Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8117 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 7059424 SHA256: 3f090fdf3072e4e5b6ac524be1fff62f6d940c0e49f39e0843ba76d43e5b7d2b SHA1: 3f7081f142023ddee661a2980ff92df8a18bf7fe MD5sum: b9da13b2959435f2ec53d8cfda008794 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: 0.9.4-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1199 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), init-system-helpers (>= 1.18~), lsb-base (>= 2.0-7) Recommends: python, iptables, whois, python3-pyinotify, python3-systemd Suggests: mailx, system-log-daemon, monit Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.4-1~nd+1+nd16.04+1_all.deb Size: 249598 SHA256: 0a64e615ff52326ea77f03f5fddffb0952cd3ec3937d4092476bc86ab2eba8d4 SHA1: c20a8d4f5c5ac3e99d3ce401380fdcc1af9074ec MD5sum: 3a1f0e5b6e59e048c5e9abde8183f0e8 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: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73 Depends: neurodebian-popularity-contest, python-matplotlib, python-nibabel, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 13946 SHA256: 98fec451744471ae6b47ee84ac52821b45ffd63401f9f29586a9aa6be46a8702 SHA1: 0fb8488befc01e715be4378c0affa5f4d8bce34c MD5sum: 7b7b1bf6546af8b8bcfa435171ebfc89 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: 4.0.1-6~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2930 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-6~nd+1+nd16.04+1_all.deb Size: 2227648 SHA256: d85f59cee9b040e9680c9817ee0e831d88dca517d2880029a7e9674aead08469 SHA1: 326b580203ce06c723591e460854d73845119293 MD5sum: 9b50fc95856220ca1a5876e4772eff2f Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: heudiconv Version: 0.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 49 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd+1+nd16.04+1_all.deb Size: 10286 SHA256: b869501f708fea57cfd20fd4325c042865373309c23439a3fc68da089e2821f3 SHA1: 1d3abeac3233e632cf971f22e066c6764272f9a3 MD5sum: 2981f738670efec821e5b4daeb773c86 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: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 39 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd+1+nd16.04+1_all.deb Size: 9092 SHA256: 3768f288d0fb7988e227131b3e41a31c00436992b06d2b18e8113e0db08835c0 SHA1: 65c2eeeeb2ec075ec99aecec567a613b9ed2343c MD5sum: 4ff78d0c6fe0960cbf435512258152c0 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: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 5088 SHA256: 5336188e50c28a623d14ce0305ec77a4efef641cdef4c53c5e52157daf080def SHA1: 3ec074921fdde47d6c380e07226bacd940068f41 MD5sum: 349af0ebe53b5ed02810a3874940a35c 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: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1961 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 157932 SHA256: 2f24afbb9b3936557b75c9f69827bad728cd057e3a34aac31466f47d948cb216 SHA1: accfe2ca334b0b97c931424db47de6e435fae5f7 MD5sum: f81b7692ba25e05413fe88a248cc60a4 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: mridefacer Version: 0.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.1-1~nd+1+nd16.04+1_all.deb Size: 637084 SHA256: 61171ad1d66be396e47ff2b9fd15f81f89f9e98a86ac5a13348dccf50c4e9ef7 SHA1: 7a0a9de78fd5f5b729443093360f9499e1f8ec92 MD5sum: 7092b1a40c46bc624b17e265611cfefc 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: netselect-apt Source: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd+1+nd16.04+1_all.deb Size: 16814 SHA256: 22e5cc29f87c08ceb667084f2af3810aaefd1b5fc0828b2f0b0e29cb2a4dc46e SHA1: 90467c75aaba4e464a72ac39884410acc60cfc49 MD5sum: 60f499833563a70a8dc586c029092380 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: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 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_0.37.4~nd+1+nd16.04+1_all.deb Size: 33220 SHA256: 7a291254cef69447223cf23e174be2bb9dde5641d732066e8133103ed477837d SHA1: 026e23734c048805c40e42dd3152d1c5374a05ba MD5sum: 305c5e15259de877b868dd87d20ec7f9 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: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 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_0.37.4~nd+1+nd16.04+1_all.deb Size: 10212 SHA256: 54f93bb27b10a63d53d5cc56bb5e5bc76e5eda79149dff996860017853bb861e SHA1: aff10204df3e0a20b90cb4ddd78a4132befd1ec8 MD5sum: d3a3a7235f2eb3aa7b806b29d07b8f97 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: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.4~nd+1+nd16.04+1_all.deb Size: 116286 SHA256: f81556e3bf5b4e5b98aa4ce962bdd588f78bfa30d6f3d02458d0ff2a805d1941 SHA1: deaf7c94a9666e5339092bc603664de59f26d677 MD5sum: 003085b0b9131edee9aa909f5cb8c6d1 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: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.4~nd+1+nd16.04+1_all.deb Size: 32578 SHA256: 3b86dc568ea07bbcc38a60c30adc9f9e5fb53648f215a33531dc86932d963b49 SHA1: ae3c1ae4a137e5fe852bb475196eaa78fd80f63a MD5sum: bde159eaa3f00b17f487946335abca22 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-popularity-contest Source: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.4~nd+1+nd16.04+1_all.deb Size: 12254 SHA256: 51221ecc02fffe5cdb87ead95e1d8b2171c95a49640ba0664e81ed7cc5bb62b2 SHA1: df497665fca4e0962d393ea3793ab56efc04a170 MD5sum: ce5743cbdf8ce13b610c6f09a3f5a069 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: nuitka Version: 0.5.21.2+ds-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2919 Depends: neurodebian-popularity-contest, g++-5 | g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.21.2+ds-1~nd16.04+1_all.deb Size: 612312 SHA256: ef7d5cfa0f96abf9950c86cae65c7a19905986b310e968be60f28e74b8f45e6b SHA1: 63cc450f621205e9fe197e368b38c74056900e34 MD5sum: 45653dafbe6c36aba61b9af825616597 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: psychopy Version: 1.83.04.dfsg-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15088 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.83.04.dfsg-2~nd+1+nd16.04+1_all.deb Size: 6133828 SHA256: 7bc5b24a1849eaf939d573157788037c0f1f6a6a54bc84c45b025780d09b207f SHA1: 60bb27e236f204f1f43c10b98e20170e50ac4f60 MD5sum: 269a0abc067dfa3a1d79234abf54295b Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.12.20160514.dfsg1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253492 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_3.0.12.20160514.dfsg1-1~nd16.04+1_all.deb Size: 24206914 SHA256: 7de703988c4bc3fceaa3d42d246ec6d7df83a85cbcdcf3e40e660e90a109d03b SHA1: 8be50f23cd6155917c3971481150c211030f1fe8 MD5sum: 9ef1e9fa7bd98831ea0926609c441dfe 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~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 24608 SHA256: 156b7dbfd8a99d398fe740c822ba51762781af630c9ce000cdebb5622fe4cd2a SHA1: 937a26dd82a75e4b14bb613ae8f6dd187ee9e10b MD5sum: 3f721e38ee6f5930587547ae87875163 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-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 505 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd+1+nd16.04+1_all.deb Size: 77560 SHA256: fb442364f1761b5203c259ef22654f0f4bb883a8eac5dba645ca88b0ec327125 SHA1: 809e0e779921d515682e8f3b543df9321b89650c MD5sum: 307b067807c7a48930ebcc46f0121e7a 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-duecredit Source: duecredit Version: 0.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 234 Depends: neurodebian-popularity-contest, python-citeproc, python-requests, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python-duecredit_0.5.0-1~nd16.04+1_all.deb Size: 49836 SHA256: 8f6b727151ec14685e5ec685c741f6a80c6e392914e444d2c8c625be85b00468 SHA1: 7f3ad805ef2aa096fd0348549186326edd60215b MD5sum: af07180f2cd5a642d3a14d34cc7fc61f Description: Publications (and donations) tracer - Python 2.X duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python-git Version: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1570 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 0.6.4), 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_2.0.2-1~nd16.04+1_all.deb Size: 288848 SHA256: 5874b2bf64b59c1ffaedeb3496f1ed8144e045e5d28baa5fe0014e0351c014c9 SHA1: 2325b61151d56301934cbd8660339e17b2356072 MD5sum: 20c6d081d52b6c87d60fa85d860e7296 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: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 929 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_2.0.2-1~nd16.04+1_all.deb Size: 118534 SHA256: aba29ca03a7bdd4569919ef729c6e4e2461d538da47902e23b0cdc68371dfae1 SHA1: d8a126e4a7c70835c41ff384da3dd4ad7a00fbdf MD5sum: 73bc8c1c52a05d0def3f16b27be8dcb0 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-mne Version: 0.12+dfsg-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9400 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), 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_0.12+dfsg-1~nd16.04+1_all.deb Size: 4429294 SHA256: c47f48baf80955067036ff7bf38ea74cba7d331dc1d2190eab733bddb5ce1cb9 SHA1: 88551144c408775c27da88fbc52421344da97bd3 MD5sum: 0f008fb18cc33ad9c47443a2e68e9ea3 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-mvpa2 Source: pymvpa2 Version: 2.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8447 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.5.0-1~nd16.04+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_2.5.0-1~nd16.04+1_all.deb Size: 5076730 SHA256: c9e3c731125b45368841bc130c36f0932471d660abe7e4e995e1b280426b57fc SHA1: 28ab1d8a76770abe17109876e991dac01f373a76 MD5sum: e5ce5dc4ef35e4f0d491bf95f01b0f45 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: 2.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34533 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_2.5.0-1~nd16.04+1_all.deb Size: 4552964 SHA256: e92f599d20b06902260bcd3a6a20d38a7ab9aed569988f75c95c1349415de14e SHA1: 478f16df19b327d66a44809f93c3bda3545b4fc6 MD5sum: 21cf8ddfdbd235ef083af4a9ac6e4915 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~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 115 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd+1+nd16.04+1_all.deb Size: 28850 SHA256: 35e58bca96796988f7c3097c71ba0e078b6063215ce782dfb2461f30da939f7a SHA1: 37df2d9b9330ef7948d4bb86173b30a9eccaa0ca MD5sum: 6fbc209e0a5e48cd60f07cdbfc7aba56 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-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1323 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-jdcal, python-lxml (>= 3.3.4) | python-et-xmlfile Recommends: python-pytest, python-pil, python-imaging Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0-2~nd16.04+1_all.deb Size: 199220 SHA256: b70affd1599e94a0a0930fb4497a75e7466ed0e7b4f1e4ad1be006c6327e75b2 SHA1: bc62307b04fb297c5e98a1e2a55ff2339524aae8 MD5sum: 90c38c6c2346aab02e8a77c47243a274 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: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13062 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+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_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 1761628 SHA256: bdf8a873b0689f85de49043080a66b3db748d23ee249ade8fd1846fdd39dd6c3 SHA1: 51dc91d23ed7d77e7226a51725870de453b229f2 MD5sum: e3af81eb6c0a538bab0f91fdaff1fa44 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: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56947 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_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 10937012 SHA256: 5f86809d0b83c1d5fe64fb18b865d454ed30b5e53ab92109238d8abf924035f3 SHA1: aa85840797bfe5ed8d61ffcccf0a8e39fa259d12 MD5sum: 0301c163fcca6afe21e7d31ded207b96 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 822 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_all.deb Size: 819350 SHA256: 2e955547503f670039815376e4ac8860679cb376009788bc07c133ad3cf0dc02 SHA1: 349b67ae265dd0cbb576d6f2cc991cb1b9582a46 MD5sum: d7b4b656eb6f9dacf1c258cfa9df35bb 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-scikits-learn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65 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_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 56050 SHA256: 45adc827b4aa2474390176c25d13dc3446faa326e86319af3f008f496006af30 SHA1: 6338a6ab54c6a7239cdf79ba9748675bea42906d MD5sum: dfbe4583cca67c94614c0005eee8e8b7 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-six Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11102 SHA256: e53e9566f3e3305d5ec1a8b3ed6a12f61a5f0d3279112666903e47ce68c4498c SHA1: e2e8f56e31d6f67994297cf8ef87bd10077f81b0 MD5sum: 19367b5b0032f4ee89cd3f543ed27e5d Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 21 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 13318 SHA256: c8c2f26a64c9b1993f231546b6d5d3f4d0f8a4e96f0653c53060c6dde6b36d59 SHA1: 3abcec44fa903592ff069a138e1f57a4ddc7a93a MD5sum: ce48e44e76d54ab53124a9eb02b58690 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-sklearn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5283 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.1-1~nd+1+nd16.04+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_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 1223586 SHA256: e3fc7a163df7f54a06719b94aaa8ae8a4fc13dd993db77e4d940c5885e90272c SHA1: c0aa990dd46f5fd4f68f524715831ca16b93c2f9 MD5sum: 1e29d4471ec9083dbe27a0022a2a961c 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: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24874 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_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 4018952 SHA256: 2267e9c87f930981ff8e6dbaeb57c3dc0162b9c64ab2a7f2f8616ba16686f6cb SHA1: 5b8788a060ca872bf02e4b506c47f46f289384c9 MD5sum: 892cb3b87ccf35037b122e6e74effe21 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-smmap Version: 0.9.0-3~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-3~nd+1+nd16.04+1_all.deb Size: 20198 SHA256: 37f7091dea7505df24c110b49803dc180666fb029226d920c1ed081d0bc5063c SHA1: 1c047a11bc08e73e4ea2c266b23a77b4b01d3b96 MD5sum: 6c69e2e20aaa72a6d5e0acd5c2483789 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-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six (>= 1.5), python-wrapt, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43580 SHA256: d13dfc1adc96024f35330d4c72825e3f09b9767177330c804cc3575079e11498 SHA1: 38af2662eef11399c694c53bdca1e4159e830bc8 MD5sum: 212bc7388c199867c3f9d80be6d829c2 Description: record and replay HTML interactions (Python library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 2. Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 21058 SHA256: c93bdaf1b23b65d220a8c08b7043df874b281287d7145de0427dd1c2234f151d SHA1: 16ffed2622ee3e42555797e3f02591e8097e9419 MD5sum: 9fb059ae75b85aec11d96ed5c6c686ed 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-duecredit Source: duecredit Version: 0.5.0-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 236 Depends: neurodebian-popularity-contest, python3-citeproc, python3-requests, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python3-duecredit_0.5.0-1~nd16.04+1_all.deb Size: 50062 SHA256: 234ba4405e3239bd4e409a9a04f55bdd571e7eebad9e5961f87c86795b09aa71 SHA1: f040a55ba952a28624501c3a51e4c2d57dd88832 MD5sum: abaa1e044235cb9607cd608816e8e41c Description: Publications (and donations) tracer duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python3 -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python3-git Source: python-git Version: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1567 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 0.6.4), 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_2.0.2-1~nd16.04+1_all.deb Size: 288842 SHA256: d76f1c9a484353c059c38ce441201d1c911503110d111e081ac04b74197d41a5 SHA1: c7e20620b35135f744b8bd9c8bdfcc86360b6fd5 MD5sum: f2e1480f0e385c449b04876cc75977cd 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-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, python3-jdcal, python3:any (>= 3.3.2-2~), python3-lxml (>= 3.3.4) | python3-et-xmlfile Recommends: python3-pytest, python3-pil Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0-2~nd16.04+1_all.deb Size: 198366 SHA256: fdbf672443fd6a1fef2972081a62e73df077d6df43362d6bb9c4103d82bb2bff SHA1: 7da58edb8f3231d5a648b5ea1f8d82c778ec35b9 MD5sum: bd9936151cca80596c5a727f5cf04c02 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: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13060 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+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_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 1761432 SHA256: 47eaf5435943a88f6ca141d87147cb81b9a448e42cd8ca25d25bae5d91f3c99e SHA1: 5e256387804735d943b9b94c1041e36224adeb03 MD5sum: 023e7c3f64cf123f9865cf60bc94af4d 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-six Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11162 SHA256: de89c30fb266478195674d595d12a1513db7e2956c8af953ce1f2720e45d4ad9 SHA1: 4c90cc7b7fc37bedacd44c403965b35de5a1751b MD5sum: ab68168bc1f5b17416eb4c2f602f33a3 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-sklearn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5282 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.1-1~nd+1+nd16.04+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_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 1223126 SHA256: 3b28b162208fa5b5f7235a0fbc97bed0f84e4275c4cb26bc8ed0565b40c7937b SHA1: 406b42aa243cabebfdb495f02e24f0871fa9c5df MD5sum: eeb95f2492c4d2fea8c7c02d99d5b94b 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: 0.9.0-3~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 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_0.9.0-3~nd+1+nd16.04+1_all.deb Size: 20284 SHA256: bfa892cc23a05905952f05183485a112e9aed4c5b0386ebf8c08e72cf9e87a06 SHA1: 9e20c8d297d9788e3b08ec4aa7e00e980e05606c MD5sum: f14ccea8516ee46232a99dac3d53ca3d 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-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python3-six (>= 1.5), python3-wrapt, python3-yaml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python3-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43654 SHA256: 18be5074cff6cd48dd691e1921cc15a96ad10de55944bad110958f0842ca8628 SHA1: 4de90dcf566f64fceaaa00a00af8fe588e105295 MD5sum: 4bb489a1b4d0759306109fcd31ec7e58 Description: record and replay HTML interactions (Python3 library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 3. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19186 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 9781970 SHA256: 30cac74b9ad9db32f093eece5bae13d28ce4e1222878358f3afc6e6a67b55b67 SHA1: 4899f3ba6a1ff156b67ed1b324ae4a83ffbbab9e MD5sum: 093fd447d8b43ebafc21585625545b37 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73019 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 45497774 SHA256: bde3c93b9c1168ff6fa5b3269782006cf5613ba3f2b7b49abd5249d07600335b SHA1: af6dce85c4ee9079c720d544dfacfe2fc2cffa67 MD5sum: 494ca73671489f3feaf525e4295caff3 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9251 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 8934936 SHA256: 7f6f08608f31115b8e51d149f8560a2cfe399bd44562ff34bf2aeb24a9632bc9 SHA1: 31e802efc7a2237d47eb5a13d1d6f6a6f9ed7324 MD5sum: c96ec4b1e942cf1f8f8eb55b327d7c40 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: ubuntu-keyring Version: 2010.+09.30~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd+1+nd16.04+1_all.deb Size: 11702 SHA256: e6052ad683b7b3eac5152f3790fcf69f3340f2526d81e9e394a6c4b11fbb26c0 SHA1: 288fe25a2be199481113954438cd17bc01060293 MD5sum: f432078db30b3298f5dbac78eaad7c06 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that.