Package: condor Version: 8.2.8~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.2.8~dfsg.1-1~nd15.04+1_all.deb Size: 14812 SHA256: d6d250778079d26934b250d396d713c763a4e99ef5758ebe89ee3023928e2100 SHA1: bfb097bf0738114c45ba9c01c761b32c507432d4 MD5sum: 041a91e525c5b3be0c660df6c57e0fcf Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.2.8~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.2.8~dfsg.1-1~nd15.04+1_all.deb Size: 14824 SHA256: af941cfceea6759b786a4519d9172db1cd923afc21f652e7dbd516ce552fbb97 SHA1: d1dacc45ac649cc9e4a3aef1d76a22b91cb18457 MD5sum: fd46c7a84d29fad6e77993cda5b5e9c2 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.2.8~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.2.8~dfsg.1-1~nd15.04+1_all.deb Size: 14824 SHA256: bc32bbb22789af23a9bfe4d80babf8fe8c44a9276022e04dca7a923e94754b14 SHA1: cfb0e28b4f4de838eab1567c31ab86ddfa147261 MD5sum: 1d7a50ef370d4b339f67d81fd0c01a8d Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.2.8~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 45 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.2.8~dfsg.1-1~nd15.04+1_all.deb Size: 14822 SHA256: 6d8f36479e09dbd65afb2a421a6cf535f46c187978ad2ef32e3ce4e6efd3048f SHA1: 024798c2fd8d1e71e2a726d875acd6bfa2457fa3 MD5sum: ceea39253f59a4728029f679f5a356cd Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: htcondor-doc Source: condor Version: 8.2.8~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5695 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.2.8~dfsg.1-1~nd15.04+1_all.deb Size: 1040902 SHA256: 9dec55582d1ed75b2f0bf5f7dcc5559b1f23a65d9d7b6af200daa375cebc7643 SHA1: 89bb9ddec88d76cf30ba69e2c543f71a4fdc7d3c MD5sum: d2c5fa37df249b36f4a03f38ca807951 Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 786 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_all.deb Size: 133088 SHA256: 0834cd7a553b3ddd2aea16144aa81e7284500b06624e4f38b63b125eaef7e0eb SHA1: b3665cab138b734212d22b1dfd72114ae180b92c MD5sum: dabc71d31109694a198434f25498d5d6 Description: library for accessing Kinect device -- documentation libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the documentation of the API of libfreenect. Package: nuitka Version: 0.5.13+ds-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2402 Depends: neurodebian-popularity-contest, 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 (>= 2.6.6-7~) 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_0.5.13+ds-1~nd15.04+1_all.deb Size: 557556 SHA256: 3cd40ad989eb077b7ac70631b7730bedf1033d76f68a678f0c247e3893097353 SHA1: f681b1ce7fe9a66dd8b65119a2a577968583a9d1 MD5sum: 99b4dfb0457048ba6b05cb2403efc534 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: 1.82.01.dfsg-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14414 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-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.82.01.dfsg-2~nd15.04+1_all.deb Size: 6059036 SHA256: f569804f5be29d31f17ff3b1cb659b4d192de96727067570a8ec9b3797ac1b57 SHA1: f9ce9e5f31c7ee2c841656e9d9bb1979f5d8b3a3 MD5sum: f74fa5fea68c78107245c943b1ef4499 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: 3.0.12.20150419.dfgs1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233227 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_3.0.12.20150419.dfgs1-1~nd15.04+1_all.deb Size: 23887120 SHA256: 1e4dc75fdb64a909571b6464c64d2abe361e366e0b9db4fc07bd087c3e3bde61 SHA1: 9e656a980a423421fd74e65cba2346ee9de7c2db MD5sum: 6d158c44757162982bfafabeac8708b6 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-mvpa2 Source: pymvpa2 Version: 2.4.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7903 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.4.0-1~nd15.04+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 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_2.4.0-1~nd15.04+1_all.deb Size: 5034260 SHA256: 7e7e1a598bfddba0feb7298fef34a4aefbe085611ff36904d295af3071265885 SHA1: fddab46e799007c4dc01500658d5aa5bcce34879 MD5sum: 6a58f0eb5866df9d2339cd9bee7e36cc 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: 2.4.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29062 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_2.4.0-1~nd15.04+1_all.deb Size: 4654198 SHA256: 893ff27d2502daa1e8b19dc5ca7a98e4acf204d12200abc57799af420fa9f476 SHA1: 74ff2f3363c2dfe8615084d5c75302eed2d53e66 MD5sum: b7fcab88cbf84659bfdfcde1fb609dcc 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.