Package: bats Version: 0.4.0-1~nd14.04+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~nd14.04+1_all.deb Size: 14380 SHA256: fddb023e52a6515b50557af46c086354d4096c16874c9cd9f375586299d472de SHA1: 618cbfadea7eb8069c32c0b3075a3033adb283be MD5sum: f13ced8df8376670cb14d9be8d8e7798 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: btrbk Version: 0.23.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 298 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv Homepage: http://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.23.3-1~nd14.04+1_all.deb Size: 70930 SHA256: 662015bd6f661f9ce322a9d3f0041e2b2db1b65143922e0257bd8534072d483f SHA1: 3246ead5de154cddffe5f172dd59c0c3549282d8 MD5sum: f09f96a39f8fa4b6f4a3bb25ef4772e7 Description: backup tool for btrfs subvolumes Backup tool for btrfs subvolumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations, with ssh and flexible retention policy support (hourly, daily, weekly, monthly). Package: condor Version: 8.4.9~dfsg.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.9~dfsg.1-2~nd14.04+1_all.deb Size: 16232 SHA256: be1ffeca09b03c726fe522d42b64f551908ecacb2355090d6770b6336beca770 SHA1: 9e1fb6e42cd2f0667371083111fc5106c96c5e23 MD5sum: 20afa2f26b41f144bf842cdc4469170f Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.9~dfsg.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.9~dfsg.1-2~nd14.04+1_all.deb Size: 16246 SHA256: f4f9298f7f793bd2c2a3778709726de61e2bb23ef9c42f050805dd6b1e92d3a8 SHA1: 35d92db070ae5c0e3419946e3efb5fecc9b02734 MD5sum: 421bb498334f405da6bb70a69216486d Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.9~dfsg.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.9~dfsg.1-2~nd14.04+1_all.deb Size: 16248 SHA256: 2a44c6e28b6c702148bc82a8dff5a70f889aebe5d2b63e90ea18a9b91bbf850f SHA1: 973fa7373f4f46af83480922241e93631255b215 MD5sum: 9e172056d3e777b8a29868e17838df56 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 47 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.9~dfsg.1-2~nd14.04+1_all.deb Size: 16244 SHA256: 3e2c2ad1b46ddeeb2eb5080a3da40c2bcca74f0450cdd919c2aa1293b06d3b85 SHA1: b73c034d70a5a6a7505b7db5b8302717873e717a MD5sum: cedad3d27bd40dfbb72bfa597d555a5f Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: datalad Version: 0.4.1-1~nd14.04+1.1~nd1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.4.1-1~nd14.04+1.1~nd1), python Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.4.1-1~nd14.04+1.1~nd1_all.deb Size: 48240 SHA256: 9c7e473f8e6afa3a25d9ce908281d889419eb140d228b4dafb0550c2e4cfe844 SHA1: f9636accd8f577e92e69ab0a6a1932650092fbfe MD5sum: 0816aa13bd40352f07beea8ebe49364b Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package provides the command line tool. Install without Recommends if you need only core functionality. Package: dh-systemd Source: init-system-helpers Version: 1.18~nd13.10+1+nd14.04+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+nd14.04+1_all.deb Size: 13814 SHA256: d174181f267afbaf3c6c7d6108b65eca78861aa6d3c71288a03db9b5cafd5a13 SHA1: 15700758d679f3bda80f55b5f435edad45d1b39e MD5sum: 4ed20ea08d8c497a1a3e9b7ce46fe4c8 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+nd14.04+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+nd14.04+1_all.deb Size: 7062228 SHA256: aa1e0c88dbb25feff7d4a79637ce14e2bd7fccf5b2e73f675ba5b88baebdcb3b SHA1: e5d9d261fdfa5d96e1fe0b8e6ce4b67948bb54c4 MD5sum: 0bf506b1eed312f76a0e48cb663cb40a 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: 0.9.6-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1243 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python, lsb-base (>= 2.0-7) Recommends: iptables, whois, python-pyinotify Suggests: mailx, system-log-daemon, monit, python-systemd Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.6-1~nd14.04+1_all.deb Size: 260178 SHA256: d3fcb6a0d04590e6e5496831b1e413bc493fad5f6f9bb493db5544d4370bfb71 SHA1: 2969db65f660b6bdb77594eaa7aed3a3f20025ee MD5sum: 613376295754d89b73b91f10eea37f36 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: freeipmi Version: 1.4.9-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd14.04+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd14.04+1_all.deb Size: 1172 SHA256: ddbc7d7bbb61097f230807cfc6c0a77d391bf1d4a6e31410718041006b827f32 SHA1: d2a247bce06f052b9d54033f81738a20cb1b9077 MD5sum: 2951d4e9077337872d5db574dfbd131f 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: 1.4.9-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest Suggests: freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-common_1.4.9-1~nd14.04+1_all.deb Size: 189106 SHA256: 705f1b5454ee66c6fb40ef496ffe68656c0b7524dd0e51b1ce2b3dc2a8e7762e SHA1: af7f15103d39b2d03ef557295a8d218997ef76a2 MD5sum: 223c7b78bf96ba503d34c6129041813f 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: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 108 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-nibabel, python, python-numpy, python:any (<< 2.8), python-pkg-resources, python-scipy, python-matplotlib, python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd14.04+1_all.deb Size: 13908 SHA256: bd401b3672c86e560a1927b583637a89617ab68c7e7785458566f6aac708be7b SHA1: 3b05c5b556d57b3764ca8a2c8d52363aeacb801f MD5sum: b8a48a2a910611bd834f22e8f1974fac Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: fslview-doc Source: fslview Version: 4.0.1-7~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 2898 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-7~nd14.04+1_all.deb Size: 2228538 SHA256: 090d2faad68a2d0bd98956f35958dc9aeb5163f534d3ba4368817f656c06d70f SHA1: cbc2784174659eb5743bb2c7c8f5ab1d658004d7 MD5sum: 5d36ffd8a0146a965379b234953844e1 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gcalcli Version: 3.4.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1798 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.4.0-1~nd14.04+1_all.deb Size: 1669814 SHA256: 8908947e8d70ee44b3961f3ef713fac676bd6b9e94e7e683b248a3ab0db3c6c9 SHA1: a955905e13081a7f41157eba57cc18fdcd7cbb97 MD5sum: d9072a4830629412c98ca829b5ceb6de Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: git-hub Version: 0.10.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 146 Depends: neurodebian-popularity-contest, python, git (>= 1:1.7.7) Homepage: https://github.com/sociomantic/git-hub Priority: optional Section: vcs Filename: pool/main/g/git-hub/git-hub_0.10.3-1~nd14.04+1_all.deb Size: 34116 SHA256: fd62ddb5bc2170bcdeb09a46e83d460b31eb0c18857d40289920e13ba483841d SHA1: 3aca884ba690f7737e0f4ff99360f9cb11fce742 MD5sum: 0abb6221dccd24afd74fb16d9ec55ab5 Description: Git command line interface to GitHub git hub is a simple command line interface to GitHub, enabling most useful GitHub tasks (like creating and listing pull request or issues) to be accessed directly through the Git command line. . Although probably the most outstanding feature (and the one that motivated the creation of this tool) is the pull rebase command, which is the rebasing version of the GitHub Merge (TM) button. This enables an easy workflow that doesn't involve thousands of merges which makes the repository history unreadable. . Another unique feature is the ability to transform an issue into a pull request by attaching commits to it (this is something offered by the GitHub API but not by the web interface). Package: gmsl Version: 1.1.5-1~nd14.04+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~nd14.04+1_all.deb Size: 13800 SHA256: 4127230a0b3a6b132f2e98087b496cddbabf8efd64fb0573ac384d4ec292ddab SHA1: 16ab5cc30564be2024ea5ea282213fc38a320743 MD5sum: 75f0db3af8b2efad55c4794e50b84412 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: heudiconv Version: 0.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 79 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd14.04+1_all.deb Size: 10218 SHA256: 43684321833fd0cc620b87b9edf3e20f1071e00fbfb1c9d9115a5938f4df236e SHA1: a5a75c8ce1c59b56fc4a82892e034ef636ee2532 MD5sum: 3155ae84167a24442e1810d0d49f75dd Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: htcondor-doc Source: condor Version: 8.4.9~dfsg.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5973 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.9~dfsg.1-2~nd14.04+1_all.deb Size: 1076304 SHA256: f85f042dcbabcf13014e12a278876405bb13f058efa51ab464d03020c4a3e64f SHA1: 66c7209f5d784fe15dc18649016fef1e26ab871c MD5sum: e0c0a2114ca31191795ec1fd754de40b Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.11.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 466 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil | python-imaging, poppler-utils | mupdf-tools | xpdf-utils (>= 3.02-2) Recommends: mplayer, pdftk, perl, xdg-utils Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.11.1-1~nd14.04+1_all.deb Size: 175686 SHA256: 93a2cfe442cded96df94ade891d2c9892a0b09d43b4fd86073a479f8ca4ba0b8 SHA1: 18a29af861ececa34319234d1929b3aeb2ff77b4 MD5sum: 34273046bb09d48c5331dd6c982e85f3 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+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+nd14.04+1_all.deb Size: 9150 SHA256: 6221480f9dac530be0388cb543cb7222a71f2eeb5a05e3b7684189951be779a9 SHA1: d6e2bc39ee2ea2858d5aa50a8b825dcc1a9766ef MD5sum: 42c1f57576c0b1537c531816653e0f04 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+nd14.04+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+nd14.04+1_all.deb Size: 13450 SHA256: 9b738273e06fa645d7746ddcfc18257e82b1aa81991b60f4940c8336ca7c276b SHA1: a69ef0da8cacfe37a1898934c6feb74737e63597 MD5sum: c519d25c91c535528c645290c7201987 Description: helper tools for all init systems This package contains helper tools that are necessary for switching between the various init systems that Debian contains (e.g. sysvinit, upstart, systemd). An example is deb-systemd-helper, a script that enables systemd unit files without depending on a running systemd. . While this package is maintained by pkg-systemd-maintainers, it is NOT specific to systemd at all. Maintainers of other init systems are welcome to include their helpers in this package. Package: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.7.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2836 Depends: neurodebian-popularity-contest Suggests: libinsighttoolkit4-dev Conflicts: insighttoolkit-examples Replaces: insighttoolkit-examples Homepage: http://www.itk.org/ Priority: optional Section: devel Filename: pool/main/i/insighttoolkit4/insighttoolkit4-examples_4.7.0-1~nd14.04+1_all.deb Size: 2498446 SHA256: ce5b7ee80d764522163321fea16c74d1159642fcb4a74a28f5c51fc9438552ab SHA1: a8a9342033fbc34ed40d182ecfbe1991bc1c9c31 MD5sum: 0abb2152be3c1e64724f0cabcb7be373 Description: Image processing toolkit for registration and segmentation - examples ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the source for example programs. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd14.04+1_all.deb Size: 5018 SHA256: 30af8e92d10d414bf87e8c4699a93b2a65aede0538a750d23b741b6c31b1d0f9 SHA1: 026b10c125ea9fb70fd9f19f71d809cf33d4c274 MD5sum: 5fc45130f6fa18505f9de5ab7ee5b221 Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 677 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.3-1~nd14.04+1_all.deb Size: 92014 SHA256: 064146257b1c0cf6dfa96e77798278903cfa4733476bfd174ba941afb1b8c52d SHA1: 024619574042575fc101f79d8b57e876a7b4fb65 MD5sum: e429a46c5c5ecd339ff069594169ba2c 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: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2003 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd14.04+1_all.deb Size: 148632 SHA256: da7fb8cdacb033da65e02cb52138088d8feb3a83d26e0ebd9525d7c554661c1f SHA1: d996863712189c004d651b50fa974c1f852401a1 MD5sum: b4dac15a86155424c1c2cbcf61d975f2 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14003 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+nd14.04+1_all.deb Size: 828262 SHA256: b80877b4eb7ac26a8d128219be2df273b0d1115bdc039118aa39f0928a03a878 SHA1: 4f2d66594f12e0670fb739d4c7333bd5ffce4b44 MD5sum: 4880b2c099431c4b8afaa3e78dee6e67 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: libnifti-doc Source: nifticlib Version: 2.0.0-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1675 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-2~nd14.04+1_all.deb Size: 137676 SHA256: 3bab4349c0f35948663f799794b88328b12952dbb9eadb0e8a4085c0f270a5e6 SHA1: 8efa4c33a93f08cd665a505ac7aa01ce2a943db6 MD5sum: b29b153538f23cfdeddd32fc9dab6436 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48075 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1_all.deb Size: 2673508 SHA256: 6bfe8da2878784c3df24ef11993ad9d5b82019204eb362235bd094ac6865c0f8 SHA1: 714ad73ca23e5c34f65c7632c395534c4baf7898 MD5sum: 5f8cbf8fba45be0c2da0d39481c9c931 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: matlab-support-dev Source: matlab-support Version: 0.0.21~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 39 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.21~nd14.04+1_all.deb Size: 7520 SHA256: 306f62724d477630ccc2dfec6de9087b8453f9f7aa47f3fbc994fc4c43b72ac0 SHA1: ebcd6a3887968b987548d284ef4398e4b7403402 MD5sum: 4ebc4831c36822a6b9606d0c7b735787 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1138 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+nd14.04+1_all.deb Size: 71894 SHA256: be1b730b60e4e46c09f731c458418f51468a54bd0bcb30c1b3ae62895cf5195c SHA1: 13b72c29850c963b4b7163d5728101f262982fad MD5sum: 68aa342ecdbdd76b549b62f3a8a0cefb 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: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1708 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd14.04+1_all.deb Size: 1658672 SHA256: 8c6fbf4d4201736009058951a8b0a0649b14eb2b31222086e4c40337b7b701fb SHA1: d390758dd46655f60156a87578c4e8bde2f62f7f MD5sum: 5c2f269adc054ae2960074a3cfec33ba Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1019 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd14.04+1_all.deb Size: 577154 SHA256: 99c69da1658d3ad0d38a2e617b99c1e97b6dd659de73b4d17de6abe2c836bee6 SHA1: 40d30c9da283129d64c2490423bc06de65605f3d MD5sum: 1e4972d196978a16b51c6ab0b5170a0b Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mridefacer Version: 0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 674 Depends: neurodebian-popularity-contest, num-utils, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.2-1~nd14.04+1_all.deb Size: 637348 SHA256: 4886e1aec5e9f3f839fdd2784eef4113eb90cd82ecdd9a4966d4d2eecf48e091 SHA1: 1feb4d5652dbc9bea40667c98ba830b8e31fa69b MD5sum: e7e127d2deea7a141e45d8ebee81107d Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: mrtrix-doc Source: mrtrix Version: 0.2.12-1~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3490 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+nd14.04+1_all.deb Size: 3191882 SHA256: f32e1267d094094ab3cc0c0dea48e1ccf69fe473877e2e60136e4e6a27db354b SHA1: 31f466b044fd9b37817cda76e708ae9f65413a1e MD5sum: 391268dd332daa65f1524ad5d28fd893 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~nd14.04+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~nd14.04+1_all.deb Size: 16732 SHA256: 6736e45053839e6ccff6ae6acee08c1b6946082a3551db89f5b75cf011f56942 SHA1: 5459e0e22973aeac24902aeb831afaca776152d2 MD5sum: 27d1f7525d5b1676fab50f43523897b3 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 116 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.5~nd14.04+1_all.deb Size: 34670 SHA256: 27d8924cce466c8743a8bfac1a20d27ca7c95361f193e200fcadcbf1228a89ee SHA1: 7c16840530fee4f807283037c987fcbf2b6d846d MD5sum: 819ebe2bebae62a2d64d6c7b93cb62a9 Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47 Depends: gnupg2 | gnupg, dirmngr Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.5~nd14.04+1_all.deb Size: 10368 SHA256: 281d4c3efe1ea9fe9dec7cbfcbd5273db29efdc819c95088bd743caa3764365b SHA1: 60ffe59f22bfb3f282448983cc10be16ced90358 MD5sum: f4286ef29a98efc82e0cc8f7a59024c1 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 223 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.5~nd14.04+1_all.deb Size: 116424 SHA256: 72bb332a465a6ce6bf367e21c498a0e1b145b14cf91039fc9f4f336104802ea2 SHA1: bb4aaab8fd20e6e8b1243c4840a4730c0d6b8e0c MD5sum: 1bd984cb9b0d1e29487626d3f6767777 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.5~nd14.04+1_all.deb Size: 32752 SHA256: 3ae80fc47aa1c58d2688e04e57483f909ffb3c89c45432eeac01dc06ddd0e692 SHA1: 84d7224bed45fe6945e544e58aa0a8cf13cc40b8 MD5sum: 6dc651151e43b970824fe53be90c35b4 Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.32~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 108 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+nd14.04+1_all.deb Size: 14088 SHA256: 97679301db4c313bf776a5d18ff76e0b1af04b77da1156d1b500a56e308379b9 SHA1: 0b00e3321e0d1bc70c40437abc74430adcf4db07 MD5sum: f3f984c91e04f7b9ab57e22d1bb1af9b 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+nd14.04+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+nd14.04+1_all.deb Size: 7470 SHA256: 8da1af69542f153184f6d344861f1557e1a7a783b6c0b6d90b67e8dee8a855e6 SHA1: fc17ac754d0a08a79a0b1615c6ae10dcd89f36ea MD5sum: 341bf775ee30c2071e1c49a1acf6f88e Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 50 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.5~nd14.04+1_all.deb Size: 12372 SHA256: 3bd260bcca32f8fae3fd5edc128c686e21061d8d2e8425287df0e8db1cbdee47 SHA1: 68b5bc9fa75563438bf65962b0c262f92e218315 MD5sum: 15f78ba9ec48533873eb31ad0296b73a Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.8-1~nd14.04+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_0.4.8-1~nd14.04+1_all.deb Size: 615402 SHA256: 5c0c4de741d502aed671afa90ffd5f9d83bbb8d9b8fe3fb61e87a83207c51387 SHA1: 1e2cfa4676c02305b4cf2b7c081125917e51667b MD5sum: 35e250c61104ee3c777aa9d7ef48b08f 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: 0.5.25+ds-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3201 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.25+ds-1~nd14.04+1_all.deb Size: 656548 SHA256: 8064af40326c047def25c11da724ab3ea0413868d30a32a57305fe250d1365bf SHA1: a7dc0209ce01e5e9421a5c3f630a76d93063457e MD5sum: be13899722cba08aec5595d5c3a7f508 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: openstack-pkg-tools Version: 52~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 208 Depends: neurodebian-popularity-contest, autopkgtest, libxml-xpath-perl, madison-lite, pristine-tar Priority: extra Section: devel Filename: pool/main/o/openstack-pkg-tools/openstack-pkg-tools_52~nd14.04+1_all.deb Size: 52286 SHA256: a4df7374f259be2c071c76914b8360bb558b4312d78d890aec9c6118324a87cc SHA1: 19ba62f52e16fd00f449f4049759a8873f5a2b81 MD5sum: 9d4b190d850abd2a8956ca7a14f57edb Description: Tools and scripts for building Openstack packages in Debian This package contains some useful shell scripts and helpers for building the Openstack packages in Debian, including: . * shared code for maintainer scripts (.config, .postinst, ...). * init script templates to automatically generate init scripts for sysv-rc, systemd and upstart. * tools to build backports using sbuild and/or Jenkins based on gbp workflow. * utility to maintain git packaging (to be included in a debian/rules). . Even if this package is maintained in order to build OpenStack packages, it is of a general purpose, and it can be used for building any package. Package: patool Version: 1.7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 154 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~nd14.04+1_all.deb Size: 32710 SHA256: b55a4dd7d4b6fcae897c79098ea6c7fc3f44db099ae976bfbc8c2fe0e90e4023 SHA1: 9d8e823445d7bd29dfe4977ec96c5443660117d7 MD5sum: 7c8650415068489375b6a4744b344781 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: 1.83.04.dfsg-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15239 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.83.04.dfsg-2~nd14.04+1_all.deb Size: 6139662 SHA256: 3d8762b44b5c77b4400a1c50764d575806e7889b8a3ec091aa1e7f89d392c649 SHA1: ff4b55dc30099dba80b0d0a269957e0e3058be39 MD5sum: 48c612f217f0d00154e7bf9cb8d57bf6 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 221025 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.14.20170103+git6-g605ff5c.dfsg1-1~nd14.04+1_all.deb Size: 24376994 SHA256: 450235936f6613bb03e15f3f2cc1f43e38f72ace1ca118cceb3aba834f77f6af SHA1: 6d17ac2d378db0c69ca51245daa3bceaa6e3dee6 MD5sum: a03c766c24a22b089045c9e016e400b8 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-argcomplete Version: 1.0.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 144 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd14.04+1_all.deb Size: 24554 SHA256: d5cabbc1905eb2d7ea5f55e77e97716ba9c00b77df63e9898b994ac7d61ca0f2 SHA1: cf9bae80c9fd4f1a7b8e350fbd2aa88d1a58a236 MD5sum: 7324a2d86401f52c399054fb6e46effc Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-boto3 Version: 1.2.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 808 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-botocore, python-jmespath, python-concurrent.futures, python-requests, python-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python-boto3_1.2.2-2~nd14.04+1_all.deb Size: 58392 SHA256: 3d3119040de8890cdcd487ff2fef87ecc62ed8945f5511647643aa5e0aea72a7 SHA1: ec7638650a886404aec6eb2f742d1b047f1ea480 MD5sum: ae294468dc70a1bfda87a9216ec9825c Description: Python interface to Amazon's Web Services - Python 2.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python-brian Source: brian Version: 1.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2449 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-brian-lib (>= 1.4.3-1~nd14.04+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_1.4.3-1~nd14.04+1_all.deb Size: 401994 SHA256: f5134e5254775f86b341da337f269211f4f57b6a6d000f2c1379a46f34a3d69f SHA1: 3cb36dfc2d17dfadd13dae4498e5d6e81ea9c35a MD5sum: 1c64dd142a5972a930f1f894b6feb127 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7021 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.3-1~nd14.04+1_all.deb Size: 1985046 SHA256: 16712a925e735cb2152f8f06887d85f19cd2f596a8b257ab0f3d8946c7e1b47f SHA1: 3cd8e0dc358b894b0e8c9af157a4d40f303577a1 MD5sum: d37f6f42d788d3674072ab728bb407da 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-citeproc Source: citeproc-py Version: 0.3.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-lxml, python:any (<< 2.8) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python-citeproc_0.3.0-1~nd14.04+1_all.deb Size: 80330 SHA256: 5b5f6be622f54003050fb0f8a663cf3aa8a7f97366b5ea77b57533b8c8f07446 SHA1: 8decfdd25deee813d966d6406d9dd709e9995c5b MD5sum: 454929edf434ef2e5af0a46e869c0dd7 Description: Citation Style Language (CSL) processor for Python Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python modules. Package: python-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python-contextlib2_0.4.0-3~nd14.04+1_all.deb Size: 8664 SHA256: 0b7d2e2de082b5a6fd9cc18b1a1141ce13073a3012289ad768da93e3a9ae0b70 SHA1: 28c6d174d1c27f1e81bdbfa47a91232246ece17d MD5sum: 1a277de9fb763099abadab3313179e1c Description: Backport and enhancements for the contextlib module - Python 2.7 contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 2.7 module. Package: python-datalad Source: datalad Version: 0.4.1-1~nd14.04+1.1~nd1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3141 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), patool, python-appdirs, python-git (>= 2.1~), python-github, python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage | python-keyring (<< 9.2), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0~), python:any (>= 2.7.5-5~), python-boto, python-jsmin, python:any (<< 2.8) Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-requests-ftp, python-scrapy, python-vcr, python-yaml Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.4.1-1~nd14.04+1.1~nd1_all.deb Size: 608572 SHA256: 9c02121c629472df50945ac3ff35694262c902928b909d8ba60fb2d481064367 SHA1: d9c18c9695461744b9d7934862cd00783a942c5b MD5sum: 17fc886b78616b7a0efb3dff3c97a8ed Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling, publishing, and testing. If you need base functionality, install without Recommends. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 515 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python:any (>= 2.7.5-5~), python, python:any (<< 2.8), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd14.04+1_all.deb Size: 78266 SHA256: 7a23acdf2448ad1c837600309ef4412059656d6bf9cad8e40fa5a25a48f8b9cc SHA1: ce40c5fa0c77453a2031a77c09afd13115749d80 MD5sum: e7c62e3fb270103f855d7c836bc61486 Description: DICOM to Nifti conversion DICOM to Nifti conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a Nifti header extension or written out as a JSON formatted text file. . This package provides the Python package, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dicom Source: pydicom Version: 0.9.9-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1522 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~nd14.04+1_all.deb Size: 357476 SHA256: 945b26004df0bd99c707955bbd4c2f62ca2354a9634b35eac851deb93f8b4072 SHA1: 4068d98bbb0c39f2cb4de12dca51e71fa35a0733 MD5sum: dbe2aff786b7ce4469b7bf6b7773f623 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-dipy Source: dipy Version: 0.10.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5778 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.10.1-1~nd14.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.10.1-1~nd14.04+1_all.deb Size: 2441610 SHA256: f167bcd77c6b5384bf0c7f67950735ba1a3efb2020f2456ab4777bf47f1d3d32 SHA1: 973c68b2f91da696229df112ae0695630deb01ec MD5sum: bd4aa46a15b82c7cb5a937e4dc4e4691 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.10.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14345 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.10.1-1~nd14.04+1_all.deb Size: 11464772 SHA256: 7e1e4e10d931dfe1b6a82e9a4338973bb09869411486e308a1b7b9df69ac9e8e SHA1: a9c4969eb66647b387444314baed86e6e37ba549 MD5sum: f324973ae8f011dad397eaf266bfe307 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-dockerpty Source: dockerpty Version: 0.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-six Recommends: python-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python-dockerpty_0.4.1-1~nd14.04+1_all.deb Size: 10954 SHA256: 465b78ccd06e3944ec9cd2ddff99bcc2f49fad80f1b39e8d1ec2b778407813ba SHA1: af19030fa2646e03a5519fc4b192aced103984d5 MD5sum: ae2b822f6db05e0b384d36bcd94d2f3a Description: Pseudo-tty handler for docker Python client (Python 2.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 2.x version of dockerpty. Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2388 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+nd14.04+1_all.deb Size: 695948 SHA256: 37604b739e17ae561b68e1ffa8fd89495abab699acaa75ce4a4160ab0e9f1dc9 SHA1: ede08d0df1746f31ccb9eb6fbcdc49722e3b1b5b MD5sum: 95df9057ee0432389482bebb2bebc420 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-funcsigs Version: 0.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 89 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python-funcsigs_0.4-2~nd14.04+1_all.deb Size: 12750 SHA256: a6c50a81866eb65c9c537e5aeaf0759bc7462e40907c9fe0fe3ef74207e805fe SHA1: 7d3a78f5d60304466ea78ec3322afdbe3402ed80 MD5sum: 73c673b7466d986891e893635cc99ebc Description: function signatures from PEP362 - Python 2.7 funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 2.7 module. Package: python-funcsigs-doc Source: python-funcsigs Version: 0.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://funcsigs.readthedocs.org Priority: optional Section: doc Filename: pool/main/p/python-funcsigs/python-funcsigs-doc_0.4-2~nd14.04+1_all.deb Size: 24170 SHA256: 91020210e46dbf1ba30776a52fb45b5a2ebb0efd4e5a6b0d2812bf9fc40b2fde SHA1: e8a88a1101c2daefd42fdf0db9dcd120937fbe90 MD5sum: f68afc7bff6e189b89513589e9f83594 Description: function signatures from PEP362 - doc funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the documentation. Package: python-future Version: 0.15.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1732 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python2.7 Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python-future_0.15.2-1~nd14.04+1_all.deb Size: 336038 SHA256: dc7401310968162b4ebed3645055285c874be325278a45db71dd1f7843632105 SHA1: 9d81fea409dba56a49279ccec79875de6f81ee04 MD5sum: 52e5592c4017dc73747fd1376c878a94 Description: single-source support for Python 3 and 2 - Python 2.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 2.x module. Package: python-future-doc Source: python-future Version: 0.15.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1577 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://python-future.org Priority: optional Section: doc Filename: pool/main/p/python-future/python-future-doc_0.15.2-1~nd14.04+1_all.deb Size: 293316 SHA256: 35ae3d991bf118c268c62b0e11b65d3ee55f5383d4bd83214045e9c6d98c03cb SHA1: 0e113bbe784a0b1b4d9519a81dd347b85a8a8a86 MD5sum: f915855e035e4f2650021f7b348888a0 Description: Clean single-source support for Python 3 and 2 - doc Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the documentation. Package: python-git Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1610 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 2), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.1.0-1~nd14.04+1_all.deb Size: 299696 SHA256: 958ade498a3c586c57a32309946ad486595c35ab5728562a4eca7edf39df4547 SHA1: 3182c5e907ff284c2bf605766283e62ee9dfb974 MD5sum: b9ca29d82b88542b455360dddf6b6e0d Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 962 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.1.0-1~nd14.04+1_all.deb Size: 128140 SHA256: bda40329f0df3941d010ffedf243c61aeb1ff96e70fe1d83773415f73bb9ac46 SHA1: 5338c93cab6f48ace57559547a921fc6c406fe74 MD5sum: 836f0930695e73f7d271de5925536449 Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-github Source: pygithub Version: 1.26.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 625 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Conflicts: python-pygithub Replaces: python-pygithub Provides: python-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python-github_1.26.0-1~nd14.04+1_all.deb Size: 44732 SHA256: 5d65de3e1bff985556028c90eb52b633869d9371d2771014f38e4dca35a7de96 SHA1: 53560414fd90cd1233d599e8d02abd78d1385ae1 MD5sum: 93a6a8fdc72f81b23a4ecfe750f7464d Description: Access to full Github API v3 from Python2 This is a Python2 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python-humanize Version: 0.5.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 117 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python-humanize_0.5.1-2~nd14.04+1_all.deb Size: 12952 SHA256: b9524acfb16d327e1a07b147b15f7904766d20a3ad66ca41dc5364025c5e5429 SHA1: 9f57df6560f1c54888b2f4054166e0d04459aad1 MD5sum: 681f7ac6228c80c5a7cabb101baf0983 Description: Python Humanize library (Python 2) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 2 version of the package. Package: python-hypothesis Version: 3.4.2-2~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest, python-enum34, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python-hypothesis_3.4.2-2~bpo8+1~nd14.04+1_all.deb Size: 67326 SHA256: 647cb35c943ca4c657c131756568e7607759c00acd72699cd190e77677e5a517 SHA1: 8faae61bf7ba551eb0e200b53cba1445ec7a96a8 MD5sum: 7acbf528448837c1b00c32658b5711a9 Description: advanced Quickcheck style testing library for Python 2 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 2 module. Package: python-hypothesis-doc Source: python-hypothesis Version: 3.4.2-2~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1674 Depends: neurodebian-popularity-contest Homepage: https://github.com/DRMacIver/hypothesis Priority: extra Section: doc Filename: pool/main/p/python-hypothesis/python-hypothesis-doc_3.4.2-2~bpo8+1~nd14.04+1_all.deb Size: 265838 SHA256: 323574f31f678876a1da09766fa377b9add568c6f9ddd52c41eb05a15f230fce SHA1: e92990ddc961b273de22843f080c6697f97916b4 MD5sum: 85de79bf2bd150ff2fa40ca19b539457 Description: advanced Quickcheck style testing library (documentation) Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the documentation for Hypothesis. Package: python-jdcal Source: jdcal Version: 1.0-1~nd14.04+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~nd14.04+1_all.deb Size: 7670 SHA256: 1f7d63bfde1855c23e02ebfce05181789c84b273daab7ea32c66f78b1cca884e SHA1: 9d0226fb987ab11a64f01766cf92eacb9543bd28 MD5sum: 35bcdfe5fe51152dddaaaffafe9b8576 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python-joblib Source: joblib Version: 0.10.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 481 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_0.10.3-1~nd14.04+1_all.deb Size: 115526 SHA256: ae06f1ffa59d3b823fb5bfd72f7efc6d16a48008035f30fc07d7e4a6054cf33a SHA1: 4e646952c008683ce29d2a12fff9ade0d1f5f26e MD5sum: 95b289158927688ebc16515eec9866f4 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 2 version. Package: python-jsmin Version: 2.2.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python-jsmin_2.2.1-1~nd14.04+1_all.deb Size: 21542 SHA256: 21c013876d1adaf4dc1455487a62bc08eb08b475d30af74f38bffe17d9b8148c SHA1: d672a392d3d0fabab47226fc482be6cc49d4c086 MD5sum: 58b2be0fc06c8e81fdbfcb82bd1c64d9 Description: JavaScript minifier written in Python - Python 2.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 2.x module. Package: python-mdp Source: mdp Version: 3.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1375 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python-numpy, python:any (<< 2.8), python-future Recommends: python-pytest, python-scipy, python-libsvm, python-joblib, python-sklearn, python-pp Enhances: python-mvpa2 Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.5-1~nd14.04+1_all.deb Size: 277596 SHA256: b341f34d09056803b902d8ba6074b485f8fd96027352d147298090555a2ba731 SHA1: 95e7b548f0a5e1854f7f6b40be03e11fd602f13c MD5sum: 1dc1ac7dca838571b91743cf7b31369f Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-mne Version: 0.13.1+dfsg-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9858 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, python-pycuda, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.13.1+dfsg-1~nd14.04+1_all.deb Size: 4509604 SHA256: 5f613eb46c3b50158b90ef2b28d178ed76f4010237d55057099a5bc193c6740f SHA1: d5a471d34eeb48964f8fd56d7a516e133bcce811 MD5sum: d5c6cb8bdefe1cc3a86b01d7687eaf52 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+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 257 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+nd14.04+1_all.deb Size: 52650 SHA256: 89c6b2097aa4c46452fc4c94f25c9552c6bdbb11de0b74d3499a9fc731fcb138 SHA1: 180f3b068696bf9372da2ab0ebdeab29e18a44c1 MD5sum: ccd5f97d5b5360920b157174f29dcace 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: 2.6.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8450 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.7.1-0ubuntu2), python-mvpa2-lib (>= 2.6.0-1~nd14.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib, python-duecredit Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.6.0-1~nd14.04+1_all.deb Size: 5096038 SHA256: d562089a0dfb4fde4f9862a1d1043cb2fa21fd95f6e899c47d63bf6265a70181 SHA1: 4612c752533d7754c1f3c3abe568b39e9417e3a5 MD5sum: 81e676cc783cbb961a22789a8e4b86f9 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.6.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31451 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.6.0-1~nd14.04+1_all.deb Size: 4724816 SHA256: 5ceb8ac4f7292bdbbbebcd32c24012517c66fe082df78a4cf20f5ad6ee4da05c SHA1: 9b2f8638589b54ad0007435cf17a9eb9268899da MD5sum: 10afc20907a5fb784c172aa4323cc3ef 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-neurosynth Source: neurosynth Version: 0.3-1~nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 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+nd14.04+1_all.deb Size: 28812 SHA256: 15d6ad200903f48f7d0ac38e08d3aea9a417b73085929fcdacce541b5ecb0f05 SHA1: ab997820ecbef62ee9805767c8810a4a4663c6a4 MD5sum: 6ca9dceaed50e4921f7759c6fe0b948f Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-nibabel Source: nibabel Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64167 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy Recommends: python-dicom, python-fuse, python-mock Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.1.0-1~nd14.04+1_all.deb Size: 2162182 SHA256: 5dabbe7ea1254fb0400741f72909ef621d0f47de484f698e48475ae341ac2f54 SHA1: 2072ef76e37cbbd74ec8de2f9db246734b4fba78 MD5sum: e9f26bd80cd013dbfd3c78bc1068e8ae Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Package: python-nibabel-doc Source: nibabel Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22074 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_2.1.0-1~nd14.04+1_all.deb Size: 2521682 SHA256: 819b8a8e27a7759c5cb81e8fb2b83824ada4fd45e92c27dbf0ca4e21fa24f1b2 SHA1: 93b06779cb3f224ae11ea2152f99fed1bbb831a6 MD5sum: f1b11d73f29468b673eb458fb81fe864 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2437 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6), python:any (>= 2.7.5-5~), python-nibabel (>= 1.1.0), python:any (<< 2.8), python-scipy (>= 0.9), python-sklearn (>= 0.12.1) Recommends: python-matplotlib Provides: python2.7-nilearn Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python-nilearn_0.2.5~dfsg.1-1~nd14.04+1_all.deb Size: 731138 SHA256: 27e64f205d899c6c771515afe37216ea3580025aa23cdb54c4e3215d4446fb78 SHA1: 0366f70e98fa1b0cbc268f6a28bfa1e096bf1880 MD5sum: aeae2c4d9b9365339daff1c25b57d453 Description: fast and easy statistical learning on neuroimaging data (Python 2) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 2 version. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.4.0+git26-gf8d3149-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3339 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 (>= 0.4.0+git26-gf8d3149-2~nd14.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.0+git26-gf8d3149-2~nd14.04+1_all.deb Size: 738044 SHA256: c06b1d13f10e0f689862dcc12dab0688a541b5691db9c3001eb0f642241357b3 SHA1: d54c171213cbbfb5e5f68a07193ea6d941f65133 MD5sum: 6171644c4f44fdb606875ed8fbcb45c6 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.0+git26-gf8d3149-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8212 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.0+git26-gf8d3149-2~nd14.04+1_all.deb Size: 1152024 SHA256: af524b7a9bd6ef362189bdb835dde7e7836854aab113164b6248a9081ce92e1c SHA1: 64b21be8daf84f53adc37f2402f019e31553790b MD5sum: bd6bd7e3ec815321609366ea756536fc 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4573 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~nd14.04+1_all.deb Size: 1158946 SHA256: 39836fcb648f64546c684c1831a50292c701b204b127ee8ea9a3ac3d162dce69 SHA1: fc0b5f3620bc163b435ce94c3537f601bd89ce0c MD5sum: f56846a6794f64b052f434dac5e5e4ca 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~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20779 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~nd14.04+1_all.deb Size: 8759220 SHA256: 4b2c7602f68541b83fefb69f9e2b3277109f40fb53ce0ab93fffdd461303f5e7 SHA1: b5dd929f7a8df02f697c2ca7e98fc28cf8f1e95a MD5sum: 91069fca772934ae6d749a309252bb74 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9397 Depends: neurodebian-popularity-contest, python-matplotlib, python:any (<< 2.8), python-scipy, python:any (>= 2.7.5-5~), python-numpy Recommends: python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.7-1~nd14.04+1_all.deb Size: 2561294 SHA256: a15abdc79be7a20df3e57ea7749aaa252da17fda7a4dbbbf5042e9f2aec01e05 SHA1: a35a7eca96ccc98026e2d8d26e3aac314b794c41 MD5sum: 461b075819a402682cefa6156d1b478b Description: timeseries analysis for neuroscience data (nitime) Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code. Package: python-nitime-doc Source: nitime Version: 0.7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7725 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.7-1~nd14.04+1_all.deb Size: 5711820 SHA256: 2bdc0adf0d4b51d09953c037c0395c1c55c462d8bd3e4afd3909f8b19ebfd28c SHA1: cdb5d3fe1fde8a1e40e335372db76e91c1fa7cd4 MD5sum: 5a16154ba239c2b3d124484b5b98f0d8 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-nosexcover Source: nosexcover Version: 1.0.10-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python-nosexcover_1.0.10-2~nd14.04+1_all.deb Size: 5250 SHA256: b2ae93571b0725e740f89e8b03cb902089365182868a9a8c8545c5037a2ccbf0 SHA1: 256b21a4c6b869033aa366e3cd70e4557846983c MD5sum: 04cf2021c398ef47e5fcf18a72394497 Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1121 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-jdcal Recommends: python-pytest, python-pil, python-imaging, python-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0~b2-1~nd14.04+1_all.deb Size: 191632 SHA256: df1c6182bb909af72b09ea8851da8e2c35717fdff7d298c5f8df9e1c01e96a6e SHA1: ce80135d40a9fc5e629b1ea13983beae49942ef9 MD5sum: 0631060ddd63fb027edeca77f0d8a195 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: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24201 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.18.1-1~nd14.04+1), python-pkg-resources, python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.18.1-1~nd14.04+1_all.deb Size: 2527632 SHA256: 7d7f696b3f35a86f86bffad275cba3cd9c50ffc019d6a6bf7528274c8c4d897c SHA1: 1537850796be6784bdc63d047e40873d657a777c MD5sum: da8eb9f836bef8fce71cd7faff5ce5ed Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56875 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.18.1-1~nd14.04+1_all.deb Size: 11547442 SHA256: 109386dee6d9887c77eeb31c9c3845e2c4fa7e78b50976892a20dc233d4921f3 SHA1: 775dd6018dad37dc79deb26aa7550e7fd1a674a6 MD5sum: 2a804c6a815ba54c61200c664345b4b9 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 794 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-six, python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.4.1+git34-ga5b54c2-1~nd14.04+1_all.deb Size: 169660 SHA256: 77b9d02b054ba4198fd46f95fd150c61d358f04ff06166791e63f9176c29c744 SHA1: 54d4d402259bac80702def8977b2a16f3d653386 MD5sum: c2dce80f4167a4e670ea8584b177b5ee Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1305 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.4.1+git34-ga5b54c2-1~nd14.04+1_all.deb Size: 358472 SHA256: 3041dc086fa93417515ad44b504d26d25f8570798a17494776d1a6d0a5ba49bf SHA1: daf8a695fef97f96c3c95ff0a34ac2a592c6485d MD5sum: 02435a846fe08316791f189332aa78e4 Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.10+1+nd14.04+1 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+nd14.04+1_all.deb Size: 81638 SHA256: a3672edffea33c0135dc765fe3dbe3524115cf8cd1ae636f2bf7cbc09cfc47be SHA1: c317f00152e89dbf84b5a85ea883b44920eef65a MD5sum: 421e4d9f4c03a34b12fbffb0d0f92b25 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-py Version: 1.4.30-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 269 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.30-1~nd14.04+1_all.deb Size: 66656 SHA256: b247e9257aa8067c8d3d4798716dd149ffcdeee0f161f7ddc0ea0ca6575e932e SHA1: 0a2216498793395a85739146301a250231177798 MD5sum: 62f120862eaaf8fd92e04296bda302e6 Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, graphviz, python-pyparsing (>= 2.0.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python-pydotplus_2.0.2-1~nd14.04+1_all.deb Size: 20246 SHA256: 2680420223b68b4e90a0e9fa995a31a5cc60f9f01d3f66d9ad667efbb7d42d60 SHA1: dfe94fade1ce954bdc6d6d2d91cd8022638af42c MD5sum: 406e4724c36431b6b0044f1d30ee4f51 Description: interface to Graphviz's Dot language - Python 2.7 PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 2.7 module. Package: python-pydotplus-doc Source: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 755 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-1~nd14.04+1_all.deb Size: 178508 SHA256: 6b083d0f654230dd8213720aa6cb97bdfac7e23bd8b4ebf0df14d83345b74e54 SHA1: 12eb8384d62b1467bf227659d49ac60786613235 MD5sum: 313af7833740ba616df312eca87c064e Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+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+nd14.04+1_all.deb Size: 819336 SHA256: 4fd57971c92c6cd4cefaf9f32063e2c926a4cb901726c02263d9b4ea8cc24bb8 SHA1: 13d0d3aa4656070b80d4bed6e11ef0228e43b195 MD5sum: 335b1dfa97a9d8678444c11354131088 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-pygraphviz-doc Source: python-pygraphviz Version: 1.3.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://pygraphviz.github.io/ Priority: optional Section: doc Filename: pool/main/p/python-pygraphviz/python-pygraphviz-doc_1.3.1-1~nd14.04+1_all.deb Size: 67900 SHA256: 7c34df50d8f08bc1e04ea61edf29492ec557263a8f5c990a7c3bb22142d0f6e2 SHA1: c3a73b8871316b164182e70e862941e6db5847c1 MD5sum: 7e0f8aaa9f527c56ca61e3bad03d97ba Description: Python interface to the Graphviz graph layout and visualization package (doc) Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. . With Pygraphviz you can create, edit, read, write, and draw graphs using Python to access the Graphviz graph data structure and layout algorithms. . This package contains documentation for python-pygraphviz. Package: python-pyld Version: 0.6.8-1~nd0~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Homepage: https://github.com/digitalbazaar/pyld/ Priority: extra Section: python Filename: pool/main/p/python-pyld/python-pyld_0.6.8-1~nd0~nd14.04+1_all.deb Size: 37232 SHA256: eac31a0d6a0838ab20a782ff1ae969f789ee0d47da1ac9e062d6da7a5a4a01c8 SHA1: 772f3d8f573c84e311fcf685e5691b5270108a5b MD5sum: a3cd10fdabf7d87545663b4b8bc1bb86 Description: implementation of the JSON-LD API This library is an implementation of the JSON-LD specification in Python. . This package provides the Python 2.x module. Package: python-pymc-doc Source: pymc Version: 2.3.4+ds-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1860 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: doc Filename: pool/main/p/pymc/python-pymc-doc_2.3.4+ds-1~nd14.04+1_all.deb Size: 839822 SHA256: ca5b4a1c229d97f73a5efabb5bce300e4461516be6d6ca3fb09a71accd13d6dc SHA1: b7faad248279ffb84dc5464d0d050883c20afe1c MD5sum: c2f9774d355e63c5a38e9d90065b3aed Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. . This package provides the documentation in HTML format. Package: python-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 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+nd14.04+1_all.deb Size: 122882 SHA256: 62e294043371c55fc47adddcd8c00ee9b823bfc2885a7fe6a17545f5a9ba2cea SHA1: ac1a6014356d9f0d27fe921f17abf9a006bc6dfd MD5sum: d08fcaa0e9cdb30bfb91d7d5082d4941 Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pytest Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python:any (<< 2.8), python:any (>= 2.7.5-5~), python Suggests: python-mock (>= 1.0.1) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python-pytest_2.7.2-2~nd14.04+1_all.deb Size: 102268 SHA256: a5bc67d196abb4d30d1d59f9ddb6cc31ba957acd0cd6a1238661d5f1d9b64eac SHA1: 4dcfe73451f8b239c438acb5319988f1f6f42608 MD5sum: c0a87dff9798b7418e011f2d0d38428e Description: Simple, powerful testing in Python This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. Package: python-pytest-doc Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2879 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-pytest | python3-pytest Homepage: http://pytest.org/ Priority: optional Section: doc Filename: pool/main/p/pytest/python-pytest-doc_2.7.2-2~nd14.04+1_all.deb Size: 401394 SHA256: 9454eed49ee66eae353e2980c3d4eb49cda6377b0a129038702726d6e993a988 SHA1: f4c4aa66f6106f3715640dd31bc4d987df510199 MD5sum: 6daf8937fe0654a85e2290e98d04119a Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python-pytest, python-werkzeug (>= 0.10), python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python-pytest-localserver_0.3.4-2~nd14.04+1_all.deb Size: 19208 SHA256: 6dc0826378989aa452e64dd8197b2daf87e5421da9dcd9780c7cfcdce32d90d0 SHA1: 918c1eed4cda552d75b0fb8d2cb4f9c59558c0ee MD5sum: 77c5995e27fabad5d0e0dacd2d6e9f85 Description: py.test plugin to test server connections locally (Python 2) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 2. Package: python-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-pytest, python-tornado Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python-pytest-tornado_0.4.4-1~nd14.04+1_all.deb Size: 5674 SHA256: 3df1aabe30adc5bcdb999720babc481798f61c8bd2af76cc81f4cb84a5fb8b8c SHA1: 0cc076b5af86d42d85122d8b771de2a4dd734835 MD5sum: 1d7b0e30f16aa344c6dbfb70f9900944 Description: py.test plugin to test Tornado applications pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 2 code. Package: python-scikits-learn Source: scikit-learn Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.18.1-1~nd14.04+1_all.deb Size: 70638 SHA256: ef5d68ff8e12a22e5411bcc39c43259a9d7d104072a50a3b95307f326faee892 SHA1: 94d263c3aa9e19c74dd1b5574514fa907605e930 MD5sum: a23633e196ef6db89b752f753185634f Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-scrapy Version: 1.0.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 812 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-lxml, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python:any (>= 2.7.5-5~), python:any (<< 2.8), python-twisted, python-six, python-pyopenssl, python, python-service-identity Recommends: ipython, python-django, python-guppy, python-imaging, python-mysqldb, python-pygments, python-simplejson | python (>= 2.6) Suggests: python-openssl Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.3-1~nd14.04+1_all.deb Size: 175830 SHA256: 43ae160995859d66d0969c6597daa3610ac3a38b35ac822e0185b15c57c9bc11 SHA1: 5a96e9daa65d1cd722efd64527f2f4d7089e38f4 MD5sum: 05bd415ef1af3f5e412b2e611376f0e8 Description: Python web scraping and crawling framework Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy script and modules. Package: python-scrapy-doc Source: python-scrapy Version: 1.0.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5944 Depends: neurodebian-popularity-contest Recommends: libjs-jquery, libjs-underscore Homepage: http://scrapy.org/ Priority: optional Section: doc Filename: pool/main/p/python-scrapy/python-scrapy-doc_1.0.3-1~nd14.04+1_all.deb Size: 651116 SHA256: 3c566a34a50e23f25f2202b780c695376e27978f404620c6bc4d389616af90ae SHA1: 9790445a5217b150a3649ac65456f9a1305cce43 MD5sum: 1e260cbd681a4cbf11874aa000a97b81 Description: Python web scraping and crawling framework documentation Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy documentation in HTML format. Package: python-seaborn Source: seaborn Version: 0.7.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 787 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-numpy, python-scipy, python-pandas, python-matplotlib Recommends: python-statsmodels, python-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python-seaborn_0.7.1-2~nd14.04+1_all.deb Size: 128266 SHA256: 5d3897320d18efed79acc2da5e2d06f5929df640b8c75931e676ba94e744b1d3 SHA1: 631132c5ec07db4a524c97d6fe27f8a34d3a81e5 MD5sum: 36d658e22fc6bd38cc6c2a5f525da235 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 2 version of the package. Package: python-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python-setuptools-scm_1.8.0-1~bpo8+1~nd14.04+1_all.deb Size: 10144 SHA256: 81fa741285e7fcba5088c45e5b0438f16fb94ecb2ce15d54362a66bdc635b62a SHA1: 0337593c9317611d4e8437b4a08a1767d868925f MD5sum: 4bdc1a720e93fecf17c65b8e1690ce09 Description: blessed package to manage your versions by scm tags for Python 2 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 2. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 11018 SHA256: e541fbf52c8d157e98be2e3d3d54fb033d5e30880458d9b143aab22f9fcbe65e SHA1: dd2095a9d2b56400abeecd526982b047084f0bdf MD5sum: 0bf7c71f9bb8cc5137d0e12156ad46d5 Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 13266 SHA256: 3a2a5d68772088d86ddca061fa261ce001e746c4c5b567216bf9f8aa641569bd SHA1: a86caffffa3a87341f18e5d13fa820e2e764bf1c MD5sum: 770748590bd24a026041c4970f925111 Description: Python 2 and 3 compatibility library (universal wheel) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six as a universal wheel. Package: python-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15134 Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-six (>= 1.3.0), python-skimage-lib (>= 0.10.1-2~nd14.04+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2) Recommends: python-imaging, python-matplotlib (>= 1.0), python-nose, python-pil, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11927494 SHA256: 82c528be9e874b39de21a4bba62421c1d6bd7589c9596093dcf97becccbfa3ae SHA1: 172a2e19e17e3b5e2b165127f92fe4ef51f60003 MD5sum: 5c1c7e773ca81f8494f6b4b97e17b06d Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21865 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.10.1-2~nd14.04+1_all.deb Size: 17205200 SHA256: 60b9c823532f9aad362ddf844c783ae8afc19152e3a8633699c1b906979ba876 SHA1: ffda4a2dd76fb4d7df9deefa82715439553fa6fd MD5sum: 34188666367a224580d2a0306199c599 Description: Documentation and examples for scikit-image This package contains documentation and example scripts for python-skimage. Package: python-sklearn Source: scikit-learn Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6603 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), python-numpy, python-scipy, python-sklearn-lib (>= 0.18.1-1~nd14.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.18.1-1~nd14.04+1_all.deb Size: 1391808 SHA256: d9aa28167b603a93ba23a9e5ed5d3049061a3335f114def6be2213239c0e2edf SHA1: 9bb21aa1dbbacb047c131afe278d1b25a6759b9e MD5sum: 1fa3911d19945f387973c018c4f44061 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28324 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.18.1-1~nd14.04+1_all.deb Size: 4812752 SHA256: 0bcf078dc0751ede387658e1903d30cf4c2949b5ed052c012c2995ded7b23aea SHA1: eb50c825f35c1cb6876ebf46460c8119fdef4365 MD5sum: 6b166b1964690277c22af56247b820f9 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-smmap Version: 2.0.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 117 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_2.0.1-1~nd14.04+1_all.deb Size: 20262 SHA256: 40951238c7d86c19dbb3425c74bdc47e51abdb9ba6c9999c7b9fca95c30ab8ce SHA1: 2ea4c4e6d513197cddc6683f27008332b87d13c0 MD5sum: cf7b83382570e645c913cc8cc801372a Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 2. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python:any (>= 2.7.5-5~), python:any (<< 2.8) Recommends: python-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python-sphinx-rtd-theme_0.1.8-1~nd14.04+1_all.deb Size: 117170 SHA256: 8d17f4cf1b75a6ea2e35dcc4ca9eb270006eeed87c54cd5eb0899e710fef410b SHA1: 7d682ebcb2df6a4681a2347d1d6f2931718ef0c4 MD5sum: 74729ef3e6968eb8ae00592b5ba23e8f Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-spykeutils Source: spykeutils Version: 0.4.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2090 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_0.4.3-1~nd14.04+1_all.deb Size: 309540 SHA256: 820c3ca420f026ec91cc0fa2018226bacd069ca010fdbf3a7a612a12be31ee15 SHA1: 11d04fd42bf9a14850534d5bf4a7b33347902451 MD5sum: 0722e50cf3dff91d8fab11c5a79c3d1b Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15956 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-statsmodels-lib (>= 0.8.0~rc1+git43-g1ac3f11-1~nd14.04+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib, python-cvxopt Suggests: python-statsmodels-doc Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.8.0~rc1+git43-g1ac3f11-1~nd14.04+1_all.deb Size: 3343660 SHA256: 186d24eb6911303e95492e2386ad448d3b0853cf9fcdd92282c9cf419d6f4e6d SHA1: b310c79c5ae84c744fd991dda4c755e92428bd25 MD5sum: 51b1658efb7a1c154a0b7037291337df Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.8.0~rc1+git43-g1ac3f11-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47867 Depends: neurodebian-popularity-contest, libjs-jquery Recommends: libjs-mathjax Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.8.0~rc1+git43-g1ac3f11-1~nd14.04+1_all.deb Size: 8391500 SHA256: c5e1482c8036a6dc2bfc516701bb45a2e3056fd9e39a9ae6e2256d157e748e9d SHA1: 4fee9d0509c8d7cd1c7ede6396102404b638ad24 MD5sum: 2479f6ebc64942301121df5544ef17e7 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-surfer Source: pysurfer Version: 0.7-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-nibabel, python-numpy, python-scipy, python-pil | python-imaging, mayavi2, python-argparse Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.7-1~nd14.04+1_all.deb Size: 42656 SHA256: 26a2aee7b9f7eba742934c92bb83be88743c5dafb47ae6b54818241a953c5c33 SHA1: a47b7b7155e973f9034c6f29c2fd1019bf8aa732 MD5sum: 40b11386b4c184630504570cdc63c356 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-tqdm Source: tqdm Version: 4.11.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 200 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python-tqdm_4.11.2-1~nd14.04+1_all.deb Size: 49804 SHA256: f3c00c205069f53baf6546179f4950d09d670c0f0833b587261656beb2da7ecb SHA1: 61b94fc29b6577c04cb362b1cc85ed8c0749cea8 MD5sum: e2c18ee1f2c9fe8122b241d380eaa79e Description: fast, extensible progress bar for Python 2 tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 2 version of tqdm . Package: python-w3lib Version: 1.11.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python-six (>= 1.6.1), python:any (>= 2.7.5-5~), python:any (<< 2.8) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python-w3lib_1.11.0-1~nd14.04+1_all.deb Size: 14094 SHA256: a143ab050c507692654ddeae18ca7ac254b7d86ac239c5046c0fe27d9f426366 SHA1: 8eb4554d5350ada80f23c95f42aea045a4554427 MD5sum: bbc1d292a81d284a45060953fac74aa8 Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python:any (>= 2.7.5-5~), python:any (<< 2.8), libjs-jquery Recommends: python-simplejson | python (>= 2.6), python-openssl, python-pyinotify Suggests: ipython, python-genshi, python-pkg-resources, python-lxml, python-greenlet, python-redis, python-pylibmc | python-memcache, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python-werkzeug_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 163266 SHA256: 30d72ddc76c40209588e9aca6110a9e7ccad863cb1e2e56d94652993743512f4 SHA1: 49839c379ce6906a8c7d6673650a6530ab1db7e7 MD5sum: a5499bc02b89cf7549e9e8cfd8e65ad9 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python-werkzeug-doc Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2559 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Conflicts: python-werkzeug (<< 0.9.3+dfsg-2) Replaces: python-werkzeug (<< 0.9.3+dfsg-2) Homepage: http://werkzeug.pocoo.org/ Priority: extra Section: doc Filename: pool/main/p/python-werkzeug/python-werkzeug-doc_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 879504 SHA256: 587cfad920e8ede1479ad00bd06417bd6839666b44fa595e8a6fcaec11d135a1 SHA1: 0901b6f1e3dca6bbc5800ae98324e4972a848276 MD5sum: 7cef970aad6fc4f6ce0fd38f8b68c13a Description: documentation for the werkzeug Python library Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 123 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd14.04+1_all.deb Size: 20990 SHA256: fcfb82d58ed9db706b5fb445a5d1a7b92c8af3c6e50e9ab6824a4b044ffa06c9 SHA1: 56062ca9770fd9bb9dbb58b7ba697a1395277aaa MD5sum: 62290f7da03fbe39f1ca8ffb65d81006 Description: bash tab completion for argparse (for Python 3) Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 3.x. Package: python3-boto3 Source: python-boto3 Version: 1.2.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 805 Depends: neurodebian-popularity-contest, python3-jmespath, python3:any (>= 3.3.2-2~), python3-botocore, python3-requests, python3-six Homepage: https://github.com/boto/boto3 Priority: optional Section: python Filename: pool/main/p/python-boto3/python3-boto3_1.2.2-2~nd14.04+1_all.deb Size: 58098 SHA256: 8c3dd34cff90255e169daec1cd1bd9d7e1fcb27b11ab2c4ccd693f668208413d SHA1: 8f36d6cc5664c9bcd9a1aaeb447b5acf4431e915 MD5sum: a151e40df463e8aad2dd7b1ae1eceb73 Description: Python interface to Amazon's Web Services - Python 3.x Boto is the Amazon Web Services interface for Python. It allows developers to write software that makes use of Amazon services like S3 and EC2. Boto provides an easy to use, object-oriented API as well as low-level direct service access. Package: python3-citeproc Source: citeproc-py Version: 0.3.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 731 Depends: neurodebian-popularity-contest, python3, python3:any (>= 3.3.2-2~), python3-lxml Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd14.04+1_all.deb Size: 81778 SHA256: 5ca21fbd35228899a0a548d3b2fbd7b70c3d3a90d59ee7598948acf90656e426 SHA1: 9a1da1d78f649a29d9957a000aa9d96323c7812a MD5sum: 6b26c48e4aaa89ffb0cc338355c500ea Description: Citation Style Language (CSL) processor for Python3 Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python 3 modules and the CLI tool csl_unsorted. Package: python3-contextlib2 Source: contextlib2 Version: 0.4.0-3~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 55 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://contextlib2.readthedocs.org/ Priority: optional Section: python Filename: pool/main/c/contextlib2/python3-contextlib2_0.4.0-3~nd14.04+1_all.deb Size: 8736 SHA256: 72841c88eabc50f3a870806d07a94f2e4c8b8c17f132af58a14eaac4099af14a SHA1: 1668fe8f673231165b07873c808a929702e3c90b MD5sum: 87622dd630ad0afc1284146b2ead624f Description: Backport and enhancements for the contextlib module - Python 3.x contextlib2 is a backport of the standard library's contextlib module to earlier Python versions. . It also serves as a real world proving ground for possible future enhancements to the standard library version. . This package contains the Python 3.x module. Package: python3-dockerpty Source: dockerpty Version: 0.4.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 79 Depends: neurodebian-popularity-contest, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-docker (>= 0.7.1) Homepage: https://github.com/d11wtq/dockerpty Priority: optional Section: python Filename: pool/main/d/dockerpty/python3-dockerpty_0.4.1-1~nd14.04+1_all.deb Size: 11020 SHA256: d6ec663d5426d4422ba5425ea2c0fc69d6b0b93ffa216d8340e749348bbe0e7c SHA1: 86265ab086768f338bb073fa3c690a018449ffed MD5sum: 5df3b91a766638bd70898e0579391473 Description: Pseudo-tty handler for docker Python client (Python 3.x) Provides the functionality needed to operate the pseudo-tty (PTY) allocated to a docker container, using the Python client. . This package provides Python 3.x version of dockerpty. Package: python3-funcsigs Source: python-funcsigs Version: 0.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 89 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-funcsigs-doc Homepage: http://funcsigs.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-funcsigs/python3-funcsigs_0.4-2~nd14.04+1_all.deb Size: 12832 SHA256: 37684478429b457dee602d6aa1519743da4149c9be0a9b9631853f5072a5be68 SHA1: 5186c91038a589d1f00ffb17022c1ed706403718 MD5sum: e225fa83d1cdfeec6ca881c05924e9a0 Description: function signatures from PEP362 - Python 3.x funcsigs is a backport of the PEP 362 function signature features from Python 3.3's inspect module. The backport is compatible with Python 2.6, 2.7 as well as 3.2 and up. . This package contains the Python 3.x module. Package: python3-future Source: python-future Version: 0.15.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1663 Pre-Depends: dpkg (>= 1.15.6~) Depends: neurodebian-popularity-contest, python3.4, python3:any (>= 3.3.2-2~) Suggests: python-future-doc Homepage: https://python-future.org Priority: optional Section: python Filename: pool/main/p/python-future/python3-future_0.15.2-1~nd14.04+1_all.deb Size: 333824 SHA256: d80df414502fa8896b82cd934dfdb63b1e8322696c947f84d8254fed9145b758 SHA1: fa57c7e6361593c539b26afbd413a9a9b3cf34de MD5sum: 062922c9fd88c6a3d8a84ab08dd474fa Description: Clean single-source support for Python 3 and 2 - Python 3.x Future is the missing compatibility layer between Python 2 and Python 3. It allows one to use a single, clean Python 3.x-compatible codebase to support both Python 2 and Python 3 with minimal overhead. . The imports have no effect on Python 3. On Python 2, they shadow the corresponding builtins, which normally have different semantics on Python 3 versus 2, to provide their Python 3 semantics. . This package contains the Python 3.x module. Package: python3-git Source: python-git Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1605 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 2), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.1.0-1~nd14.04+1_all.deb Size: 299524 SHA256: 0f53ea088d9534002e933edf2dec20e7bba7e6da329bd648a34e25d940a6af5f SHA1: 227169cab8d9224ba9540406a7447d5bb6f69620 MD5sum: f7528618cb3000344e7d8dd64c2dd316 Description: Python library to interact with Git repositories - Python 3.x python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 3.x module. Package: python3-github Source: pygithub Version: 1.26.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 623 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Conflicts: python3-pygithub Replaces: python3-pygithub Homepage: https://pypi.python.org/pypi/PyGithub Priority: optional Section: python Filename: pool/main/p/pygithub/python3-github_1.26.0-1~nd14.04+1_all.deb Size: 44856 SHA256: 3c798d85b70eaa94f678a931d45d9356361a814edb1926b6d396b1c97a72d190 SHA1: b0a83daca16a5b60316612ad8dbff4cbba8ea5ed MD5sum: 42c50d2bdee56e5b53aeb0c0d7b7bf40 Description: Access the full Github API v3 from Python3 This is a Python3 library to access the Github API v3. With it, you can manage Github resources (repositories, user profiles, organizations, etc.) from Python scripts. . It covers almost the full API and all methods are tested against the real Github site. Package: python3-humanize Source: python-humanize Version: 0.5.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 114 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: http://github.com/jmoiron/humanize Priority: optional Section: python Filename: pool/main/p/python-humanize/python3-humanize_0.5.1-2~nd14.04+1_all.deb Size: 12682 SHA256: 392c4a2e07c72ad76f98a7bee9625ed7631477c377a61275e855c48a5ebafbd9 SHA1: d6f38ce9bbf537c685316b39f486acf21e96f11f MD5sum: 83735535f9e1e28f2251831c80e2e640 Description: Python Humanize library (Python 3) This library proposes various common humanization utilities, like turning a number into a fuzzy human readable duration ('3 minutes ago') or into a human readable size or throughput. . This is the Python 3 version of the package. Package: python3-hypothesis Source: python-hypothesis Version: 3.4.2-2~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 393 Depends: neurodebian-popularity-contest Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python3-hypothesis_3.4.2-2~bpo8+1~nd14.04+1_all.deb Size: 67344 SHA256: 5f603f39a98f4d6122502653053628f21e663fec53eb9cb0dcff07051e46fa8d SHA1: bab4ed2b78660837d811bdde37715bda0e0fd0c7 MD5sum: c2b700f731b9506bda8cc1100dc6540a Description: advanced Quickcheck style testing library for Python 3 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 3 module. Package: python3-jdcal Source: jdcal Version: 1.0-1~nd14.04+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~nd14.04+1_all.deb Size: 7468 SHA256: 94b7e4cf3470fc765314561c161e497952f1597f87ab641b702080c2dc2c4249 SHA1: 64f8dbeedd11a34c60e16344e5943e5977723c4a MD5sum: 3f05614962ed5a2ba097afe9a6646e99 Description: Julian dates from proleptic Gregorian and Julian calendars This module contains functions for converting between Julian dates and calendar dates. . Different regions of the world switched to Gregorian calendar from Julian calendar on different dates. Having separate functions for Julian and Gregorian calendars allow maximum flexibility in choosing the relevant calendar. Package: python3-joblib Source: joblib Version: 0.10.3-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 472 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_0.10.3-1~nd14.04+1_all.deb Size: 112144 SHA256: 3e8edd7a6552158f237a1a86017b265867a5afd3159b6f2622ad65cd1b20e49d SHA1: a5b7946048a1902a92a43e9d67cb5c49f8eb4321 MD5sum: 15a6466b59372002b6737f9192ffdf09 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 3 version. Package: python3-jsmin Source: python-jsmin Version: 2.2.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/tikitu/jsmin Priority: optional Section: python Filename: pool/main/p/python-jsmin/python3-jsmin_2.2.1-1~nd14.04+1_all.deb Size: 21608 SHA256: aafc5275a8e6590b28c1a39b4bc04dcf92bfd8acecddd33115bb4e84b134f444 SHA1: d136effad4ccc67de5640cc9aa9a288210239087 MD5sum: afdb2f8f14a9e71f03a5cdd096c231ec Description: JavaScript minifier written in Python - Python 3.x Python-jsmin is a JavaScript minifier, it is written in pure Python and actively maintained. . This package provides the Python 3.x module. Package: python3-mdp Source: mdp Version: 3.5-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1373 Depends: neurodebian-popularity-contest, python3-future, python3:any (>= 3.3.2-2~), python3-numpy, python-numpy, python-future Recommends: python3-pytest, python3-scipy, python3-joblib, python3-sklearn Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.5-1~nd14.04+1_all.deb Size: 275288 SHA256: 933a89a5ed29ea4fac21629f5c29ea097b0677a531e0ce61b501c5f7dc10fb9c SHA1: 4cf2240a0cebaacccb73390a1d3eba3f61a2df27 MD5sum: 67945f3d1e3c5dd87c3c3549ce0d29ea 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-nibabel Source: nibabel Version: 2.1.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 64135 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy Suggests: python-nibabel-doc, python3-dicom, python3-fuse, python3-mock Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.1.0-1~nd14.04+1_all.deb Size: 2154596 SHA256: 4ff26c8c1783929f674ff94b643b8b82b93ed80776d078767abc6f519876d8c1 SHA1: 7f064e84587792922725b1f2dfc1e6fa73572616 MD5sum: 70d72a888925c517b8bf960200055b11 Description: Python3 bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. Package: python3-nilearn Source: nilearn Version: 0.2.5~dfsg.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2189 Depends: neurodebian-popularity-contest, python3-nibabel (>= 1.1.0), python3:any (>= 3.3.2-2~), python3-numpy (>= 1:1.6), python3-scipy (>= 0.9), python3-sklearn (>= 0.12.1) Recommends: python-matplotlib Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python3-nilearn_0.2.5~dfsg.1-1~nd14.04+1_all.deb Size: 685238 SHA256: c44dbee085adfab56fcbfbf6c1f47665af6fd05aceb20aebfaa0d7465eea65eb SHA1: a6d967748befc9a05af6fbd3a9838afac2dc4fb0 MD5sum: e897612bf3bb824aaeb0289859073b7c Description: fast and easy statistical learning on neuroimaging data (Python 3) This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. . This package provides the Python 3 version. Package: python3-nosexcover Source: nosexcover Version: 1.0.10-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 52 Depends: neurodebian-popularity-contest, python3-coverage, python3-nose, python3:any (>= 3.3.2-2~), python-nose, python-coverage (>= 3.4) Homepage: http://pypi.python.org/pypi/nosexcover Priority: extra Section: python Filename: pool/main/n/nosexcover/python3-nosexcover_1.0.10-2~nd14.04+1_all.deb Size: 5190 SHA256: ec5797bfbbb38a2fd876dba8ae84283f67241da2c3e556e304c23a77f77845df SHA1: af0de88db9af2a743a7c6fac7099ad5eb0da11f7 MD5sum: cd2819a0290d34d8d1e4db6474e2d9fb Description: Add Cobertura-style XML coverage report to nose A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml. . It will honor all the options you pass to the Nose coverage plugin, especially --cover-package. Package: python3-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1115 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-jdcal Recommends: python3-pytest, python3-pil, python3-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0~b2-1~nd14.04+1_all.deb Size: 190148 SHA256: fde43ee0bc57973ed26742d30d0cf5b1afb96c75dfc77e8b310ef1a639f97ba3 SHA1: 94781407d5fbe3630d81ae0779d03b080210ea3a MD5sum: 162cda742a0df264ecb31c12a2cc20e0 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24174 Depends: neurodebian-popularity-contest, python3-tz, python3:any (>= 3.3.2-2~), python3-dateutil, python3-numpy (>= 1:1.7~), python3-pandas-lib (>= 0.18.1-1~nd14.04+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.18.1-1~nd14.04+1_all.deb Size: 2524926 SHA256: 987b81ef49a5b74e7f8dbbf4b1d7f4994bfae5b333ed3ffcbf482f92f0675892 SHA1: e3b55eb16705c59357df7f869a87f3f65f3e7715 MD5sum: 0a5dc35ad1dccdbb250aacb3c33cb3b4 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: 0.4.1+git34-ga5b54c2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 792 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-six Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1+git34-ga5b54c2-1~nd14.04+1_all.deb Size: 169116 SHA256: b1e81ede6f6e54fd7289cbfb82b5d270a2ffac15f3623483385ba6d309a5a150 SHA1: a012cb62af233bd3c6a65be606b56e9f0c87cfcc MD5sum: a44028b99331ec59ec43adccd71d8bbd Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-py Source: python-py Version: 1.4.30-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.30-1~nd14.04+1_all.deb Size: 66732 SHA256: e4dcfe9e8309d67391f594dda9d7269daafc070875fe12b73024f8ed01380fbd SHA1: 094aa133c0e1a436c886640ebb23027d7156c562 MD5sum: 64d7b6a21473e75644ae095e83d922e9 Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pydotplus Source: python-pydotplus Version: 2.0.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, graphviz, python3-pyparsing (>= 2.0.1), python3:any (>= 3.3.2-2~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python3-pydotplus_2.0.2-1~nd14.04+1_all.deb Size: 20328 SHA256: f878b5238169859cdfca8f65be40ae18381ba955417d26ee2f9817d559ce616b SHA1: ab8151f6d6dc0ba917068caf83dc90953f3db4b7 MD5sum: a3b03af3de91f24f3694bf839962a4d5 Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-pyld Source: python-pyld Version: 0.6.8-1~nd0~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/digitalbazaar/pyld/ Priority: extra Section: python Filename: pool/main/p/python-pyld/python3-pyld_0.6.8-1~nd0~nd14.04+1_all.deb Size: 37282 SHA256: a82f7f001832fda80a0dd4cbfff9bf648da1817eb2ff71cccb27fddc3f578fef SHA1: 3d90b6d8f3c43d8b3daa4e4faae43edbf00e64f8 MD5sum: 4f327db93300982873fd5480b1e26841 Description: implementation of the JSON-LD API This library is an implementation of the JSON-LD specification in Python. . This package provides the Python 3.x module. Package: python3-pytest Source: pytest Version: 2.7.2-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3:any (>= 3.3.2-2~), python3 Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_2.7.2-2~nd14.04+1_all.deb Size: 102354 SHA256: 7d9fb489c914e606248a0294617b538a5193215ecf854ad29f08f28a65b97b68 SHA1: b3c50c08769a54606316afd8ec30a8c563c5a82a MD5sum: 26b41695fda6c1ec4c738f37d4570110 Description: Simple, powerful testing in Python3 This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 3 module and the py3.test script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python3-pytest, python3-werkzeug (>= 0.10), python3:any (>= 3.3.2-2~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python3-pytest-localserver_0.3.4-2~nd14.04+1_all.deb Size: 19282 SHA256: f04709d1c2db63f580e469b1f85733085237f906a06df554696474abd2df6f35 SHA1: 956eca0fd74095f7bf25e43f4dad4004e1bdd606 MD5sum: bb5531e1156ea9242f6270db14158e07 Description: py.test plugin to test server connections locally (Python 3) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 3. Package: python3-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pytest, python3-tornado Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python3-pytest-tornado_0.4.4-1~nd14.04+1_all.deb Size: 5738 SHA256: ed4ef503575a9ddc8f97b3d71b5b187de160ed49dd9c0a191fc2816a3ea31ef3 SHA1: 4dd119a69a7f70acfa2924f149ac973a10c9b35a MD5sum: 085c9055f034291d1ce05eec7de6655e Description: py.test plugin to test Tornado applications (Python 3) pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 3 code. Package: python3-seaborn Source: seaborn Version: 0.7.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 787 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-pandas, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.7.1-2~nd14.04+1_all.deb Size: 128358 SHA256: 9d1ded41861f9575280fde9c262d252cac64f7e5966b5be46a7085f256aa1e38 SHA1: ad6db9bde203f0735808ad33ddf7e63d5ad8903e MD5sum: df1c89ec24a36ad3a1e773ce3e174a2c Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 3 version of the package. Package: python3-setuptools-scm Source: setuptools-scm Version: 1.8.0-1~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 70 Depends: neurodebian-popularity-contest Homepage: https://github.com/pypa/setuptools_scm Priority: optional Section: python Filename: pool/main/s/setuptools-scm/python3-setuptools-scm_1.8.0-1~bpo8+1~nd14.04+1_all.deb Size: 10198 SHA256: ff11bd9f5b7c1d7d2e2eed7f9219d3ded1d3d8d73d01e08637362b6c7e35a84f SHA1: 27fcdd8880354be354775a704569bcc0f80a5d17 MD5sum: e63ae3aa2d57a735ac152d987a263b4e Description: blessed package to manage your versions by scm tags for Python 3 setuptools_scm handles managing your Python package versions in scm metadata. It also handles file finders for the suppertes scm's. . This package installs the library for Python 3. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd14.04+1_all.deb Size: 11092 SHA256: 79a6de23973f24df722d22b027db5db5b132861197a2ca85de60db65a4045cb9 SHA1: a8ae88a5d47c0725e8e7db7f9485915ab5594566 MD5sum: 54c44c9fe9707b2f852bda2e5fed9373 Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-skimage Source: skimage Version: 0.10.1-2~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15115 Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-six (>= 1.3.0), python3-skimage-lib (>= 0.10.1-2~nd14.04+1), python3:any (>= 3.3.2-2~) Recommends: python3-imaging, python3-matplotlib (>= 1.0), python3-nose, python3-pil Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.10.1-2~nd14.04+1_all.deb Size: 11919718 SHA256: 1d1b5c2fbf5fef5eb25d8d619bac87cfcb6362a1c97dbd10fae204f3acbeb3f4 SHA1: ca840ff46b54b7653bfbc18b965e09f2cfe9dd97 MD5sum: 42a0247cf46cf44a61b843f8c6c13542 Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-sklearn Source: scikit-learn Version: 0.18.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6602 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.18.1-1~nd14.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.18.1-1~nd14.04+1_all.deb Size: 1391530 SHA256: c7191c71499ddd2b813e5d1c3b7452374baf4c7434de19675b642479d8ed14d7 SHA1: 642942b4d598e13ceea3085a87642864f24e7a2a MD5sum: a37e84e7c4861289b90d6a9509dda710 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-smmap Source: python-smmap Version: 2.0.1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 117 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-nose Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python3-smmap_2.0.1-1~nd14.04+1_all.deb Size: 20190 SHA256: f0fee18045389d77aa60ee9d5cd2809a81fc078b88183430ad78465b7d393045 SHA1: 7ea43f9a13c60b287083ca55b45277db4d66b2c2 MD5sum: c7b11ec8b0c8d259b36d0f0d5d8eb3b7 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 3. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3:any (>= 3.3.2-2~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd14.04+1_all.deb Size: 117200 SHA256: 16e1aaa6f2ea3e37894d69d01a1b30aa08b677a195343faf5f359d3c7adbea0f SHA1: e9a95bac6f5e7264d3035deb962fe65dfe02d031 MD5sum: abb571938ace7e00ea171c003e50a9ad Description: sphinx theme from readthedocs.org (Python 3) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 3 version of the package. Package: python3-tqdm Source: tqdm Version: 4.11.2-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 204 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3 Homepage: https://github.com/tqdm/tqdm Priority: optional Section: python Filename: pool/main/t/tqdm/python3-tqdm_4.11.2-1~nd14.04+1_all.deb Size: 50100 SHA256: 05cb624292828b6f890b22e63160ac8960ed0ef29533da7b993bc7e9596d1ca3 SHA1: 7c5f5a3752446759352e6946b0e0e25cbff0c85e MD5sum: 744167a6eeb6a49979e3ed85e256e13c Description: fast, extensible progress bar for Python 3 and CLI tool tqdm (read taqadum, تقدّم) means “progress” in Arabic. tqdm instantly makes your loops show a smart progress meter, just by wrapping any iterable with "tqdm(iterable)". . This package contains the Python 3 version of tqdm and its command-line tool. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-six (>= 1.6.1) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python3-w3lib_1.11.0-1~nd14.04+1_all.deb Size: 14190 SHA256: 008f9ec2dd25186b977ab66c67873429efcf26bbc5ffaa02650ab0ed4c103a63 SHA1: 775d95cf272476a5deaa8eef7c1941e362c784a5 MD5sum: 0562a201189207e45c218e5a5465deb2 Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: python3-werkzeug Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libjs-jquery Recommends: python3-simplejson | python3, python3-openssl, python3-pyinotify Suggests: ipython3, python3-pkg-resources, python3-lxml, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python3-werkzeug_0.10.4+dfsg1-1~nd14.04+1_all.deb Size: 163216 SHA256: b685e053e4c5536d78e641e5b26441a9938a61038832b9d616215ddd4082b56b SHA1: 4787e0c8be6967ba696d4b011edd2562cbde87cb MD5sum: c02d0f4c7f7e88cc1acde12249702472 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 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+nd14.04+1_all.deb Size: 9749152 SHA256: c83baf314478407e2f1b908e55554b5645b4a1d52f9ef5be18864a6ec74c454b SHA1: 993dd179e97b25766a9dd6b1d5884041448089a3 MD5sum: d92e890135a7c0c8eb5f4102b380b07c Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 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+nd14.04+1_all.deb Size: 45484386 SHA256: 182e2818ac165f6a04ef610a17226e4019e76b6403242ce5106dc8084088f456 SHA1: 4ede6932c3e3b32e11bd0e1360522b3cda6e69e2 MD5sum: dd2edf6746682da9d77ea73d1ee36418 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 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+nd14.04+1_all.deb Size: 8935290 SHA256: 5742ed7248b597e91212ca03e53541e520bbeccc2d59f865b278b7c94362661e SHA1: 32542240cefbb5d936731db01ffc3175348bc80e MD5sum: 511c71c1ed452c9f1c5dd547eaade5c8 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: spykeviewer Version: 0.4.4-1~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1975 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_0.4.4-1~nd14.04+1_all.deb Size: 1291946 SHA256: 60a2857f96c3cd0e6f58d20a188950adf7574b8d5289daf8ba2d7dabe63f58dc SHA1: 69a899c9566acd0b4a3babe34e37a5173d046249 MD5sum: 777bf20e134ee592f75d0ef5c1d63a1f 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+nd14.04+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+nd14.04+1_all.deb Size: 22678 SHA256: ea800adb74820759f1c8041031b4b396c15b127a50f03a44c9e7e374649c351e SHA1: 0b16001f8fc76a1fadef374d9f61187cc11edfcf MD5sum: 3ece230b8a5225d2691618b7b10e78ba 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+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 358 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 85950 SHA256: 9a51b163a417b1a421415111ce4ddedea08a840e943a7a144f782b37944d8699 SHA1: 77a25da70008038d7ccaa99042ef1b0fe2a04229 MD5sum: f54d2b8e28fcffe650211599731dab19 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