Package: eeglab11-sampledata
Source: eeglab11
Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 8109
Depends: neurodebian-popularity-contest
Priority: extra
Section: science
Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 7224862
SHA256: b676b82109d135052588444785b36d65fe3e96cd7199cbbb0bd7c2c07d3cd801
SHA1: f9190f6dbe6d6596884363f4aeadd7181991eb43
MD5sum: 06ebb1802f177f2a117f1d51a2213ec5
Description: sample EEG data for EEGLAB tutorials
 EEGLAB is sofwware for processing continuous or event-related EEG or other
 physiological data.
 .
 This package provide some tutorial data files shipped with the EEGLAB
 distribution.

Package: fail2ban
Version: 0.8.11-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 525
Depends: neurodebian-popularity-contest, python:any (>= 2.7.1-0ubuntu2), lsb-base (>= 2.0-7)
Recommends: iptables, whois, python-pyinotify
Suggests: python-gamin, mailx, system-log-daemon
Homepage: http://www.fail2ban.org
Priority: optional
Section: net
Filename: pool/main/f/fail2ban/fail2ban_0.8.11-1~nd13.10+1_all.deb
Size: 176912
SHA256: 8c211a9afaaf4847a4dd50b72622a5c5805f67b19162007df0a746c082617d0c
SHA1: b401bf0e26bb45cf9f4721410c8d4c35fc5f2383
MD5sum: 4ff6bd1b562e28c47175467a8fe53d46
Description: ban hosts that cause multiple authentication errors
 Fail2ban monitors log files (e.g. /var/log/auth.log,
 /var/log/apache/access.log) and temporarily or persistently bans
 failure-prone addresses by updating existing firewall rules.  Fail2ban allows
 easy specification of different actions to be taken such as to ban an
 IP using iptables or hostsdeny rules, or simply to send a
 notification email.
 .
 By default, it comes with filter expressions for various services
 (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be
 easily extended for monitoring any other text file.  All filters and
 actions are given in the config files, thus fail2ban can be adopted
 to be used with a variety of files and firewalls.

Package: fslview-doc
Source: fslview
Version: 4.0.1-2~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 2874
Depends: neurodebian-popularity-contest
Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview
Priority: optional
Section: doc
Filename: pool/main/f/fslview/fslview-doc_4.0.1-2~nd13.04+1+nd13.10+1_all.deb
Size: 2346584
SHA256: d18c868829872ad3b67c0902b9dba50a49c1b221a498c79efda662247520d444
SHA1: 0eee7201a822e7f6e330c233f732e29df7e2cfa1
MD5sum: 1fbf262f0226c131b9096afe8705b64b
Description: Documentation for FSLView
 This package provides the online documentation for FSLView.
 .
 FSLView is part of FSL.

Package: incf-nidash-oneclick-clients
Source: incf-nidash-oneclick
Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 28
Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2
Homepage: http://xnat.incf.org/
Priority: extra
Section: science
Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 9792
SHA256: 0b9a6311f3505e3617a06a6c9c484f2d75b0c5d72c8399f677eda471fc8d0acd
SHA1: 68241f8405acc62727278602c524900998fa8dc4
MD5sum: 27174485f0fac376de0ebe388d427929
Description: utility for pushing DICOM data to the INCF datasharing server
 A command line utility for anonymizing and sending DICOM data to the XNAT
 image database at the International Neuroinformatics Coordinating Facility
 (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH)
 task force.

Package: ipython1x
Version: 1.1.0+git7-gf5891e9-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 11748
Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2)
Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib
Suggests: ipython1x-doc, python-gobject, python-gtk2, python-numpy, python-profiler
Conflicts: ipython-common, python2.3-ipython, python2.4-ipython
Replaces: ipython-common, python2.3-ipython, python2.4-ipython
Homepage: http://ipython.org/
Priority: optional
Section: python
Filename: pool/main/i/ipython1x/ipython1x_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb
Size: 4486488
SHA256: 6016a44c2c4ebb56d8df6ce5cc15cc7c12ab6d093667f1910829fc12ca964581
SHA1: 7a208528c1a006209745efb2e691c3b1b6770b0a
MD5sum: 313e52e500fd07fe87d6e12893fa7fde
Description: enhanced interactive Python shell
 IPython can be used as a replacement for the standard Python shell,
 or it can be used as a complete working environment for scientific
 computing (like Matlab or Mathematica) when paired with the standard
 Python scientific and numerical tools. It supports dynamic object
 introspections, numbered input/output prompts, a macro system,
 session logging, session restoring, complete system shell access,
 verbose and colored traceback reports, auto-parentheses, auto-quoting,
 and is embeddable in other Python programs.
 .
 This is a non-official, custom build of IPython post 0.11 with
 notebooks support.  It provides IPython1X module thus not
 conflicting with system-wide installed IPython

Package: ipython1x-doc
Source: ipython1x
Version: 1.1.0+git7-gf5891e9-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 10391
Depends: neurodebian-popularity-contest, libjs-jquery, ipython1x
Homepage: http://ipython.org/
Priority: optional
Section: doc
Filename: pool/main/i/ipython1x/ipython1x-doc_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb
Size: 4192434
SHA256: 6c1ed43bf785fc0278365207e66311c6cace48f4631178de5fcdc15fea6431cf
SHA1: bd3d87ffc7b305c9db0ca716ad99fdc3c9949ede
MD5sum: 120527fda1c679b4b209ed795f3c3a52
Description: enhanced interactive Python shell
 IPython can be used as a replacement for the standard Python shell,
 or it can be used as a complete working environment for scientific
 computing (like Matlab or Mathematica) when paired with the standard
 Python scientific and numerical tools. It supports dynamic object
 introspections, numbered input/output prompts, a macro system,
 session logging, session restoring, complete system shell access,
 verbose and colored traceback reports, auto-parentheses, auto-quoting,
 and is embeddable in other Python programs.
 .
 This package contains the documentation.
 .
 This is a non-official, custom build of IPython post 0.11 with
 workbooks support.  It provides IPython1X module thus not
 conflicting with system-wide installed IPython

Package: ipython1x-notebook
Source: ipython1x
Version: 1.1.0+git7-gf5891e9-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1
Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~)
Homepage: http://ipython.org/
Priority: extra
Section: python
Filename: pool/main/i/ipython1x/ipython1x-notebook_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb
Size: 908
SHA256: 937c26f74dc38685ccda4a8278e7953f3b6c80aaebd36947fd876785a6429e68
SHA1: 34d85abfe2a419d600769382228b62f121a76b9d
MD5sum: af008fba904dd966354b267c7819efb8
Description: enhanced interactive Python shell -- notebook dummy package
 This is a dummy package depending on ipython1x which ships
 notebook functionality inside.  It is made so to stay in line to
 modularization of official ipython package in Debian.  There is no
 real good reason to install this package.

Package: ipython1x-parallel
Source: ipython1x
Version: 1.1.0+git7-gf5891e9-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1
Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~)
Homepage: http://ipython.org/
Priority: extra
Section: oldlibs
Filename: pool/main/i/ipython1x/ipython1x-parallel_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb
Size: 836
SHA256: d031b9d628624c792764afb15e2e0c0f4f663064bef7b0045edb641106d09310
SHA1: e894ddc3eb3662df68d481f510b7a8251f29be93
MD5sum: 8a22a6f641780b0b77f58a614c4d26f0
Description: enhanced interactive Python shell
 This is a transitional package and can be safely removed
 after the installation is complete.

Package: ipython1x-qtconsole
Source: ipython1x
Version: 1.1.0+git7-gf5891e9-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1
Depends: neurodebian-popularity-contest, ipython1x (>= 0.13.1~git33-gcfc5692-2~)
Homepage: http://ipython.org/
Priority: extra
Section: python
Filename: pool/main/i/ipython1x/ipython1x-qtconsole_1.1.0+git7-gf5891e9-1~nd13.10+1_all.deb
Size: 924
SHA256: 71f4ce8327f6abb548302e1b70ed8d1ea0c824b0bee5f6b65b8e7d0b19c678a4
SHA1: 89622b1042ff646e64e3334bebb09e4418c144ec
MD5sum: 7aefa70e0eeab5e8034b8d0230e5551c
Description: enhanced interactive Python shell -- notebook dummy package
 This is a dummy package depending on ipython1x which ships
 qt console functionality inside.  It is made so to stay in line to
 modularization of the official ipython package in Debian.  There is no
 real good reason to install this package.

Package: mricron-data
Source: mricron
Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 1678
Depends: neurodebian-popularity-contest
Homepage: http://www.cabiatl.com/mricro/mricron/index.html
Priority: extra
Section: science
Filename: pool/main/m/mricron/mricron-data_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 1664274
SHA256: 68ce273dcde27c573053b0978397336aee2bd4bd411278f9950e11a9aac27989
SHA1: 3e484323149fadfcff8ba1c124dc23cb188c9cf6
MD5sum: 895c3045ff8a360f730cb00692214f7f
Description: data files for MRIcron
 This is a GUI-based visualization and analysis tool for (functional) magnetic
 resonance imaging. MRIcron can be used to create 2D or 3D renderings of
 statistical overlay maps on brain anatomy images. Moreover, it aids drawing
 anatomical regions-of-interest (ROI), or lesion mapping, as well as basic
 analysis of functional timeseries (e.g. creating plots of peristimulus
 signal-change).
 .
 This package provides data files for MRIcron, such as brain atlases, anatomy,
 and color schemes.

Package: mricron-doc
Source: mricron
Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 980
Depends: neurodebian-popularity-contest
Homepage: http://www.cabiatl.com/mricro/mricron/index.html
Priority: extra
Section: doc
Filename: pool/main/m/mricron/mricron-doc_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 735992
SHA256: e5a580a7bae121b13d1e22d622c6de9466ca7e01fe5abc460fe3285906c721f5
SHA1: f39199a65bb18cded064d3123319184a4c9e6878
MD5sum: 92dbcb21cb1674db34d549b65a2c61d7
Description: data files for MRIcron
 This is a GUI-based visualization and analysis tool for (functional) magnetic
 resonance imaging. MRIcron can be used to create 2D or 3D renderings of
 statistical overlay maps on brain anatomy images. Moreover, it aids drawing
 anatomical regions-of-interest (ROI), or lesion mapping, as well as basic
 analysis of functional timeseries (e.g. creating plots of peristimulus
 signal-change).
 .
 This package provides documentation for MRIcron in HTML format.

Package: mrtrix-doc
Source: mrtrix
Version: 0.2.11-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 3488
Depends: neurodebian-popularity-contest
Homepage: http://www.brain.org.au/software/mrtrix
Priority: extra
Section: doc
Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.11-1~nd13.04+1+nd13.10+1_all.deb
Size: 3315566
SHA256: 71442f92e14e7d4a7ede19192c4f90b7b499f2d970d23f243034a52a035cb1e9
SHA1: 93ff9dbf790cd956cdab14959d4a968a5145ba5a
MD5sum: d62cbb6f62b76dbb3c632b95ec797787
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: neurodebian-desktop
Source: neurodebian
Version: 0.32~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 142
Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest
Homepage: http://neuro.debian.net
Priority: optional
Section: science
Filename: pool/main/n/neurodebian/neurodebian-desktop_0.32~nd13.10+1_all.deb
Size: 115540
SHA256: 9ba5d4dabb6e93f31272b3b486f15ac6b076af64cf23bf39344807b8dfed0d4c
SHA1: 28c84332645d7e4341bc5337e9ea93b556a492d6
MD5sum: d68aaaccaf699b6dd38e1882de06e1e5
Description: neuroscience research environment
 This package contains NeuroDebian artwork (icons, background image)
 and a NeuroDebian menu featuring most popular neuroscience tools
 automatically installed upon initial invocation.

Package: neurodebian-dev
Source: neurodebian
Version: 0.32~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 6842
Depends: devscripts, cowbuilder, neurodebian-keyring
Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils
Suggests: virtualbox-ose, virtualbox-ose-fuse
Homepage: http://neuro.debian.net
Priority: optional
Section: science
Filename: pool/main/n/neurodebian/neurodebian-dev_0.32~nd13.10+1_all.deb
Size: 6433068
SHA256: aa1c7d670d5242fb0a926b76a4da98688b0241afbd0930920ed750c3fee6db63
SHA1: 0db76d411ca7c35145284885f1beca74c6763675
MD5sum: feb4c2acd0742deb03aa350b145ad9b2
Description: NeuroDebian development tools
 neuro.debian.net sphinx website sources and development tools used by
 NeuroDebian to provide backports for a range of Debian/Ubuntu
 releases.

Package: neurodebian-guest-additions
Source: neurodebian
Version: 0.32~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 107
Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms
Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity
Recommends: chromium-browser, update-manager-gnome, update-notifier
Homepage: http://neuro.debian.net
Priority: optional
Section: science
Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.32~nd13.10+1_all.deb
Size: 15362
SHA256: 87323f095aec2a104af3633b311a231531765476441b4e34dd49f40c426537cc
SHA1: 6204775b5aee5af8692750f2011b1311cb16c0d5
MD5sum: 3473a9e49831da14507f033d87a05481
Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX)
 This package configures a Debian installation as a guest operating system
 in a VirtualBox-based virtual machine for NeuroDebian.
 .
 DO NOT install this package unless you know what you are doing! For example,
 installation of this package relaxes several security mechanisms.

Package: neurodebian-keyring
Source: neurodebian
Version: 0.32~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 8
Homepage: http://neuro.debian.net
Priority: optional
Section: science
Filename: pool/main/n/neurodebian/neurodebian-keyring_0.32~nd13.10+1_all.deb
Size: 7626
SHA256: 971b8c7f9c290670165b5b4480681aa056ad296d0a66d4b7f5b13699f898dcf3
SHA1: 4520e7bcbbdedcf856195ca443fef0bc0e14a99f
MD5sum: 84091b28d29885a610724d371af9321c
Description: GnuPG archive keys of the NeuroDebian archive
 The NeuroDebian project digitally signs its Release files. This package
 contains the archive keys used for that.

Package: neurodebian-popularity-contest
Source: neurodebian
Version: 0.32~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 7
Depends: popularity-contest
Homepage: http://neuro.debian.net
Priority: optional
Section: science
Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.32~nd13.10+1_all.deb
Size: 6838
SHA256: eb7c13a98d2d0e64a57475dfb1af249c082531254bcdf62b676c43f2198918c9
SHA1: a98d5388ac8f622a3e72444192feb4e72a24f744
MD5sum: cf62e0d246ae30891e4df6332e4e3ed3
Description: Helper for NeuroDebian popularity contest submissions
 This package is a complement to the generic popularity-contest
 package to enable anonymous submission of usage statistics to
 NeuroDebian in addition to the popcon submissions to the underlying
 distribution (e.g. Debian or Ubuntu) popcon server.
 .
 Your participation in popcon is important for following reasons:
  - Popular packages receive more attention from developers, bugs are
    fixed faster and updates are provided quicker.
  - Assure that we do not drop support for a previous release of Debian
    or Ubuntu while are active users.
  - User statistics could be used by upstream research software
    developers to acquire funding for continued development.
 .
 It has an effect only if you have decided to participate in the
 Popularity Contest of your distribution, i.e. Debian or Ubuntu.
 You can always enable or disable your participation in popcon by
 running 'dpkg-reconfigure popularity-contest' as root.

Package: nifti2dicom-data
Source: nifti2dicom
Version: 0.4.6-2~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
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_0.4.6-2~nd13.04+1+nd13.10+1_all.deb
Size: 615226
SHA256: 0f0a456de3bee8393c788a8e386db5850e1114f6d0888aa2962aeaca3285701f
SHA1: 1348f2d5aa245a47b7e921228df9d88801ea0037
MD5sum: 56b8ed8c1d235d57922f2fbda44bf0ed
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: 0.4.6.2+ds-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1904
Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.1-0ubuntu2)
Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6)
Suggests: ccache
Homepage: http://nuitka.net
Priority: optional
Section: python
Filename: pool/main/n/nuitka/nuitka_0.4.6.2+ds-1~nd13.10+1_all.deb
Size: 509766
SHA256: 899e9ef6f5bc3fae92f6c44b2a1fe21dea3b2f8160f5e44749b498dad0d9ea0a
SHA1: 010f177362353b9fc10962c7190205f52d83f549
MD5sum: 64fe93bc44017c8327d194d5537d15de
Description: Python compiler with full language support and CPython compatibility
 This Python compiler achieves full language compatibility and compiles Python
 code into compiled objects that are not second class at all. Instead they can
 be used in the same way as pure Python objects.

Package: opensesame
Version: 0.27.4-2~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 26639
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme
Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown
Homepage: http://www.cogsci.nl/software/opensesame
Priority: extra
Section: science
Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd13.04+1+nd13.10+1_all.deb
Size: 25359292
SHA256: 7eb6ad30eac4d0899910debe19d8f7d67bc93d31570781782b9c297f0ed84053
SHA1: 1f09336470b48636de42f67e545284e24f6b15ef
MD5sum: 076b71a8a142d25cbc32e85c9e11720f
Description: graphical experiment builder for the social sciences
 This graphical environment provides an easy to use, point-and-click interface
 for creating psychological experiments. In addition to a powerful sketchpad for
 creating visual stimuli, OpenSesame features a sampler and synthesizer for
 sound playback. For more complex tasks, OpenSesame supports Python
 scripting using the built-in editor with syntax highlighting.

Package: psychtoolbox-3-common
Source: psychtoolbox-3
Version: 3.0.11.20131017.dfsg1-2~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 49635
Depends: neurodebian-popularity-contest
Recommends: subversion
Suggests: gnuplot
Homepage: http://psychtoolbox.org
Priority: extra
Section: science
Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.11.20131017.dfsg1-2~nd13.10+1_all.deb
Size: 19937316
SHA256: 1d633396593cd68aee1f7aedfd2f627c93fe031b87bee46eca446b19e5dbbc30
SHA1: e91de726712bc8e2c5710b1afb72e7e533c053c0
MD5sum: 37b535b8bc0512f543a8b4b06df40d98
Description: toolbox for vision research -- arch/interpreter independent part
 Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and
 GNU/Octave functions for vision research. It makes it easy to
 synthesize and show accurately controlled visual and auditory stimuli
 and interact with the observer.
 .
 The Psychophysics Toolbox interfaces between Matlab or Octave and the
 computer hardware. The Psychtoolbox's core routines provide access to
 the display frame buffer and color lookup table, allow
 synchronization with the vertical retrace, support millisecond
 timing, allow access to OpenGL commands, and facilitate the
 collection of observer responses. Ancillary routines support common
 needs like color space transformations and the QUEST threshold
 seeking algorithm.
 .
 This package contains architecture independent files (such as .m scripts)

Package: python-brian
Source: brian
Version: 1.4.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 2336
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.1-1~nd13.04+1+nd13.10+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0)
Recommends: python-sympy
Suggests: python-brian-doc, python-nose, python-cherrypy
Homepage: http://www.briansimulator.org/
Priority: extra
Section: python
Filename: pool/main/b/brian/python-brian_1.4.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 549212
SHA256: 988ae070c4a1f6ff509598736733a666ccf337407b9f1b54fe51dcc41f453071
SHA1: c0d825559c7fa6cc94df99326cd0bf135b9af3d2
MD5sum: 19b10c71f6878e6e0ca5eea1637284fe
Description: simulator for spiking neural networks
 Brian is a clock-driven simulator for spiking neural networks. It is
 designed with an emphasis on flexibility and extensibility, for rapid
 development and refinement of neural models. Neuron models are
 specified by sets of user-specified differential equations, threshold
 conditions and reset conditions (given as strings). The focus is
 primarily on networks of single compartment neuron models (e.g. leaky
 integrate-and-fire or Hodgkin-Huxley type neurons). Features include:
  - a system for specifying quantities with physical dimensions
  - exact numerical integration for linear differential equations
  - Euler, Runge-Kutta and exponential Euler integration for nonlinear
    differential equations
  - synaptic connections with delays
  - short-term and long-term plasticity (spike-timing dependent plasticity)
  - a library of standard model components, including integrate-and-fire
    equations, synapses and ionic currents
  - a toolbox for automatically fitting spiking neuron models to
    electrophysiological recordings

Package: python-brian-doc
Source: brian
Version: 1.4.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 6810
Depends: neurodebian-popularity-contest, libjs-jquery
Suggests: python-brian
Homepage: http://www.briansimulator.org/
Priority: extra
Section: doc
Filename: pool/main/b/brian/python-brian-doc_1.4.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 2247326
SHA256: 02613c13a722df13156e9ae18dfaa9328810fca303950ba19a1356da2a77a3a7
SHA1: 4341f8754a618702eb2f745017fc50c57b88b2e6
MD5sum: 90d9953badd70e123284cef6b7fb2904
Description: simulator for spiking neural networks - documentation
 Brian is a clock-driven simulator for spiking neural networks.
 .
 This package provides user's manual (in HTML format), examples and
 demos.

Package: python-joblib
Source: joblib
Version: 0.7.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 182
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0)
Recommends: python-numpy, python-nose, python-simplejson
Homepage: http://packages.python.org/joblib/
Priority: optional
Section: python
Filename: pool/main/j/joblib/python-joblib_0.7.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 54902
SHA256: 8da3ca02ba5ac7b0ef34f0b086d3e687788a3ac689f9d9ee53d36ec03c720928
SHA1: 89ecf1f16e6ef9b552359f960e5a4ebe10c3a8fa
MD5sum: 896e7ee9f14eff60a67380bde75474f3
Description: tools to provide lightweight pipelining in Python
 Joblib is a set of tools to provide lightweight pipelining in
 Python. In particular, joblib offers:
  - transparent disk-caching of the output values and lazy
    re-evaluation (memoize pattern)
  - easy simple parallel computing
  - logging and tracing of the execution
 .
 Joblib is optimized to be fast and robust in particular on large,
 long-running functions and has specific optimizations for numpy arrays.

Package: python-mdp
Source: mdp
Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1495
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy
Recommends: python-scipy, python-libsvm, python-joblib, python-scikits-learn | python-sklearn, python-pp
Suggests: python-py, shogun-python-modular
Enhances: python-mvpa
Homepage: http://mdp-toolkit.sourceforge.net/
Priority: optional
Section: python
Filename: pool/main/m/mdp/python-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 478670
SHA256: dcbf8dcbd35c93951698aa8a700355c7f7df66000b6e7e4b42432fef2a273b63
SHA1: 47eb8ef49afe92e183de028ecbe170ccc8227fad
MD5sum: 3e08fab66beaacec7b7071b569c74ded
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-mpi4py-doc
Source: mpi4py
Version: 1.3.1+hg20131106-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 256
Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0)
Suggests: python-mpi4py
Homepage: http://code.google.com/p/mpi4py/
Priority: extra
Section: doc
Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.3.1+hg20131106-1~nd13.10+1_all.deb
Size: 73120
SHA256: 0b134f816eac4329b2752f7b2e16c6956ecd2ffc949074ee1c9eb390675b9e18
SHA1: 81d29c74376e92ec5c3386727d44258ffba85f8a
MD5sum: d041dee2f5707ed612450c5d7b65f545
Description: bindings of the MPI standard -- documentation
 MPI for Python (mpi4py) provides bindings of the Message Passing
 Interface (MPI) standard for the Python programming language,
 allowing any Python program to exploit multiple processors.
 .
 mpi4py is constructed on top of the MPI-1/MPI-2 specification
 and provides an object oriented interface which closely follows MPI-2
 C++ bindings.  It supports point-to-point (sends, receives) and
 collective (broadcasts, scatters, gathers) communications of any
 picklable Python object as well as optimized communications of Python
 object exposing the single-segment buffer interface (NumPy arrays,
 builtin bytes/string/array objects).
 .
 This package provides HTML rendering of the user's manual.

Package: python-neo
Source: neo
Version: 0.3.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 2485
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~)
Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore
Suggests: python-nose
Homepage: http://neuralensemble.org/trac/neo
Priority: extra
Section: python
Filename: pool/main/n/neo/python-neo_0.3.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 1441986
SHA256: ec381fea8a1c2ad6d8301f88c0ca4362cbbbab180c6e618772181f5b4055fd62
SHA1: 7ae0814b66bf4f821fbb042de12c70a6cd53b3e0
MD5sum: cfd02e2d5a37dcf504472f5f31e11f67
Description: Python IO library for electrophysiological data formats
 NEO stands for Neural Ensemble Objects and is a project to provide common
 classes and concepts for dealing with electro-physiological (in vivo
 and/or simulated) data to facilitate collaborative software/algorithm
 development. In particular Neo provides: a set a classes for data
 representation with precise definitions, an IO module with a simple API,
 documentation, and a set of examples.
 .
 NEO offers support for reading data from numerous proprietary file formats
 (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for
 various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well
 as support common file formats, such as HDF5 with Neo-structured content
 (NeoHDF5, NeoMatlab).
 .
 Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare
 replacement.

Package: python-neurosynth
Source: neurosynth
Version: 0.3-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 83
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-nibabel, python-ply
Recommends: python-nose, fsl-mni152-templates
Suggests: python-testkraut
Homepage: http://neurosynth.org
Priority: extra
Section: python
Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd13.04+1+nd13.10+1_all.deb
Size: 32584
SHA256: e38eecc0a3733f22718924755061092da20b4ce592bc1f0044cc0fcd3b5d946e
SHA1: acb8d58022eca092a686c7665b5225fca8074794
MD5sum: 3eedb70c2ed5b4a73f58c6b2981af4f0
Description: large-scale synthesis of functional neuroimaging data
 NeuroSynth is a platform for large-scale, automated synthesis of
 functional magnetic resonance imaging (fMRI) data extracted from
 published articles.  This Python module at the moment provides
 functionality for processing the database of collected terms and
 spatial coordinates to generate associated spatial statistical maps.

Package: python-nibabel
Source: nibabel
Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 4152
Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy
Recommends: python-dicom, python-fuse
Suggests: python-nibabel-doc
Provides: python2.7-nibabel
Homepage: http://nipy.sourceforge.net/nibabel
Priority: extra
Section: python
Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 1816464
SHA256: 1e268bf6e0aedbb094d99515235bca7859435018effc35b32c1ad61bc8f45576
SHA1: b446856aaabf44b569c5fb168697b97baafc6fb2
MD5sum: 9fc3310c254316621359200032f71b23
Description: Python bindings to various neuroimaging data formats
 NiBabel provides read and write access to some common medical and
 neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI,
 NIfTI1, MINC, as well as PAR/REC. The various image format classes give full
 or selective access to header (meta) information and access to the image data
 is made available via NumPy arrays.  NiBabel is the successor of PyNIfTI.
 .
 This package also provides a commandline tools:
 .
  - dicomfs - FUSE filesystem on top of a directory with DICOMs
  - nib-ls - 'ls' for neuroimaging files
  - parrec2nii - for conversion of PAR/REC to NIfTI images
Python-Version: 2.7

Package: python-nibabel-doc
Source: nibabel
Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 2446
Depends: neurodebian-popularity-contest, libjs-jquery
Homepage: http://nipy.sourceforge.net/nibabel
Priority: extra
Section: doc
Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 441902
SHA256: 024cc31c57fad25b7ece5bf111183562ed9f306c69b9c615ada8252c8ae51f5f
SHA1: 34c515cf5d1ec4eda26a1be813c65d420e3f22a0
MD5sum: 282caebc75ef0933a993491196a60143
Description: documentation for NiBabel
 NiBabel provides read and write access to some common medical and
 neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI,
 NIfTI1, MINC, as well as PAR/REC. The various image format classes give full
 or selective access to header (meta) information and access to the image data
 is made available via NumPy arrays.  NiBabel is the successor of PyNIfTI.
 .
 This package provides the documentation in HTML format.

Package: python-openpyxl
Source: openpyxl
Version: 1.7.0+ds1-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 452
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0)
Recommends: python-nose, python-pil, python-imaging
Homepage: http://bitbucket.org/ericgazoni/openpyxl/
Priority: optional
Section: python
Filename: pool/main/o/openpyxl/python-openpyxl_1.7.0+ds1-1~nd13.10+1_all.deb
Size: 91942
SHA256: 45e03738ea43ee24a77af63a0910957f19fed443bdb9fa5f0fbf8d0505002c43
SHA1: bb8bbd20152df002810b7998237cdb1ef04c7a73
MD5sum: 5dc3c2964ab771ebebbd199b4b15c60e
Description: module to read/write OpenXML xlsx/xlsm files
 Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML)
 xlsx/xlsm files.

Package: python-patsy
Source: patsy
Version: 0.2.1-2~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 542
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy
Recommends: python-pandas
Suggests: python-patsy-doc
Homepage: http://github.com/pydata/patsy
Priority: optional
Section: python
Filename: pool/main/p/patsy/python-patsy_0.2.1-2~nd13.10+1_all.deb
Size: 141566
SHA256: 129dbb8c395d3ec89e03e9a07c950a52657450af33b3a29987f9643a54ca5427
SHA1: bf09927d1ada6b8c4fa217cb8931cff0a5f27b98
MD5sum: 1e7166dbc44ab5325bf9e4c1bafe79c0
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: 0.2.1-2~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 827
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_0.2.1-2~nd13.10+1_all.deb
Size: 271938
SHA256: 961ceeb48ffbeaaff905d26aee5fc323e3f1b06cc466cd8a349f03daaf930aed
SHA1: 553e1c06cd178a1c78962fcce0903dec8d2a5e5a
MD5sum: b31d6af765cda6ad2f0ff8ff085917cd
Description: documentation and examples for patsy
 This package contains documentation and example scripts for
 python-patsy.

Package: python-pyepl-common
Source: pyepl
Version: 1.1.0+git12-g365f8e3-2~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 813
Depends: neurodebian-popularity-contest, python
Homepage: http://pyepl.sourceforge.net/
Priority: optional
Section: python
Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1_all.deb
Size: 818248
SHA256: 9ce8e6041a5deeccea8c28454166623b53d9a571d442a63bc8844c07dd698293
SHA1: 90dc97067b797c017c9da331c41ed24072f8d156
MD5sum: d3ec7da2336f2e9e5ab0cff98c32ebaf
Description: module for coding psychology experiments in Python
 PyEPL is a stimuli delivery and response registration toolkit to be
 used for generating psychology (as well as neuroscience, marketing
 research, and other) experiments.
 .
 It provides
  - presentation: both visual and auditory stimuli
  - responses registration: both manual (keyboard/joystick) and
    sound (microphone) time-stamped
  - sync-pulsing: synchronizing your behavioral task with external
    acquisition hardware
  - flexibility of encoding various experiments due to the use of
    Python as a description language
  - fast execution of critical points due to the calls to linked
    compiled libraries
 .
 This toolbox is here to be an alternative for a widely used
 commercial product E'(E-Prime)
 .
 This package provides common files such as images.

Package: python-pynn
Source: pynn
Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 763
Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0)
Recommends: python-jinja2, python-cheetah
Suggests: python-neuron, python-brian, python-csa
Homepage: http://neuralensemble.org/trac/PyNN
Priority: extra
Section: python
Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 175892
SHA256: 0490096bb6a4e6d5ed2ec0e77261346c947d46d28d86acd3bb617c35ad3f10d2
SHA1: 0573a0e1d66e53f5af548774aae5578cc3346cc3
MD5sum: 908111812c3b5221360aff3852de45a8
Description: simulator-independent specification of neuronal network models
 PyNN allows for coding a model once and run it without modification
 on any simulator that PyNN supports (currently NEURON, NEST, PCSIM
 and Brian).  PyNN translates standard cell-model names and parameter
 names into simulator-specific names.

Package: python-pyxnat
Source: pyxnat
Version: 0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 862
Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0)
Recommends: python-networkx, python-matplotlib
Homepage: http://packages.python.org/pyxnat/
Priority: extra
Section: python
Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 190426
SHA256: 5854904257cb3119ee3d4389a93ef91f6d0b09cb8761ad8202ad2871c93c79b5
SHA1: ab34bd5639fc33e6891167d65f60d00d368405b5
MD5sum: 3e607b3d81f724a53cce9d8e07b15a74
Description: Interface to access neuroimaging data on XNAT servers
 pyxnat is a simple Python library that relies on the REST API provided
 by the XNAT platform since its 1.4 version. XNAT is an extensible
 database for neuroimaging data. The main objective is to ease
 communications with an XNAT server to plug-in external tools or Python
 scripts to process the data. It features:
 .
  - resources browsing capabilities
  - read and write access to resources
  - complex searches
  - disk-caching of requested files and resources

Package: python-scikits-learn
Source: scikit-learn
Version: 0.14.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 35
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_0.14.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 33394
SHA256: c5c4921959294695cc1786c21f6a4221e9643c4a37dd2eb00c4fde018b09c98e
SHA1: 69e189ae57b2d9d71d6163d3cad67ac43cc41b07
MD5sum: 3d82217021f148a186e7a70eabaea5ad
Description: transitional compatibility package for scikits.learn -> sklearn migration
 Provides old namespace (scikits.learn) and could be removed if
 dependent code migrated to use sklearn for clarity of the namespace.

Package: python-scikits.statsmodels
Source: statsmodels
Version: 0.5.0-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 9
Depends: neurodebian-popularity-contest, python-statsmodels
Homepage: http://statsmodels.sourceforge.net/
Priority: extra
Section: oldlibs
Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb
Size: 5690
SHA256: 32c363d5c9c614e8dc79f3e4416b5f5f130a1a14bc01a655340725b9debc7732
SHA1: 31cc26d464f24154400ac5af0077098c538e3903
MD5sum: a0418afa93e68377deca41d04268bd03
Description: transitional compatibility package for statsmodels migration
 Provides old namespace (scikits.statsmodels) and could be removed if
 dependent code migrated to use statsmodels for clarity of the namespace.

Package: python-skimage
Source: skimage
Version: 0.9.3-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 6267
Depends: neurodebian-popularity-contest, libfreeimage3, python-numpy, python-scipy (>= 0.10), python-skimage-lib (>= 0.9.3-1~nd13.10+1), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2)
Recommends: python-imaging, python-pil, python-matplotlib (>= 1.0), python-nose, python-qt4
Suggests: python-opencv, python-skimage-doc
Homepage: http://scikit-image.org
Priority: optional
Section: python
Filename: pool/main/s/skimage/python-skimage_0.9.3-1~nd13.10+1_all.deb
Size: 4538212
SHA256: 38ce12bcda96fb048603a041bf97348639c933fe350844078531e0b0b0325e8a
SHA1: 1326d280a0d3bd379aeabf6d2fea67d8384b150e
MD5sum: ffd316ff9cf30d8cd16d769688403f46
Description: Python modules for image processing
 scikit-image is a collection of image processing algorithms for
 Python.  It performs tasks such as image loading, filtering,
 morphology, segmentation, color conversions, and transformations.
 .
 This package provides the Python 2 module.

Package: python-skimage-doc
Source: skimage
Version: 0.9.3-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 17726
Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0)
Suggests: python-skimage
Homepage: http://scikit-image.org
Priority: optional
Section: doc
Filename: pool/main/s/skimage/python-skimage-doc_0.9.3-1~nd13.10+1_all.deb
Size: 14620090
SHA256: 01aafb0fe1ee85f69bd722c23a4b72f003261bd8511eacfc811590bb5249b116
SHA1: f049087ae92a499a52955ad443bbe99b6e0344af
MD5sum: 1f9af2c36987770895b8dc2ca67b25ac
Description: Documentation and examples for scikit-image
 This package contains documentation and example scripts for
 python-skimage.

Package: python-sklearn
Source: scikit-learn
Version: 0.14.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 3549
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn-lib (>= 0.14.1-1~nd13.04+1+nd13.10+1), python-joblib (>= 0.4.5)
Recommends: python-nose, python-matplotlib
Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython
Enhances: python-mdp, python-mvpa2
Breaks: python-scikits-learn (<< 0.9~)
Replaces: python-scikits-learn (<< 0.9~)
Provides: python2.7-sklearn
Homepage: http://scikit-learn.sourceforge.net
Priority: optional
Section: python
Filename: pool/main/s/scikit-learn/python-sklearn_0.14.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 1103724
SHA256: e9dd3918afc487965fa705fcf6833913aeab546ec8360f0f7dd40f476e96e382
SHA1: 907583b96f7ca554661469323cdd9d604f0a31be
MD5sum: 682700752ca3096fbfef096744e44581
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: 0.14.1-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 579
Depends: neurodebian-popularity-contest, libjs-jquery
Suggests: python-sklearn
Conflicts: python-scikits-learn-doc
Replaces: python-scikits-learn-doc
Homepage: http://scikit-learn.sourceforge.net
Priority: optional
Section: doc
Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.14.1-1~nd13.04+1+nd13.10+1_all.deb
Size: 190084
SHA256: a8ff6e017748e6a98c998dc6f9967700c97ad590da834c76fe4f1f340340bd35
SHA1: d84325dd92092e8afc55efd278b283734b37de2a
MD5sum: e613e6e4a1d3fd2bb50f2d8d7c0ac6db
Description: documentation and examples for scikit-learn
 This package contains documentation and example scripts for
 python-sklearn.

Package: python-spyderlib
Source: spyder
Version: 2.2.5+dfsg-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 4009
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), libjs-sphinxdoc (>= 1.0), libjs-jquery, libjs-mathjax, python-qt4
Recommends: ipython-qtconsole, pep8, pyflakes (>= 0.5.0), pylint, python-matplotlib, python-numpy, python-psutil (>= 0.3.0), python-rope, python-scipy, python-sphinx
Suggests: tortoisehg, gitk
Breaks: spyder (<< 2.0.12-1)
Replaces: spyder (<< 2.0.12-1)
Provides: python2.7-spyderlib
Homepage: http://code.google.com/p/spyderlib/
Priority: extra
Section: python
Filename: pool/main/s/spyder/python-spyderlib_2.2.5+dfsg-1~nd13.10+1_all.deb
Size: 1847912
SHA256: 5901bcb679c7ab73afcc6a5ba4e91c7d8e5f0b26e89da7dfc808ebd2efa321dc
SHA1: fd5f1fc3a2f2efdd2910acf381322602cd2ae029
MD5sum: 50f033bac3cde622865ed80cb0137101
Description: python IDE for scientists
 Originally written to design Spyder (the Scientific PYthon
 Development EnviRonment), the spyderlib Python library provides
 ready-to-use pure-Python widgets: source code editor with syntax
 highlighting and code introspection/analysis features, NumPy array
 editor, dictionary editor, Python console, etc. It's based on the Qt
 Python binding module PyQt4 (and is compatible with PySide since
 v2.2).

Package: python-spykeutils
Source: spykeutils
Version: 0.4.0-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 2018
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_0.4.0-1~nd13.04+1+nd13.10+1_all.deb
Size: 401644
SHA256: 602a18a5f0d14a20169f4ee7aed21ce25645fcfe8d8668731c99a71b25f1b2b2
SHA1: 6a95e964f341f0950776a46e9abad5cc30a36c82
MD5sum: b1e989f4caccc9d2ef07a86391511353
Description: utilities for analyzing electrophysiological data
 spykeutils is a Python library for analyzing and plotting data from
 neurophysiological recordings. It can be used by itself or in
 conjunction with Spyke Viewer, a multi-platform GUI application for
 navigating electrophysiological datasets.

Package: python-statsmodels
Source: statsmodels
Version: 0.5.0-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 20496
Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd13.04+1+nd13.10+1), python-patsy
Recommends: python-pandas, python-matplotlib, python-nose, python-joblib
Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4)
Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4)
Provides: python2.7-statsmodels
Homepage: http://statsmodels.sourceforge.net/
Priority: extra
Section: python
Filename: pool/main/s/statsmodels/python-statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb
Size: 4690538
SHA256: 38a545728cb1df2d44d1fc3579354ddfe8b89c5f207ece0cd3b2b68175730d29
SHA1: 95347b8acb0ef160eea8eb223ef7ec8d4d46f0ed
MD5sum: d7b2743076ae1cc2f1aadfa920e3b4ec
Description: Python module for the estimation of statistical models
 statsmodels Python module provides classes and functions for the
 estimation of several categories of statistical models. These
 currently include linear regression models, OLS, GLS, WLS and GLS
 with AR(p) errors, generalized linear models for six distribution
 families and M-estimators for robust linear models. An extensive list
 of result statistics are available for each estimation problem.

Package: python-statsmodels-doc
Source: statsmodels
Version: 0.5.0-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 31202
Depends: neurodebian-popularity-contest, libjs-jquery
Suggests: python-statsmodels
Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc
Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc
Homepage: http://statsmodels.sourceforge.net/
Priority: extra
Section: doc
Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.5.0-1~nd13.04+1+nd13.10+1_all.deb
Size: 9240594
SHA256: afc8c22ea8bad165091cb11c971caaf688a39748726afc7430379266cbd8220a
SHA1: d7f880340bf05c73be55fe618e1ce0706681724a
MD5sum: 8a8961c09b31992954ac76ce98daf033
Description: documentation and examples for statsmodels
 This package contains HTML documentation and example scripts for
 python-statsmodels.

Package: python-surfer
Source: pysurfer
Version: 0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 93
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython
Recommends: mencoder
Homepage: http://pysurfer.github.com
Priority: extra
Section: python
Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 28156
SHA256: 50ddfd6a338724eef65c70fdf5accda6cb4138a4a880812d575a3a24c82e0f4e
SHA1: 3dd5e53ea0d12307cf09854ee4857f26557ed6e5
MD5sum: 5e15b6ff76d04fb48b8d45537ef67a97
Description: visualize Freesurfer's data in Python
 This is a Python package for visualization and interaction with cortical
 surface representations of neuroimaging data from Freesurfer. It
 extends Mayavi’s powerful visualization engine with a high-level interface for
 working with MRI and MEG data.
 .
 PySurfer offers both a command-line interface designed to broadly replicate
 Freesurfer’s Tksurfer program as well as a Python library for writing scripts
 to efficiently explore complex datasets.
Python-Version: 2.7

Package: python3-mdp
Source: mdp
Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1457
Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy
Homepage: http://mdp-toolkit.sourceforge.net/
Priority: optional
Section: python
Filename: pool/main/m/mdp/python3-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 472732
SHA256: 34d326fd987ac56b05616b45fdf1a1feee5c3cee4851ed34e871d9a8ef1ddf49
SHA1: 0191963e9dfae4b7b3dfe58d707a3114399d19f9
MD5sum: 2601097ca9fcd09b10342a784917d739
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-patsy
Source: patsy
Version: 0.2.1-2~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 535
Depends: neurodebian-popularity-contest, python3-numpy, python3:any (>= 3.3.2-2~)
Recommends: python3-pandas
Suggests: python-patsy-doc
Homepage: http://github.com/pydata/patsy
Priority: optional
Section: python
Filename: pool/main/p/patsy/python3-patsy_0.2.1-2~nd13.10+1_all.deb
Size: 140384
SHA256: 240fefb22e743b5a444acad849e63ae4701920fb3c7fa6cba885e0f9744ec338
SHA1: b0dbd969743a2cc6d89044af4e6575fc21f0cdef
MD5sum: 3350a251e0975db1c5b799599cf525c1
Description: statistical models in Python using symbolic formulas
 patsy is a Python library for describing statistical models
 (especially linear models, or models that have a linear component)
 and building design matrices.
 .
 This package contains the Python 3 version.

Package: python3-skimage
Source: skimage
Version: 0.9.3-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 6161
Depends: neurodebian-popularity-contest, libfreeimage3, python3-numpy, python3-scipy (>= 0.10), python3-skimage-lib (>= 0.9.3-1~nd13.10+1), python3:any (>= 3.3.2-2~)
Recommends: python3-imaging, python3-pil, python3-matplotlib (>= 1.0), python3-nose
Suggests: python-skimage-doc
Homepage: http://scikit-image.org
Priority: optional
Section: python
Filename: pool/main/s/skimage/python3-skimage_0.9.3-1~nd13.10+1_all.deb
Size: 4529352
SHA256: 1954d095c5dda861a9a16d40bc290dd87d9c62b5a3ebffed61bca0b3940dc3be
SHA1: fec0293ba0f1d43be9dc26b2a221cc88fddb4397
MD5sum: ecd693c691939be0476ffd23dda19fa6
Description: Python 3 modules for image processing
 scikit-image is a collection of image processing algorithms for
 Python.  It performs tasks such as image loading, filtering,
 morphology, segmentation, color conversions, and transformations.
 .
 This package provides the Python 3 module.

Package: spm8-common
Source: spm8
Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 18499
Depends: neurodebian-popularity-contest
Recommends: spm8-data, spm8-doc
Priority: extra
Section: science
Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 10744052
SHA256: 05f7ef0de3af1f49c7f7dafba91b9d8f5f082bd48ad7acd365a89a105fcd6c71
SHA1: 829ef9f220b3a9595b3acdb7ada1bedcdfdbc378
MD5sum: 137a219ff42452e9439fe275cb949cc3
Description: analysis of brain imaging data sequences
 Statistical Parametric Mapping (SPM) refers to the construction and assessment
 of spatially extended statistical processes used to test hypotheses about
 functional brain imaging data. These ideas have been instantiated in software
 that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG
 and MEG data.
 .
 This package provides the platform-independent M-files.

Package: spm8-data
Source: spm8
Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 72987
Depends: neurodebian-popularity-contest
Priority: extra
Section: science
Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 52166702
SHA256: 85b2c5e9081fd7cf506defb5327413d0222f01f3b7e6fd959e5e2ccf8d83000c
SHA1: 8a53b81d37062647c56fac6117a589fb776bbac5
MD5sum: 9d6cae39f3455ec2cc5a2f3ccf8b002d
Description: data files for SPM8
 Statistical Parametric Mapping (SPM) refers to the construction and assessment
 of spatially extended statistical processes used to test hypotheses about
 functional brain imaging data. These ideas have been instantiated in software
 that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG
 and MEG data.
 .
 This package provide the data files shipped with the SPM distribution, such as
 various stereotaxic brain space templates and EEG channel setups.

Package: spm8-doc
Source: spm8
Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Team <team@neuro.debian.net>
Installed-Size: 9242
Depends: neurodebian-popularity-contest
Priority: extra
Section: doc
Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 8990912
SHA256: a35cf1eaaf17c77bc2c148da711ed2d386131f25f4ea98c326b36ee3a0867e07
SHA1: a21337c1d47d0ae2b39bcabb477ecbdf0fdff4f0
MD5sum: e7247d37c03ce8eafa3ae5e619c752a2
Description: manual for SPM8
 Statistical Parametric Mapping (SPM) refers to the construction and assessment
 of spatially extended statistical processes used to test hypotheses about
 functional brain imaging data. These ideas have been instantiated in software
 that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG
 and MEG data.
 .
 This package provides the SPM manual in PDF format.

Package: spyder
Version: 2.2.5+dfsg-1~nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 94
Depends: neurodebian-popularity-contest, python:any, python-spyderlib (= 2.2.5+dfsg-1~nd13.10+1)
Homepage: http://code.google.com/p/spyderlib/
Priority: extra
Section: devel
Filename: pool/main/s/spyder/spyder_2.2.5+dfsg-1~nd13.10+1_all.deb
Size: 36094
SHA256: 9b421cf2dd4baf6337fee59f8d4de941497d7c115ba7a078fbf22c0adda8a839
SHA1: e2fd2c04cce115e7fa8cdbb9005c75039af9f1fa
MD5sum: 140f3abee79c6f9f3d6469c93b721c9a
Description: python IDE for scientists
 Spyder (previously known as Pydee) is a free open-source Python
 development environment providing MATLAB-like features in a simple
 and light-weighted software

Package: spykeviewer
Version: 0.4.0-1~nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 1120
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_0.4.0-1~nd13.04+1+nd13.10+1_all.deb
Size: 575306
SHA256: 959cbfd23cf8d7761d77fac41530d08a428c4f4a773f411acb5e26ecb6e5d507
SHA1: c639d49e4fe954f60c40dbccb74e9c158da58912
MD5sum: cb9540ab965b6ba06bbab01ed8f3d8b3
Description: graphical utility for analyzing electrophysiological data
 Spyke Viewer is a multi-platform GUI application for navigating, analyzing
 and visualizing electrophysiological datasets. Based on the Neo framework,
 it works with a wide variety of data formats. Spyke Viewer includes an
 integrated Python console and a plugin system for custom analyses and plots.

Package: stabilitycalc
Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 119
Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti
Recommends: python-dicom
Homepage: https://github.com/bbfrederick/stabilitycalc
Priority: extra
Section: science
Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 28850
SHA256: 2885d99daf2891a6f2fe488f25d5f54002ff6d6df0252f5e946ceff1f20e452b
SHA1: a9e67198cec5f15cc2bc910b9a9fdbb90f7f40ac
MD5sum: 505b20b36e42d72d4d7ca1bc051d90b5
Description: evaluate fMRI scanner stability
 Command-line tools to calculate numerous fMRI scanner stability metrics, based
 on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries
 image in NIfTI format is support input. Output is a rich HTML report.
Python-Version: 2.7

Package: testkraut
Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 359
Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse
Recommends: strace, python-scipy, python-colorama, python-apt
Homepage: https://github.com/neurodebian/testkraut
Priority: extra
Section: python
Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb
Size: 99698
SHA256: 40b0868fbb47a9758a535769ae6eaac9e3ec55f0c3b39557f43303f5fe8dd0b3
SHA1: 3ca2b3698fcbc13058665807cb8ffc9ad4fd25d9
MD5sum: a6c94efec638cee547260e58486ee71a
Description: test and evaluate heterogeneous data processing pipelines
 This is a framework for software testing. That being said, testkraut tries to
 minimize the overlap with the scopes of unit testing, regression testing, and
 continuous integration testing. Instead, it aims to complement these kinds of
 testing, and is able to re-use them, or can be integrated with them.
 .
 In a nutshell testkraut helps to facilitate statistical analysis of test
 results. In particular, it focuses on two main scenarios:
 .
  * Comparing results of a single (test) implementation across different or
    changing computational environments (think: different operating systems,
    different hardware, or the same machine before an after a software upgrade).
  * Comparing results of different (test) implementations generating similar
    output from identical input (think: performance of various signal detection
    algorithms).
 .
 While such things can be done using other available tools as well, testkraut
 aims to provide a lightweight, yet comprehensive description of a test run.
 Such a description allows for decoupling test result generation and analysis
 – opening up the opportunity to “crowd-source” software testing efforts, and
 aggregate results beyond the scope of a single project, lab, company, or site.
Python-Version: 2.7