Package: libfreenect-doc Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd90+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 647 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~nd90+1_all.deb Size: 90116 SHA256: 7b1f3f8718bae55e7d612ff46474321e316a7b6c3995e61c2d1f9bd3206f34f8 SHA1: 2dabe10f4ec42810d36c3f92740c078eae537399 MD5sum: fb51b5583055b3c4a2f2eb4facd36aab 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~nd90+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~nd90+1_all.deb Size: 557740 SHA256: e5121e1f576339f39aec5bb9a54971a867f26bf355b4966f7f1c5b007b8bc9c3 SHA1: 1a502117824ccc5044998f7c0d0bee23ccf913f7 MD5sum: e80fc78faa529a78dccae904957ac980 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: 3.0.12.20150419.dfgs1-1~nd90+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233231 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~nd90+1_all.deb Size: 23890344 SHA256: 73d6c80bc4d73e55c0c229b9ab1f0803e5cc313d6653a6e64e2f40f41743acde SHA1: 55cc4f1241d931c1982ce59467049897bb1a0b77 MD5sum: cd7a3f7f0b8d75a73b8788ba9cc7f4d5 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~nd90+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~nd90+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~nd90+1_all.deb Size: 5034172 SHA256: ae37b38f52f0b48c6bf68e1eede58f59e3554a9f4351dd35f92efb92527d5d99 SHA1: 7181390303989dc418b7459e4738f2542119b937 MD5sum: ca72c9f8d500dd4cae5468eedb29d1be 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~nd90+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~nd90+1_all.deb Size: 4654180 SHA256: c95dfad2ccc38d2fb6a1fede3ea94ae229bd55189df14838066794e02cade753 SHA1: c5f00ff4b3e2eec654369ccadb228a3629b2ccb8 MD5sum: 27b35f45a7748d7fb164b73d661bea4d 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.