Package: datalad Version: 0.15.5-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 195 Depends: neurodebian-popularity-contest, python3-datalad (= 0.15.5-1~nd120+1), python3-argcomplete, python3:any Suggests: datalad-container, datalad-crawler, datalad-neuroimaging Homepage: https://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.15.5-1~nd120+1_all.deb Size: 158028 SHA256: 587d0428c13571f9111ca7b3725a0b27f4e804ed4615bc7a4a90489f5cdac8ba SHA1: 4c5a55a2898c00f77ca98025fd7d2eb539c9e540 MD5sum: 48f537e87ac3be1a28ef514f1cb388c7 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) Package: impressive Version: 0.13.1-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 502 Depends: neurodebian-popularity-contest, python3, python3-pygame, python3-pil, mupdf-tools (>= 1.5) | poppler-utils Recommends: mplayer, ffmpeg, perl, xdg-utils Suggests: ghostscript, latex-beamer, pdftk Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.13.1-1~nd120+1_all.deb Size: 201912 SHA256: c5500d87a6fc0938c54dec0f1ad2dd5943f73291b4ae21bf27e17d4689758923 SHA1: 09ae8dacc2a14e6b82ecc93cc6e47cb6dba035dd MD5sum: bc442098ddc692e94fc1936ce00d5e68 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: nuitka Version: 0.6.19.1+ds-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12321 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python3-jinja2, python3-appdirs | base-files (<< 7.2), python3-dev, zlib1g-dev, ccache, chrpath, patchelf, python3:any (>= 3.3~) Recommends: python3-lxml, python3-tqdm, strace, libfuse2 Homepage: https://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.6.19.1+ds-1~nd120+1_all.deb Size: 1267012 SHA256: 9901ec0131c02dc5c3706131cf9324bed916c904f45b0c52ba5307c059cc4827 SHA1: e075552dd41c0320c91b157102ef4a2d16a6b654 MD5sum: 1e74c1d844fc19a66b471e1d19fc549f 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: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.18.4.dfsg1-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 647928 Depends: neurodebian-popularity-contest Recommends: alsa-utils, gamemode Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: optional Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.18.4.dfsg1-1~nd120+1_all.deb Size: 26211580 SHA256: fed73a8b2e46b17336a9b005fa17fd261a3eaac7dd9cac3b835201f50dc105db SHA1: 60629071248a75641758d6a38e2c245727e03e93 MD5sum: 9062114b3f5717ac021397a19773341c 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: python3-datalad Source: datalad Version: 0.15.5-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4214 Depends: neurodebian-popularity-contest, git-annex (>= 8.20200309~) | git-annex-standalone (>= 8.20200309~), patool, p7zip-full, python3 (>= 3.6), python3-annexremote, python3-appdirs, python3-distro, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners (>= 0.14~), python3-gitlab, python3-humanize, python3-importlib-metadata | python3 (>> 3.8), python3-iso8601, python3-keyring, python3-keyrings.alt | python3-keyring (<= 8), python3-mock, python3-msgpack, python3-pil, python3-requests (>= 1.2), python3-secretstorage, python3-simplejson, python3-six, python3-tqdm, python3-wrapt, python3-chardet, python3-packaging, python3:any Recommends: python3-boto, python3-exif, python3-github, python3-html5lib, python3-httpretty, python3-jsmin, python3-libxmp, python3-lzma, python3-mutagen, python3-nose, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, datalad-container, datalad-crawler, datalad-neuroimaging, python3-bs4, python3-numpy Breaks: datalad-container (<< 1.1.2) Homepage: https://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.15.5-1~nd120+1_all.deb Size: 883152 SHA256: 715c492ce5c9660cf6e83f9dd7e06efad2b5cefa9e5de7da526c4cd0a9a427d6 SHA1: ce63bc7cfb7157da5e57e8106411d5ffc344897c MD5sum: 765722ed289d9fa26b01628b72528074 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python3-duecredit Source: duecredit Version: 0.9.1-1~nd120+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 284 Depends: neurodebian-popularity-contest, python3-citeproc, python3-importlib-metadata | python3 (>> 3.8), python3-requests, python3-six, python3:any Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python3-duecredit_0.9.1-1~nd120+1_all.deb Size: 67272 SHA256: 88810abe8cd9e534b83724f0a1dd9fdc171aa72d3caabd5421f9d7e30af33f36 SHA1: f21449bb9185076934bca5eaf7bbe6d11093108b MD5sum: 36177580e7b6103956cd3bca44b67baf 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