Package: biosig-tools Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 658 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 281678 SHA256: 885b1ca3db821763bea5d8c15a16543c6e4e0fa40c5c78bc291527041c016903 SHA1: f0d767a5bdd1824a6eeb0589e02d70276988cc3a MD5sum: c2a4e407321d93bf26a55a5165d58401 Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as . - save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 48006 SHA256: 2adeda07ebad03851a8b51721aac5692dd62758654cabef62d31c7b367ecba4b SHA1: f77f2d40282de63770e2b169722fe0cada0b248e MD5sum: 530a41eb330082ace23d42ac9558dc92 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 7224862 SHA256: b676b82109d135052588444785b36d65fe3e96cd7199cbbb0bd7c2c07d3cd801 SHA1: f9190f6dbe6d6596884363f4aeadd7181991eb43 MD5sum: 06ebb1802f177f2a117f1d51a2213ec5 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: eegview Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libeegdev0, libmcpanel0 (>= 0.0), libxdffileio0 (>= 0.0) Homepage: http://cnbi.epfl.ch/software/eegview.html Priority: extra Section: science Filename: pool/main/e/eegview/eegview_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 11052 SHA256: e6f2aa5eed5d9cf52a8e29b96ef132147e2fec9c4727587ad33101f095f38e6b SHA1: c6cd4e0941cc9814a190af1a36554dfdcaaf365d MD5sum: edf9bc4600b66fa8e05da55ebcb0c3eb Description: Software to display EEG data in realtime This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment. Package: fslview Version: 4.0.1-2~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6576 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-2~nd13.04+1+nd13.10+1_amd64.deb Size: 2341194 SHA256: e864966e24bc9337101255c5b2070433f4a6ddd7524ca891e3105a31c9851475 SHA1: 18762f20b2e47ae971046a4e98ec57543f77a8b5 MD5sum: f9bdf69e64347898aea4142a35ab9050 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 4.0.1-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2874 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-2~nd13.04+1+nd13.10+1_all.deb Size: 2346584 SHA256: d18c868829872ad3b67c0902b9dba50a49c1b221a498c79efda662247520d444 SHA1: 0eee7201a822e7f6e330c233f732e29df7e2cfa1 MD5sum: 1fbf262f0226c131b9096afe8705b64b Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: glew-utils Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 409 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1), libc6 (>= 2.4), libgl1-mesa-glx | libgl1, libx11-6 Replaces: libglew1.6 (<< 1.7) Homepage: http://glew.sourceforge.net Priority: optional Section: utils Filename: pool/main/g/glew/glew-utils_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 126340 SHA256: 32a60283320afcbcd373a66376c490d73193c2ceb1caca92af0e736d8fd6b6b9 SHA1: b5ec87f77805de84c191d6e750d7852ae7e63b70 MD5sum: a04054fa821b4eb3fcb9e8b75fde1256 Description: OpenGL Extension Wrangler - utilities For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the utilities which can be used to query the supported OpenGL extensions. Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 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~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 9792 SHA256: 0b9a6311f3505e3617a06a6c9c484f2d75b0c5d72c8399f677eda471fc8d0acd SHA1: 68241f8405acc62727278602c524900998fa8dc4 MD5sum: 27174485f0fac376de0ebe388d427929 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: libbiosig-dev Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1705 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 426368 SHA256: dd19d418332c15e655b661a9a673986077ab7eb7ec94ae96ef0d0ecce42b51b9 SHA1: 36019b060d88b3fbedfcbdd60451c362c33cc778 MD5sum: f1a14518155e31ea099f64c256310fa0 Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig1 Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 904 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig1_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 336726 SHA256: 31ea11d9c9243e76842c7aab17391deb78c548efb4d3256157faa2ed857eed83 SHA1: 28cc20ab900b0475900bb38714f2316a5f4b5231 MD5sum: 792da309271c0646cfc6fa9b3554a915 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig1-dbg Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 373 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 118266 SHA256: 4e27b8b8b9011ac0025cc506d9ba8a7180eba6a1cfd42ea80daefbed007bbc30 SHA1: 67546d3a1782c277f0881e73fdd7682fa5ac4551 MD5sum: 4e8f6c1e6c99cd728f2aa9399a82f0ac Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED . . This package provides debug symbols. Package: libglew1.9 Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 632 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Suggests: glew-utils Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglew1.9_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 173972 SHA256: 309227756d4a317e9f5651b35c2ec3ed370a932523e278bf50f60828859cc7b1 SHA1: c049a94211b8f54a32d0e49e8493af093f2e9dbd MD5sum: 930b0e7744818bce03c692c6fc44b3c9 Description: OpenGL Extension Wrangler - runtime environment For more information about GLEW please refer to the description of the libglew-dev package. . This package contains the runtime support files. Package: libglew1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 149 Depends: neurodebian-popularity-contest, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglew1.9-dbg_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 41082 SHA256: 42cf1240768081c1631851b9ad9b58d36da62274a06b6cae73d3616c2e3506bb SHA1: 04a5d355b7449d0ae20c63d17807f99f63c3ea2c MD5sum: 75020909acc9729521894e9b72263a66 Description: OpenGL Extension Wrangler (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglew1.9. Package: libglew1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1000 Depends: neurodebian-popularity-contest, libgl1-mesa-dev | libgl-dev, libglew1.9 (= 1.9.0-3~bnd1~nd13.10+1), libglu1-mesa-dev | libglu-dev Conflicts: libglew-dev, libglew1.6-dev Provides: libglew1.5-dev, libglew1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglew1.9-dev_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 153240 SHA256: 70bd790b090cc50a23a0ffc02d9cad93136f5257c86a0b9694d079edf312cfed SHA1: 54b3ac933a0166f14bef2b41acd3dba00a5c56eb MD5sum: ebc5e67ddc5a14d69c17e7fc33570e13 Description: OpenGL Extension Wrangler - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development documentation as well as the required header files. Package: libglewmx1.9 Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 555 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), libgl1-mesa-glx | libgl1 Conflicts: libglew1 Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libs Filename: pool/main/g/glew/libglewmx1.9_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 158202 SHA256: fb0cdff05bf1689780498437c9bacf525f6206ac9c5f443ebf0bcc1691e77d48 SHA1: 700cb6509f12f853a896096750a67e3c8ef0f13e MD5sum: 8148032fb25345041054f8ac4f5acef9 Description: OpenGL Extension Wrangler (Multiple Rendering Contexts) For more information about GLEW please refer to the description of the libglewmx-dev package. . This package contains the runtime support files, built with GLEW_MX option, adding support for thread-safe usage of multiple rendering contexts. Package: libglewmx1.9-dbg Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 122 Depends: neurodebian-popularity-contest, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.10+1) Homepage: http://glew.sourceforge.net Priority: extra Section: debug Filename: pool/main/g/glew/libglewmx1.9-dbg_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 33058 SHA256: 94b3a21c091fce21495ac6ca26f0c7eb4ebf1d8c4945b8716f8254189920b26c SHA1: acbdf4a22edd068cfcde306b31c5573213be8324 MD5sum: 33354fac0242ca753417e1829c087ecf Description: OpenGL Extension Wrangler MX (debugging symbols) The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the debugging symbols for libglewmx1.9. Package: libglewmx1.9-dev Source: glew Version: 1.9.0-3~bnd1~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libglew1.9-dev, libglewmx1.9 (= 1.9.0-3~bnd1~nd13.10+1) Conflicts: libglewmx-dev, libglewmx1.6-dev Provides: libglewmx1.5-dev, libglewmx1.6-dev Multi-Arch: same Homepage: http://glew.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/g/glew/libglewmx1.9-dev_1.9.0-3~bnd1~nd13.10+1_amd64.deb Size: 8836 SHA256: be6fe3cc014d9e216be1baf4f18c1fbf80b54db607824004fdd1d67f6ea276c3 SHA1: 2d259b8e72454d4b086e9814cae3f5699278912e MD5sum: 947e9c2db5108de2b0b45f0a1be900a0 Description: OpenGL Extension Wrangler MX - development environment The OpenGL Extension Wrangler, GLEW for short, is a library that handles initialization of OpenGL extensions in a portable and simple way. Once the program initializes the library and checks the availability of extensions, it can safely call the entry points defined by the extension. Currently GLEW supports almost all the extensions found in the OpenGL extension registry (http://www.opengl.org/registry). . This package contains the development libraries compiled with GLEW_MX. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libdevel Filename: pool/main/m/mcpanel/libmcpanel-dev_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 2408 SHA256: 577b75bd54e2107375d8b9c7c060e62129f4eef124bcd0495483ad15c4d3e938 SHA1: c1c910854a377441a8a2a611f61256da0d599d21 MD5sum: 47fa076c405b3372e9a1ecf295f68abc Description: Library to display multichannel data in realtime (Developement files) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the files needed to compile and link programs which use mcpanel Package: libmcpanel0 Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 140 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.37.3), libgtk2.0-0 (>= 2.14.0), libpango-1.0-0 (>= 1.14.0), librtfilter1 (>= 1.0) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: libs Filename: pool/main/m/mcpanel/libmcpanel0_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 48962 SHA256: 886900174a33744124b1c6c7f171a58543239938b39d14222cf24cb5618c9161 SHA1: c8bc2f78cc587fa9682033d6c0d50f8b0b5669ca MD5sum: 4dc13563a72d9824d8c49b6dc13f2d94 Description: Library to display multichannel data in realtime This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. Package: libmcpanel0-dbg Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 21 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://cnbi.epfl.ch/software/mcpanel.html Priority: extra Section: debug Filename: pool/main/m/mcpanel/libmcpanel0-dbg_0.0-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 6822 SHA256: 0a291e656745de31dc07174a44087d1da8ff321d2f29886a1c56b1ed278ed2fb SHA1: 75d5fc7788319657a0acd7f5b2df57d5980fe654 MD5sum: 7bf0a2d611c41ab58f10b2649d24aaa3 Description: Library to display multichannel data in realtime (Debugging symbols) This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful. . This package contains the debugging information of the library. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 174234 SHA256: e809cc49a42a1a44c85b9d23c387edd5dd6e79174a772e960800c098967d4697 SHA1: fed6b906ef0b4699ecad0b144c29311ecea61e4e MD5sum: 1b6f50f2e58f4cf6c094bd730ae91479 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 523 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 178580 SHA256: 94ef5bf17707ae55a67161a07499bbfd71c8ab812699fdabdaff16ebdc3c3b23 SHA1: 44c9c604af8935bf078bc360ac66ea271760c9f0 MD5sum: f63d8682d6851c28a61c527f85b69602 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1311 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 425038 SHA256: 94d0fd991e7727086cc4d9f9d53d2cc3b565b8af77bd9035a494f1b83b058605 SHA1: 3e68fa4db0361bd8daf2d89b64fa94e203f9bd7e MD5sum: c14b5fe7c0551553bc44a74378b343bf Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 15759 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_amd64.deb Size: 5065264 SHA256: 90a86a6e80b434821be2b2b188441d2934f1eb14cb6d4c404fff761f69aa56c6 SHA1: ea193051ae875e88aa038ef98d5503a8e3bb30a6 MD5sum: 4d70bbd7389052fd438fea743f5acecd Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1678 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1664274 SHA256: 68ce273dcde27c573053b0978397336aee2bd4bd411278f9950e11a9aac27989 SHA1: 3e484323149fadfcff8ba1c124dc23cb188c9cf6 MD5sum: 895c3045ff8a360f730cb00692214f7f Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 980 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20130828.1~dfsg.1-1~nd13.04+1+nd13.10+1_all.deb Size: 735992 SHA256: e5a580a7bae121b13d1e22d622c6de9466ca7e01fe5abc460fe3285906c721f5 SHA1: f39199a65bb18cded064d3123319184a4c9e6878 MD5sum: 92dbcb21cb1674db34d549b65a2c61d7 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.11-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 8180 Depends: neurodebian-popularity-contest, libatkmm-1.6-1 (>= 2.22.1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.36.2), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.24.0), libsigc++-2.0-0c2a (>= 2.0.2), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.11-1~nd13.04+1+nd13.10+1_amd64.deb Size: 2600252 SHA256: f98a8ac1054926435a7f5086ce2f40843e43ef0333a83b8d2fd54a7668641ff9 SHA1: 7ba85d16e475f87157575cb0b38dfc93ced3dd61 MD5sum: 3ef9b1867c176edd2e6207d3c8a05084 Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.11-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3488 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.11-1~nd13.04+1+nd13.10+1_all.deb Size: 3315566 SHA256: 71442f92e14e7d4a7ede19192c4f90b7b499f2d970d23f243034a52a035cb1e9 SHA1: 93ff9dbf790cd956cdab14959d4a968a5145ba5a MD5sum: d62cbb6f62b76dbb3c632b95ec797787 Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: neurodebian-desktop Source: neurodebian Version: 0.31~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 142 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.31~nd13.10+1_all.deb Size: 115336 SHA256: 5dbbcc84a873e21e10b4d7c5ba42a52ab31d0ee0fb2bc8975c66dc110c80061c SHA1: c998033c1f2ae3b68c70aeefc99e6ed3f77869ca MD5sum: 973c265a07811be91fc4754d4c89933e Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.31~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5762 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.31~nd13.10+1_all.deb Size: 5351226 SHA256: 9bd320f46429342abdc200dd6990b00246af500ea64dc2301a64ca6803684a74 SHA1: cf3fd7e2c166637cc0142ffb7deb36597629bf8e MD5sum: d8c371a7f43b47beb3a239ed0c324b48 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.31~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 107 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | lightdm, zenity Recommends: chromium-browser, update-manager-gnome, update-notifier Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.31~nd13.10+1_all.deb Size: 15202 SHA256: 2176f6fff4799fbd5fcba4a576178b0619c314228aba5b72ff2912edc6f58b7b SHA1: f2f01d08e4eaeec5c9fa856a7d3c70d321fe1b95 MD5sum: bd0d36386217e5ea16129fb436c73bb3 Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.31~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.31~nd13.10+1_all.deb Size: 7502 SHA256: 443aa7fa989cefb430ded4ae0264fae64e839454daa6fd72fb34ceb27fea501e SHA1: 9653a5650a676737f86d8ca5eaf660d3d544aa23 MD5sum: dd99d1f3c87ec9dac514d4923df75b66 Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.31~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.31~nd13.10+1_all.deb Size: 6714 SHA256: d04d58ffa40a5628189f4db6cd9db3948dc109dd443270a32e0950a341bd9cf5 SHA1: 3c2457fd0ce6291ce5b58313dd0bad76106fa103 MD5sum: 7bb58e0475b49422e4ab6076bb066f16 Description: Helper for NeuroDebian popularity contest submissions 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 (e.g. Debian or Ubuntu) popcon server. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . It has an effect only if you have decided to participate in the Popularity Contest of your distribution, i.e. Debian or Ubuntu. You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2203 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.3, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.6-2~nd13.04+1+nd13.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.6-2~nd13.04+1+nd13.10+1_amd64.deb Size: 473514 SHA256: 6608099072e85b0683e9f2db4edf81068727a7430560b64499f29ec89ca55f5a SHA1: 46184b35912bb132ee0fde0347f3f5aaca987162 MD5sum: f4a0f116f408b64550647ed1d6b3754e Description: convert 3D medical images to DICOM 2D series Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package includes the command line tools. Package: nifti2dicom-data Source: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 606 Depends: neurodebian-popularity-contest Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom-data_0.4.6-2~nd13.04+1+nd13.10+1_all.deb Size: 615226 SHA256: 0f0a456de3bee8393c788a8e386db5850e1114f6d0888aa2962aeaca3285701f SHA1: 1348f2d5aa245a47b7e921228df9d88801ea0037 MD5sum: 56b8ed8c1d235d57922f2fbda44bf0ed Description: data files for nifti2dicom This package contains architecture-independent supporting data files required for use with nifti2dicom, such as such as documentation, icons, and translations. Package: nuitka Version: 0.4.5.1+ds-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1793 Depends: neurodebian-popularity-contest, 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 (>= 2.7.1-0ubuntu2) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6) Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.4.5.1+ds-1~nd13.04+1+nd13.10+1_all.deb Size: 450068 SHA256: 145bf66b70faad7078317ea80c34f47e5df419494c84a962fb1016e54b780af4 SHA1: e8ccab3be9b5bf5ea366c653b9fa2a2c281c5896 MD5sum: a4496c3072e89e60b4430ada531d9ba1 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: numdiff Version: 5.8.1-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 898 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), dpkg (>= 1.15.4) | install-info Homepage: http://nongnu.org/numdiff/ Priority: extra Section: science Filename: pool/main/n/numdiff/numdiff_5.8.1-1~nd13.04+1+nd13.10+1_amd64.deb Size: 614266 SHA256: 362d66518be17dc07a2d1d070452cd1158e08d240f0534193bcf80a9f199dd56 SHA1: 37560d66ece72d0b9b935bcfc9be3d793e9bea01 MD5sum: 2095be117cb2d476e76194ab58e2a50c Description: Compare similar files with numeric fields Numdiff is a console application that can be used to compare putatively similar files line by line and field by field, ignoring small numeric differences or/and different numeric formats. It is similar diff or wdiff, but it is aware of floating point numbers including complex and multi-precision numbers. Numdiff is useful to compare text files containing numerical fields, when testing or doing quality control in scientific computing or in numerical analysis. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.14), liboctave1 (>= 3.6.2) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 23432 SHA256: 120f316c16bc30aeb0347413ad3915f8cbd1459cdb8ea7bb61cbf34ef9804f15 SHA1: 50efdc21843327f7035f9ba5d42d51cc891ce8a3 MD5sum: 70d7e51284d83ff2bd4be089f158bad3 Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2729 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.1 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglew1.9 (>= 1.9.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), liboctave1 (>= 3.6.2), libopenal1 (>= 1:1.13), libpciaccess0 (>= 0.8.0+git20071002), libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.11.20131017.dfsg1-2~nd13.10+1), psychtoolbox-3-lib (= 3.0.11.20131017.dfsg1-2~nd13.10+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.11.20131017.dfsg1-2~nd13.10+1_amd64.deb Size: 888700 SHA256: 6657d7654324ed97402207d87bfe271aa0acd356146016ec39ae7222a7bcffe4 SHA1: 408e37a65e4796fab05dbbeb3846fbdced897f21 MD5sum: c4ce7acb5ab965a2d29bdf5e9d756b34 Description: toolbox for vision research -- Octave bindings 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. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: opensesame Version: 0.27.4-2~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26639 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-qt4, python-pygame (>= 1.8.1~), python-numpy (>= 1.3.0~), python-qscintilla2, gnome-icon-theme Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1), expyriment (>= 0.5.2), ipython-qtconsole (>= 0.12), python-markdown Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.27.4-2~nd13.04+1+nd13.10+1_all.deb Size: 25359292 SHA256: 7eb6ad30eac4d0899910debe19d8f7d67bc93d31570781782b9c297f0ed84053 SHA1: 1f09336470b48636de42f67e545284e24f6b15ef MD5sum: 076b71a8a142d25cbc32e85c9e11720f Description: graphical experiment builder for the social sciences This graphical environment provides an easy to use, point-and-click interface for creating psychological experiments. In addition to a powerful sketchpad for creating visual stimuli, OpenSesame features a sampler and synthesizer for sound playback. For more complex tasks, OpenSesame supports Python scripting using the built-in editor with syntax highlighting. Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49635 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_3.0.11.20131017.dfsg1-2~nd13.10+1_all.deb Size: 19937316 SHA256: 1d633396593cd68aee1f7aedfd2f627c93fe031b87bee46eca446b19e5dbbc30 SHA1: e91de726712bc8e2c5710b1afb72e7e533c053c0 MD5sum: 37b535b8bc0512f543a8b4b06df40d98 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: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2290 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.11.20131017.dfsg1-2~nd13.10+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.11.20131017.dfsg1-2~nd13.10+1_amd64.deb Size: 787656 SHA256: 2dfa8bdc0178451626850c7afc94350ac1c84b8d4bc734247fde75c8c6d405bd SHA1: da685a88119bc4e71d4e37f6af93d60549eb5e70 MD5sum: cc7642f8af32ce83f193608002e587a7 Description: toolbox for vision research -- debug symbols for binaries 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. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.11.20131017.dfsg1-2~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 153 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer0.10-plugins-base, gstreamer0.10-plugins-good, gstreamer0.10-plugins-bad, gstreamer0.10-plugins-ugly Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.11.20131017.dfsg1-2~nd13.10+1_amd64.deb Size: 65212 SHA256: 08eeb18d2e0e74b0c1cc2078b7716639f72711571591e14546d3893a107d4a9d SHA1: 203773e147964acf8fa766171b087213b9f4deea MD5sum: 26317707df9e982496370423800bdc0d Description: toolbox for vision research -- arch-specific parts 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 additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.14), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_1.4.1-1~nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 55728 SHA256: 26bf45ea5650683097e5f28c8ac896276f23a955bc426ab78723454679b0a09a SHA1: aeb4806dccf57764c7a060b2b9abb73920364bb8 MD5sum: cd4ad60656165407237a97c42929f869 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2336 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.1-1~nd13.04+1+nd13.10+1), python-matplotlib (>= 0.90.1), python-numpy (>= 1.3.0), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose, python-cherrypy Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 549212 SHA256: 988ae070c4a1f6ff509598736733a666ccf337407b9f1b54fe51dcc41f453071 SHA1: c0d825559c7fa6cc94df99326cd0bf135b9af3d2 MD5sum: 19b10c71f6878e6e0ca5eea1637284fe Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6810 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.4.1-1~nd13.04+1+nd13.10+1_all.deb Size: 2247326 SHA256: 02613c13a722df13156e9ae18dfaa9328810fca303950ba19a1356da2a77a3a7 SHA1: 4341f8754a618702eb2f745017fc50c57b88b2e6 MD5sum: 90d9953badd70e123284cef6b7fb2904 Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML format), examples and demos. Package: python-brian-lib Source: brian Version: 1.4.1-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 141 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python-support (>= 0.90.0), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.4.1-1~nd13.04+1+nd13.10+1_amd64.deb Size: 54362 SHA256: d5d3c651e2047c910ad250829356de15b30bbd77936651127bfbbde3be6f9dd0 SHA1: 677c5e2cea666d230a30f0a946c94a49c8b5a781 MD5sum: 55c3d690c0d003321fd65aa93156eebc Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-joblib Source: joblib Version: 0.7.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 182 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.7.1-1~nd13.04+1+nd13.10+1_all.deb Size: 54902 SHA256: 8da3ca02ba5ac7b0ef34f0b086d3e687788a3ac689f9d9ee53d36ec03c720928 SHA1: 89ecf1f16e6ef9b552359f960e5a4ebe10c3a8fa MD5sum: 896e7ee9f14eff60a67380bde75474f3 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1495 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-scipy, python-libsvm, python-joblib, python-scikits-learn | python-sklearn, python-pp Suggests: python-py, shogun-python-modular Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 478670 SHA256: dcbf8dcbd35c93951698aa8a700355c7f7df66000b6e7e4b42432fef2a273b63 SHA1: 47eb8ef49afe92e183de028ecbe170ccc8227fad MD5sum: 3e08fab66beaacec7b7071b569c74ded Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 2. Package: python-neo Source: neo Version: 0.3.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2485 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Suggests: python-nose Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.3.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1441986 SHA256: ec381fea8a1c2ad6d8301f88c0ca4362cbbbab180c6e618772181f5b4055fd62 SHA1: 7ae0814b66bf4f821fbb042de12c70a6cd53b3e0 MD5sum: cfd02e2d5a37dcf504472f5f31e11f67 Description: Python IO library for electrophysiological data formats NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples. . NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab). . Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement. Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), 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~nd13.04+1+nd13.10+1_all.deb Size: 32584 SHA256: e38eecc0a3733f22718924755061092da20b4ce592bc1f0044cc0fcd3b5d946e SHA1: acb8d58022eca092a686c7665b5225fca8074794 MD5sum: 3eedb70c2ed5b4a73f58c6b2981af4f0 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-nibabel Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Provides: python2.7-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 1816464 SHA256: 1e268bf6e0aedbb094d99515235bca7859435018effc35b32c1ad61bc8f45576 SHA1: b446856aaabf44b569c5fb168697b97baafc6fb2 MD5sum: 9fc3310c254316621359200032f71b23 Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Python-Version: 2.7 Package: python-nibabel-doc Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2446 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.3.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 441902 SHA256: 024cc31c57fad25b7ece5bf111183562ed9f306c69b9c615ada8252c8ae51f5f SHA1: 34c515cf5d1ec4eda26a1be813c65d420e3f22a0 MD5sum: 282caebc75ef0933a993491196a60143 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-openpyxl Source: openpyxl Version: 1.6.1+hg2-g4bff8e3-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 291 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.6.1+hg2-g4bff8e3-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 62128 SHA256: fa92d9eb0ad016916bcfcaf44f61a414f6aae4ce44c7b724073ac3f3f2ca2a6a SHA1: 074d32f31042fea4167b9cd1e6296791ba9b2eac MD5sum: 67acd033409ce48456ba928c8be5f618 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-patsy Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 542 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy Recommends: python-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.2.1-2~nd13.10+1_all.deb Size: 141566 SHA256: 129dbb8c395d3ec89e03e9a07c950a52657450af33b3a29987f9643a54ca5427 SHA1: bf09927d1ada6b8c4fa217cb8931cff0a5f27b98 MD5sum: 1e7166dbc44ab5325bf9e4c1bafe79c0 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 827 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.2.1-2~nd13.10+1_all.deb Size: 271938 SHA256: 961ceeb48ffbeaaff905d26aee5fc323e3f1b06cc466cd8a349f03daaf930aed SHA1: 553e1c06cd178a1c78962fcce0903dec8d2a5e5a MD5sum: b31d6af765cda6ad2f0ff8ff085917cd Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1378 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd13.10+1_amd64.deb Size: 383450 SHA256: fad6d5f996efe2506be7a95621cf1d83f5850e93dbe43abc8f8478e998e25efb SHA1: fa14d74bf559ab3d76cac3868a6a8f9b199032f0 MD5sum: 70f8eeb895e8123720b6d7a39f8bcf9c 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 PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 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~nd13.10+1_all.deb Size: 818248 SHA256: 9ce8e6041a5deeccea8c28454166623b53d9a571d442a63bc8844c07dd698293 SHA1: 90dc97067b797c017c9da331c41ed24072f8d156 MD5sum: d3ec7da2336f2e9e5ab0cff98c32ebaf 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-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 175892 SHA256: 0490096bb6a4e6d5ed2ec0e77261346c947d46d28d86acd3bb617c35ad3f10d2 SHA1: 0573a0e1d66e53f5af548774aae5578cc3346cc3 MD5sum: 908111812c3b5221360aff3852de45a8 Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1599 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.6), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 447696 SHA256: 2c4320663cdec4fe767294e1770c1b20a44b3d5d3cdef73f4df3fb263d440e52 SHA1: 79684ae0ac5bbb9048d3dad2b43f344d3a1c6a6d MD5sum: bd25900887fa524e8bd1c13e54804d89 Description: psychometric analysis of psychophysics data in Python Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers: . * full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment * identification of influential observations and outlier detection * flexible shape definition of the psychometric function . This package provides the Python bindings. Package: python-pyxnat Source: pyxnat Version: 0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 862 Depends: neurodebian-popularity-contest, python-lxml, python-simplejson, python-httplib2 (>= 0.7.0) Recommends: python-networkx, python-matplotlib Homepage: http://packages.python.org/pyxnat/ Priority: extra Section: python Filename: pool/main/p/pyxnat/python-pyxnat_0.9.1+git39-g96bf069-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 190426 SHA256: 5854904257cb3119ee3d4389a93ef91f6d0b09cb8761ad8202ad2871c93c79b5 SHA1: ab34bd5639fc33e6891167d65f60d00d368405b5 MD5sum: 3e607b3d81f724a53cce9d8e07b15a74 Description: Interface to access neuroimaging data on XNAT servers pyxnat is a simple Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or Python scripts to process the data. It features: . - resources browsing capabilities - read and write access to resources - complex searches - disk-caching of requested files and resources Package: python-scikits-learn Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 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_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 33394 SHA256: c5c4921959294695cc1786c21f6a4221e9643c4a37dd2eb00c4fde018b09c98e SHA1: 69e189ae57b2d9d71d6163d3cad67ac43cc41b07 MD5sum: 3d82217021f148a186e7a70eabaea5ad 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-scikits.statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9 Depends: neurodebian-popularity-contest, python-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: oldlibs Filename: pool/main/s/statsmodels/python-scikits.statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 5690 SHA256: 32c363d5c9c614e8dc79f3e4416b5f5f130a1a14bc01a655340725b9debc7732 SHA1: 31cc26d464f24154400ac5af0077098c538e3903 MD5sum: a0418afa93e68377deca41d04268bd03 Description: transitional compatibility package for statsmodels migration Provides old namespace (scikits.statsmodels) and could be removed if dependent code migrated to use statsmodels for clarity of the namespace. Package: python-sklearn Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3549 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-sklearn-lib (>= 0.14.1-1~nd13.04+1+nd13.10+1), python-joblib (>= 0.4.5) 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_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 1103724 SHA256: e9dd3918afc487965fa705fcf6833913aeab546ec8360f0f7dd40f476e96e382 SHA1: 907583b96f7ca554661469323cdd9d604f0a31be MD5sum: 682700752ca3096fbfef096744e44581 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: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 579 Depends: neurodebian-popularity-contest, libjs-jquery 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_0.14.1-1~nd13.04+1+nd13.10+1_all.deb Size: 190084 SHA256: a8ff6e017748e6a98c998dc6f9967700c97ad590da834c76fe4f1f340340bd35 SHA1: d84325dd92092e8afc55efd278b283734b37de2a MD5sum: e613e6e4a1d3fd2bb50f2d8d7c0ac6db Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.14.1-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3802 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.14.1-1~nd13.04+1+nd13.10+1_amd64.deb Size: 1506308 SHA256: 85afc04bd610647ba3ad5bb795b612af1a76457823cc39b068d5eeff059f7fa8 SHA1: 93e3ffcdee0f5ad8aa1b1ea7c84f61fc714f4211 MD5sum: 305705df714f4d903e22530df6146f2a Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-spykeutils Source: spykeutils Version: 0.4.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2018 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-scipy, python-quantities, python-neo (>= 0.2.1), python-nose, python-sphinx Recommends: python-guidata, python-guiqwt, python-tables, libjs-jquery, libjs-underscore, python-sklearn (>= 0.11), python-joblib (>= 0.4.5) Provides: python2.7-spykeutils Homepage: https://github.com/rproepp/spykeutils Priority: extra Section: python Filename: pool/main/s/spykeutils/python-spykeutils_0.4.0-1~nd13.04+1+nd13.10+1_all.deb Size: 401644 SHA256: 602a18a5f0d14a20169f4ee7aed21ce25645fcfe8d8668731c99a71b25f1b2b2 SHA1: 6a95e964f341f0950776a46e9abad5cc30a36c82 MD5sum: b1e989f4caccc9d2ef07a86391511353 Description: utilities for analyzing electrophysiological data spykeutils is a Python library for analyzing and plotting data from neurophysiological recordings. It can be used by itself or in conjunction with Spyke Viewer, a multi-platform GUI application for navigating electrophysiological datasets. Package: python-statsmodels Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20496 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-numpy, python-scipy, python-statsmodels-lib (>= 0.5.0-1~nd13.04+1+nd13.10+1), python-patsy Recommends: python-pandas, python-matplotlib, python-nose, python-joblib Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Provides: python2.7-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 4690538 SHA256: 38a545728cb1df2d44d1fc3579354ddfe8b89c5f207ece0cd3b2b68175730d29 SHA1: 95347b8acb0ef160eea8eb223ef7ec8d4d46f0ed MD5sum: d7b2743076ae1cc2f1aadfa920e3b4ec Description: Python module for the estimation of statistical models statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. Package: python-statsmodels-doc Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 31202 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-statsmodels Conflicts: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: doc Filename: pool/main/s/statsmodels/python-statsmodels-doc_0.5.0-1~nd13.04+1+nd13.10+1_all.deb Size: 9240594 SHA256: afc8c22ea8bad165091cb11c971caaf688a39748726afc7430379266cbd8220a SHA1: d7f880340bf05c73be55fe618e1ce0706681724a MD5sum: 8a8961c09b31992954ac76ce98daf033 Description: documentation and examples for statsmodels This package contains HTML documentation and example scripts for python-statsmodels. Package: python-statsmodels-lib Source: statsmodels Version: 0.5.0-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 359 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Conflicts: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Replaces: python-scikits-statsmodels, python-scikits.statsmodels (<< 0.4) Homepage: http://statsmodels.sourceforge.net/ Priority: extra Section: python Filename: pool/main/s/statsmodels/python-statsmodels-lib_0.5.0-1~nd13.04+1+nd13.10+1_amd64.deb Size: 103894 SHA256: 2fe899cc1513e6892ed43ed36333ff6adf2d5a8d5f334c975ff587e597c43a5b SHA1: 6c855edaeef80233633d581d440c56a30804395b MD5sum: d6029c7b542ba28c0ea5a278ea880c28 Description: low-level implementations and bindings for statsmodels This package contains architecture dependent extensions for python-statsmodels. Package: python-stfio Source: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 829 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python:any (>= 2.7.1-0ubuntu2), libbiosig1, libc6 (>= 2.14), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libhdf5-7, libpython2.7 (>= 2.7), libstdc++6 (>= 4.2.1) Recommends: python-matplotlib, python-scipy Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.13.2-1~nd13.04+1+nd13.10+1_amd64.deb Size: 274420 SHA256: acec8f41b9d6ac292d91578ee512a845490ed8bc9d7feeff35fbc68986475905 SHA1: f2edc67bd72463fc815fbe48ebb3cd99920512f6 MD5sum: c08b23eb19fe7b56d9411ac71da518a0 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-surfer Source: pysurfer Version: 0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-nibabel, python-imaging, mayavi2, python-argparse, ipython Recommends: mencoder Homepage: http://pysurfer.github.com Priority: extra Section: python Filename: pool/main/p/pysurfer/python-surfer_0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28156 SHA256: 50ddfd6a338724eef65c70fdf5accda6cb4138a4a880812d575a3a24c82e0f4e SHA1: 3dd5e53ea0d12307cf09854ee4857f26557ed6e5 MD5sum: 5e15b6ff76d04fb48b8d45537ef67a97 Description: visualize Freesurfer's data in Python This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data. . PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets. Python-Version: 2.7 Package: python-traits4 Source: python-traits Version: 4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 1683 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0) Suggests: python-traitsui Conflicts: python-traits (>= 4.0~) Homepage: http://pypi.python.org/pypi/traits Priority: optional Section: python Filename: pool/main/p/python-traits/python-traits4_4.0.0-1~cbp1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 344276 SHA256: 3e3a1b187e0f7733282a374fd6640f396343c9cca69f80d324efdd792de1f2a2 SHA1: 1ba6fe60451f242edc1e65635e82804cb7aac8bf MD5sum: 747b9dd980e94e61c9f69e945734f72d Description: Manifest typing and reactive programming for Python The traits package provides a metaclass with special attributes that are called traits. A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics: * Initialization: A trait attribute can have a default value * Validation: A trait attribute is manifestly typed. * Delegation: The value of a trait attribute can be contained in another object * Notification: Setting the value of a trait attribute can fired callbacks * Visualization: With the TraitsUI package, GUIs can be generated automatically from traited objects. Uploaders: Yaroslav Halchenko , Michael Hanke Vcs-Browser: http://git.debian.org/?p=pkg-exppsy/python-traits4.git Vcs-Git: git://git.debian.org/git/pkg-exppsy/python-traits4.git Package: python3-mdp Source: mdp Version: 3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1457 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python3-mdp_3.3+git6-g7bbd889-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 472732 SHA256: 34d326fd987ac56b05616b45fdf1a1feee5c3cee4851ed34e871d9a8ef1ddf49 SHA1: 0191963e9dfae4b7b3dfe58d707a3114399d19f9 MD5sum: 2601097ca9fcd09b10342a784917d739 Description: Modular toolkit for Data Processing Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. . This package contains MDP for Python 3. Package: python3-patsy Source: patsy Version: 0.2.1-2~nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 535 Depends: neurodebian-popularity-contest, python3-numpy, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.2.1-2~nd13.10+1_all.deb Size: 140384 SHA256: 240fefb22e743b5a444acad849e63ae4701920fb3c7fa6cba885e0f9744ec338 SHA1: b0dbd969743a2cc6d89044af4e6575fc21f0cdef MD5sum: 3350a251e0975db1c5b799599cf525c1 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.6-2~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3131 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit4.3, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4, nifti2dicom (= 0.4.6-2~nd13.04+1+nd13.10+1), nifti2dicom-data (= 0.4.6-2~nd13.04+1+nd13.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.6-2~nd13.04+1+nd13.10+1_amd64.deb Size: 661134 SHA256: 54e3c050ac5ce2d6aeeffb944b54bfec1f2ee77b96d67c61bf18663e7d7cad18 SHA1: 9edcb282733d74370f1339bac139362488c0ac11 MD5sum: b4fdf5446f01da2e1ee89dc8662463a0 Description: convert 3D medical images to DICOM 2D series (gui) Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS. . This package contains the Qt4 GUI. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 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~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 10744052 SHA256: 05f7ef0de3af1f49c7f7dafba91b9d8f5f082bd48ad7acd365a89a105fcd6c71 SHA1: 829ef9f220b3a9595b3acdb7ada1bedcdfdbc378 MD5sum: 137a219ff42452e9439fe275cb949cc3 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~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 52166702 SHA256: 85b2c5e9081fd7cf506defb5327413d0222f01f3b7e6fd959e5e2ccf8d83000c SHA1: 8a53b81d37062647c56fac6117a589fb776bbac5 MD5sum: 9d6cae39f3455ec2cc5a2f3ccf8b002d 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~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 8990912 SHA256: a35cf1eaaf17c77bc2c148da711ed2d386131f25f4ea98c326b36ee3a0867e07 SHA1: a21337c1d47d0ae2b39bcabb477ecbdf0fdff4f0 MD5sum: e7247d37c03ce8eafa3ae5e619c752a2 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: spykeviewer Version: 0.4.0-1~nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1120 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-guidata, python-guiqwt (>= 2.1.4), python-spyderlib, python-spykeutils (>= 0.4.0), python-neo (>= 0.2.1), python-matplotlib, python-scipy, python-nose, python-sphinx, python-tables Recommends: libjs-jquery, libjs-underscore, ipython-qtconsole (>= 0.12) Homepage: http://www.ni.tu-berlin.de/software/spykeviewer Priority: extra Section: python Filename: pool/main/s/spykeviewer/spykeviewer_0.4.0-1~nd13.04+1+nd13.10+1_all.deb Size: 575306 SHA256: 959cbfd23cf8d7761d77fac41530d08a428c4f4a773f411acb5e26ecb6e5d507 SHA1: c639d49e4fe954f60c40dbccb74e9c158da58912 MD5sum: cb9540ab965b6ba06bbab01ed8f3d8b3 Description: graphical utility for analyzing electrophysiological data Spyke Viewer is a multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets. Based on the Neo framework, it works with a wide variety of data formats. Spyke Viewer includes an integrated Python console and a plugin system for custom analyses and plots. Package: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 28850 SHA256: 2885d99daf2891a6f2fe488f25d5f54002ff6d6df0252f5e946ceff1f20e452b SHA1: a9e67198cec5f15cc2bc910b9a9fdbb90f7f40ac MD5sum: 505b20b36e42d72d4d7ca1bc051d90b5 Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2485 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.14), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-7, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.4.0), libwxbase2.8-0 (>= 2.8.12.1), libwxgtk2.8-0 (>= 2.8.12.1), python-numpy (>= 1:1.7-0~b1), python-numpy-abi9, python2.7, python:any (>= 2.7.1-0ubuntu2), python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.13.2-1~nd13.04+1+nd13.10+1_amd64.deb Size: 841648 SHA256: 73c854ef467145fdb8ec3cc3e70097555ff30d9f9762d1c984d69892d2cddfef SHA1: beffdabe27905d4465c08d5f70173cf4449f1e72 MD5sum: fecb2c25295eb4a57c158eace450c4c6 Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.13.2-1~nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 17651 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.13.2-1~nd13.04+1+nd13.10+1_amd64.deb Size: 5387378 SHA256: e6e7e0c02f856a434f3ae77212abc6c46ec397c079c9914ffd0da66b5bb740fa SHA1: a0d4e9ee3b3f0087a6da0a89d8fd4e9c187eaeea MD5sum: 8a4aa2f7919d4fed5680e31cd7a7ac46 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1_all.deb Size: 99698 SHA256: 40b0868fbb47a9758a535769ae6eaac9e3ec55f0c3b39557f43303f5fe8dd0b3 SHA1: 3ca2b3698fcbc13058665807cb8ffc9ad4fd25d9 MD5sum: a6c94efec638cee547260e58486ee71a Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 315 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 64946 SHA256: 8994a130c17ba2879a01c0748788859acf069220c616eb3379a263a9c1068031 SHA1: a2317e6db3e151987547acd6125bb3583bf0358f MD5sum: 4f2dcf627617a1f943eb1d92a9e7b41e Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5250 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1_amd64.deb Size: 1660132 SHA256: 4cbf851620942bf91d36c9b158ca91792c95027589e893aea9aa807c28594c45 SHA1: a3f27279eb53aeec38e246c543c2d7ed2c6ecb24 MD5sum: 2641aed58403c577b3d907d061e1f955 Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables.