, tvland.com, TVN24, TVNet, TVNoe, TVNow, TVNowAnnual, TVNowNew, TVNowSeason, TVNowShow, tvp, tvp:embed, tvp:series, TVPlayer, TVPlayHome, Tweakers, TwitCasting, twitch:clips, twitch:stream, twitch:vod, TwitchCollection, TwitchVideos, TwitchVideosClips, TwitchVideosCollections, twitter, twitter:amplify, twitter:broadcast, twitter:card, udemy, udemy:course, UDNEmbed, UFCArabia, UFCTV, UKTVPlay, umg:de, UnicodeBOM, Unistra, Unity, uol.com.br, uplynk, uplynk:preplay, Urort, URPlay, USANetwork, USAToday, ustream, ustream:channel, ustudio, ustudio:embed, Varzesh3, Vbox7, VeeHD, Veoh, Vesti, Vevo, VevoPlaylist, VGTV, vh1.com, vhx:embed, Viafree, vice, vice:article, vice:show, Vidbit, Viddler, Videa, video.google:search, video.sky.it, video.sky.it:live, VideoDetective, videofy.me, videomore, videomore:season, videomore:video, VideoPress, Vidio, VidLii, vidme, vidme:user, vidme:user:likes, vier, vier:videos, viewlift, viewlift:embed, Viidea, viki, viki:channel, vimeo, vimeo:album, vimeo:channel, vimeo:group, vimeo:likes, vimeo:ondemand, vimeo:review, vimeo:user, vimeo:watchlater, Vimple, Vine, vine:user, Viqeo, Viu, viu:ott, viu:playlist, Vivo, vk, vk:uservideos, vk:wallpost, vlive, vlive:channel, vlive:post, Vodlocker, VODPl, VODPlatform, VoiceRepublic, Voot, VoxMedia, VoxMediaVolume, vpro, Vrak, VRT, VrtNU, vrv, vrv:series, VShare, VTM, VTXTV, vube, VuClip, VVVVID, VVVVIDShow, VyboryMos, Vzaar, Wakanim, Walla, WalyTV, washingtonpost, washingtonpost:article, wat.tv, WatchBox, WatchIndianPorn, WDR, wdr:mobile, WDRElefant, WDRPage, Webcaster, WebcasterFeed, WebOfStories, WebOfStoriesPlaylist, Weibo, WeiboMobile, WeiqiTV, Wistia, WistiaPlaylist, wnl, WorldStarHipHop, WSJ, WSJArticle, WWE, XBef, XboxClips, XFileShare, XHamster, XHamsterEmbed, XHamsterUser, xiami:album, xiami:artist, xiami:collection, xiami:song, ximalaya, ximalaya:album, XMinus, XNXX, Xstream, XTube, XTubeUser, Xuite, XVideos, XXXYMovies, Yahoo, yahoo:gyao, yahoo:gyao:player, yahoo:japannews, YandexDisk, yandexmusic:album, yandexmusic:artist:albums, yandexmusic:artist:tracks, yandexmusic:playlist, yandexmusic:track, YandexVideo, YapFiles, YesJapan, yinyuetai:video, Ynet, YouJizz, youku, youku:show, YouNowChannel, YouNowLive, YouNowMoment, YouPorn, YourPorn, YourUpload, youtube, youtube:favorites, youtube:history, youtube:playlist, youtube:recommended, youtube:search, youtube:search:date, youtube:subscriptions, youtube:tab, youtube:truncated_id, youtube:truncated_url, youtube:watchlater, YoutubeYtBe, YoutubeYtUser, Zapiks, Zattoo, ZattooLive, ZDF, ZDFChannel, zingmp3, Zype