Package: datalad Version: 0.7.0-2~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 98 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.7.0-2~nd100+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.7.0-2~nd100+1_all.deb Size: 66286 SHA256: 4b5babb074a4688a19c483255b2bca4655041c7097037f865b1faa051a36fe85 SHA1: 6c9587036437c32d1d64d04025cfe0045b1d0830 MD5sum: 6b8979d628b568fdcbb1f17a8d9f49ea Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package provides the command line tool. Install without Recommends if you need only core functionality. Package: git-annex-standalone Source: git-annex Version: 6.20170525+gitge1cf095ae-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 164613 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20170525+gitge1cf095ae-1~ndall+1_amd64.deb Size: 34661988 SHA256: 7476a401212cdfccb4071413d593eb4a6a2a3b90abfe35dc2f21b49a5aa906de SHA1: 25957a76088e23087397fab4b552dec5e62dd17a MD5sum: 9b28890978374ebe8919567ecd37843a Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: nuitka Version: 0.5.26.4+ds-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3461 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-pyqt5, strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.26.4+ds-1~nd100+1_all.deb Size: 683878 SHA256: 975a385b58daec07bee9c2782221b94a245474647ea72a763999ff36e54f5e2d SHA1: 7f68313131ebb516d9814a69c7046a77bca1cc76 MD5sum: 4c75d70c942c58d3092c74e2b515881b 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: python-datalad Source: datalad Version: 0.7.0-2~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3650 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), patool, python-appdirs, python-git (>= 2.1~), python-github, python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage | python-keyring (<< 9.2), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0), python-wrapt, python-boto, python-jsmin, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-requests-ftp, python-scrapy, python-vcr, python-yaml Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.7.0-2~nd100+1_all.deb Size: 707520 SHA256: afc01141c5d52675a8e324df201745562f90a7c0bc60d06b06ef90346638491b SHA1: 5e5d058b091b8324853ff26f630f8a31b31b4393 MD5sum: 9135212fc9154b6cf61180b027419ae6 Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling, publishing, and testing. If you need base functionality, install without Recommends. Package: python-dipy Source: dipy Version: 0.12.0-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6929 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.12.0-1~nd100+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.12.0-1~nd100+1_all.deb Size: 3014488 SHA256: f5a083cc63eff24a2be6a46b7d8f5ffb731dfcdf2cc4443b9d0b6ba5495a2e2f SHA1: 3f073f686180dd8865046ffb8c3e80c20b944a3d MD5sum: 0363ce5e7c8d159445e068f372cdde01 Description: Python library for the analysis of diffusion MRI datasets DIPY is a software project for computational neuroanatomy. It focuses on diffusion magnetic resonance imaging (dMRI) analysis and tractography but also contains implementations of other computational imaging methods such as denoising and registration that are applicable to the greater medical imaging and image processing communities. Additionally, DIPY is an international project which brings together scientists across labs and countries to share their state-of-the-art code and expertise in the same codebase, accelerating scientific research in medical imaging. . Here are some of the highlights: - Reconstruction algorithms: CSD, DSI, GQI, DTI, DKI, QBI, SHORE and MAPMRI - Fiber tracking algorithms: deterministic and probabilistic - Native linear and nonlinear registration of images - Fast operations on streamlines (selection, resampling, registration) - Tractography segmentation and clustering - Many image operations, e.g., reslicing or denoising with NLMEANS - Estimation of distances/correspondences between streamlines and connectivity matrices - Interactive visualization of streamlines in the space of images Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.12.0-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14215 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://dipy.org Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.12.0-1~nd100+1_all.deb Size: 10551850 SHA256: e422a518abf56346508fd94e8e0df481b9c7926aa6a8fbafcf9a54f6104fc61d SHA1: 16254163533e3554b325fd17c03563aa8c1952d4 MD5sum: 51b3af04733fb250180ae23bd4f4a4cb Description: Python library for the analysis of diffusion MRI datasets -- documentation DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.12.0-1~nd100+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 9425 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7), libc6 (>= 2.14), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.12.0-1~nd100+1_amd64.deb Size: 1838284 SHA256: 2fd1f4e4b21eb4b1533534bcf22bf1e06d2d86d67d504b70bfe4576269cfec89 SHA1: 3f6bbcd4544e2c0fcace89c6562b4b8807df9798 MD5sum: c45ce7906f502ddd4f7b1ddc1dd61c0e Description: Python library for the analysis of diffusion MRI datasets -- extensions DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-dipy-lib-dbgsym Source: dipy Version: 0.12.0-1~nd100+1 Auto-Built-Package: debug-symbols Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8938 Depends: python-dipy-lib (= 0.12.0-1~nd100+1) Homepage: http://dipy.org Priority: extra Section: debug Filename: pool/main/d/dipy/python-dipy-lib-dbgsym_0.12.0-1~nd100+1_amd64.deb Size: 7875654 SHA256: 571110b0ad69355a796fcbe1f95bdda9a8655f08070d41e9e107287f0085dd36 SHA1: 6a5a1d3d479e5ecb7b640f1842ba69ce8293cb21 MD5sum: 6f4969776ac0a94b94aeab618c4a4d34 Description: Debug symbols for python-dipy-lib Build-Ids: 084921106b5b8faa27f343faaf140c16ec8678f1 19cabc86cae473b4cc6f27e35ad4955a99e0e120 2654b16b4a107f245efa95d91c55c3b0f0c23f50 330e3502253124f857db1449331885d0b58922d9 347dff78a7ad89732a21d04cc3b99527c8ce6615 41367730e19a41a37e3e3fb044c20bb459b63544 41a4205e8579b8f22efa5b4d05b8f67b3e376e7a 4e0df7106ad82088ee09bb10bc2cb95bb8ae6bb8 4f8375b9bdea7d2499c3100239cccf7d3dc0e037 5d5af17fa12f0f43afc59d51784168ac1486aef2 5e219c292f3c12b8ddccbcdb0f07a266b57f0b69 6c841d39a3ebf6a5be8da507becfa20832f96a16 73ec41e2b5980d6ae84a2f889f21d085eed2ee4a 76bbbbc5c25b227b4e5c6ae777eb35ab61be4aff 7c39b355f84f49d1c67528212c4cf827911749d7 7da43111a75e62068b773d04ecd9bb5e4f8ac3fe 7dafefece304e62c4d50cb909094cbfdda0578af 813c24638068f0584a97a878cedb62bd962b9b13 9112b3d28b6ae015c6e8c5c97b87a6ef39c5c36d 9541459a691bea8b001a6e740c8c1d4fec94e70a a713d0637a78c95d6ae827ca72119df680ee1491 afb427fc8cd4430e464a9ad634d8ccfc97b1cc16 b294d72781713ab0f20209b5cebf650a9856a9a6 b92235e71b78b179ba72a602c30fbb56235218ea ba3aecaeaa30b64e1cf9d9b4645f267286621c75 c63bfb8576e0058d7ee41c14c8180cfd972af216 d1d1caba67eab461b55a14803bca2925a09fd559 d1e1b4e2970084ff9fef0cc72a340b8f3239e5ae d23c02b2c0addf054292dc5a25ea6d77d2b2b615 dc3702d6c1107142e59b51846f2b14233e5add29 f4039adc4cc7fcb205316719cd7efa5254d7822d fedfe03eeda56918e5da926b323b89d29ae335bb Python-Version: 2.7 Package: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python-whoosh_2.7.4+git6-g9134ad92-1~nd100+1_all.deb Size: 290690 SHA256: 5cc2d7491e8ab52563aa8a32cdd3a223b78899713b74fbce565c022bba475819 SHA1: 745ce72af3b29abb3e44f83ee80a8fe450908bd9 MD5sum: a4a92bdf70ca01e924e0381d347635b4 Description: pure-Python full-text indexing, search, and spell checking library (Python 2) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python2 library Package: python-whoosh-doc Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2213 Pre-Depends: dpkg (>= 1.17.14) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Replaces: python-whoosh (<< 2.1.0) Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: extra Section: doc Filename: pool/main/p/python-whoosh/python-whoosh-doc_2.7.4+git6-g9134ad92-1~nd100+1_all.deb Size: 241300 SHA256: c28cc15134ac59dfd4c7384e30f72d97f7b263f0e27d7074afb29d953e785352 SHA1: 23d3044711e4074d5e1be14cf7b4cf5d644c2b2e MD5sum: 5d4ab18c7fe2b916a8aea674872b4224 Description: full-text indexing, search, and spell checking library (doc) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the library documentation for python-whoosh. Package: python3-whoosh Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python3-whoosh_2.7.4+git6-g9134ad92-1~nd100+1_all.deb Size: 290826 SHA256: 571725d4546678cbe70e525f38fc66853aa7fda32e27b56dfaac8ce5b674210b SHA1: fb6fa2b9a76d4ed9fec61aeb4972ce88487d5e7f MD5sum: b46e377dd534da6136e6d9d087ca69a2 Description: pure-Python full-text indexing, search, and spell checking library (Python 3) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python3 library Package: singularity-container Version: 2.3.1-1~nd100+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2344 Depends: neurodebian-popularity-contest, libc6 (>= 2.16), python Homepage: http://gmkurtzer.github.io/singularity Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.3.1-1~nd100+1_amd64.deb Size: 288040 SHA256: eb20f6b95ebadb0b1093f7bbf7bd3b182a42978dafd3904cbef944a744b3835c SHA1: 73272936b91e506ea2586fd79df17e40d2f3efb2 MD5sum: 512a341c2e61601298e84c67001234b8 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: singularity-container-dbgsym Source: singularity-container Version: 2.3.1-1~nd100+1 Auto-Built-Package: debug-symbols Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1294 Depends: singularity-container (= 2.3.1-1~nd100+1) Homepage: http://gmkurtzer.github.io/singularity Priority: extra Section: debug Filename: pool/main/s/singularity-container/singularity-container-dbgsym_2.3.1-1~nd100+1_amd64.deb Size: 979612 SHA256: 43106156e5fc8ab6c9cfda341f4eb3757c13a40b0ec99251e8f93415a15f9c7d SHA1: 15ae82d20d1cc3e8747e4ec51aa83adb6ef86e5a MD5sum: 54d99e82b87d8323d37fff9249300233 Description: Debug symbols for singularity-container Build-Ids: 00576af8d457f8e10a84033811c0d92b5bc7ef5b 1a14f9b55b975f0eb065c7b7f1e1b0590cc1a2ec 294ff7ae3a95aa28e0603dfa77c87e6d782d7154 3db88c62c692fbdc3f8efdb15d7f7e8916b1dbf5 4204720efff869881ebfc6d86232bd1ab761c4d2 695e5e7193b1cf20cb86cefdeed83ba278beb8a9 77398d18467b7132898eb85b700f29e7114ff81d 81a1681a08bfbb693b6f3bf9c73d5329ac50207f 99810957efdfe5a45cc6db6cf26d32a5c27929ef 9ae93818f1ef175a40c72a7549be4c03f20c2d94 9e0456cf4d5a2432696b16a853deaca49e1d6613 a2db705b18738e1fee74db1452dedb7dd838b6a9 ab6ed56d4dee60a3e6cc9b9454ed00f1ac7dec40 ac15177a67dbb0dc483f2ed02db3a325aaa6cacd c40c3476f852280b5fbdf07ef1dfd1edf8bfb5dd e21aab48e4632b8d784291ca066669dfb912a0a0 ee416f8f4edd4c6212f1e48b01a5f76e0161b6fa fb9ffdc34952f15e8b7786a0698d1b8b70b561cd