Package: aghermann Version: 0.7.1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1131 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp7, libpango1.0-0 (>= 1.14.0), libstdc++6 (>= 4.6), libunique-3.0-0 (>= 2.90.1) Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_0.7.1-1~nd12.04+1+nd12.10+1_amd64.deb Size: 505786 SHA256: d22619578e8169aefff693021add6c366e1555b8873c675d48af6f75bd9f126f SHA1: cdb30e5f833199fc76026c489e02f50228c6329d MD5sum: 95c4be8c9bdc73d04796e94c344d0bf6 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility, EEG power spectrum and power course visualization, and Process S simulation following Achermann et al, 1993. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 667 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_amd64.deb Size: 282682 SHA256: d2b094e16b8fb5bea06912d3e553449b5054264d351f188f6836091dd4559665 SHA1: d5fec10cba69b5a0bf0272cba8260296c5e7b550 MD5sum: bddfc5782565a472503063b650c38905 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: cmtk Version: 2.2.6-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 23320 Depends: neurodebian-popularity-contest, libbz2-1.0, libc6 (>= 2.14), libdcmtk2 (>= 3.6.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.2.1), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 4.6), zlib1g (>= 1:1.1.4) Recommends: sri24-atlas Suggests: numdiff Homepage: http://www.nitrc.org/projects/cmtk/ Priority: extra Section: science Filename: pool/main/c/cmtk/cmtk_2.2.6-1~nd12.10+1_amd64.deb Size: 6252180 SHA256: bc6c63006c6280a21fa8f1f498cdd1de1bde3af06d2e9292e83adb2f4c167f58 SHA1: b7ad77116a9a67d1d51a66219cef966ca10024bc MD5sum: 754e5cf06a854ad7b5a34bb34c8dd0f8 Description: Computational Morphometry Toolkit A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O. . The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear regression). Package: cnrun Version: 1.1.13-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 475 Depends: neurodebian-popularity-contest, libboost-regex1.49.0 (>= 1.49.0-1), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libreadline6 (>= 6.0), libstdc++6 (>= 4.6), libxml2 (>= 2.6.27) Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun_1.1.13-1~nd12.04+1+nd12.10+1_amd64.deb Size: 179100 SHA256: e21a94911aac3007e700fc92a09cec1ec995b0fa75d828e48b4c716e01d87713 SHA1: 2f323194f53041503e275f5e645838454dc6b51c MD5sum: 863ddb20bf3d0793c988c3ab9e522a75 Description: NeuroML-capable neuronal network simulator CNrun is a neuronal network model simulator, similar in purpose to NEURON except that individual neurons are not compartmentalised. It can read NeuroML files (e.g., as generated by neuroConstruct); provides a Hodgkin-Huxley neuron (plus some varieties), a Rall and Alpha-Beta synapses, Poisson, Van der Pol, Colpitts oscillators and regular pulse generator; external inputs and logging state variables. Uses a 6-5 Runge-Kutta integration method. Basic scripting and (if run interactively) context-aware autocompletion. Package: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 14689 Depends: neurodebian-popularity-contest, debconf (>= 0.5) | debconf-2.0, libc6 (>= 2.14), libclassad3, libcomerr2 (>= 1.01), libcurl3 (>= 7.16.2), libexpat1 (>= 2.0.1), libgcc1 (>= 1:4.1.1), libglobus-common0 (>= 14), libglobus-ftp-control1 (>= 4), libglobus-gass-transfer2 (>= 7), libglobus-gram-client3 (>= 12), libglobus-gsi-credential1 (>= 5), libglobus-gsi-proxy-core0 (>= 6), libglobus-gsi-sysconfig1 (>= 5), libglobus-gss-assist3 (>= 8), libglobus-gssapi-gsi4 (>= 10), libglobus-io3 (>= 9), libglobus-rsl2 (>= 9), libglobus-xio0 (>= 3), libgsoap2, libk5crypto3 (>= 1.6.dfsg.2), libkrb5-3 (>= 1.10+dfsg~), libldap-2.4-2 (>= 2.4.7), libpcre3 (>= 8.10), libssl1.0.0 (>= 1.0.0), libstdc++6 (>= 4.6), libuuid1 (>= 2.16), libvirt0 (>= 0.5.0), python, perl, adduser, libdate-manip-perl Recommends: dmtcp Suggests: coop-computing-tools Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/condor_7.8.6~dfsg.1-1~nd12.10+1_amd64.deb Size: 4904094 SHA256: 25cf73673275ea544e1842a72d71a5beae20f5851a6165eb8e9603ee69072e35 SHA1: fc6850be8c2c3117dccb3619e1f5dc8b8ca5e43b MD5sum: 7aeab11943227974ccff40f55c5e48ac Description: distributed workload management system Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package can set up an appropriate initial configuration at install time for a machine intended either as a member of an existing Condor pool or as a "Personal" (single machine) Condor pool. Package: condor-dbg Source: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 35911 Depends: neurodebian-popularity-contest, condor (= 7.8.6~dfsg.1-1~nd12.10+1) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: debug Filename: pool/main/c/condor/condor-dbg_7.8.6~dfsg.1-1~nd12.10+1_amd64.deb Size: 12363140 SHA256: 89ed7531dcecf7ed21aefc28fb78dcda7a568d7bbfb8f9affb8656d7e8ce8a0f SHA1: ebef12f6f48be9285bafd071e2f537dee4f326e0 MD5sum: 9005ad6ecabb2a86e76224905fd5a233 Description: distributed workload management system - debugging symbols Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides the debugging symbols for Condor. Package: condor-dev Source: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2035 Depends: neurodebian-popularity-contest Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: devel Filename: pool/main/c/condor/condor-dev_7.8.6~dfsg.1-1~nd12.10+1_amd64.deb Size: 460372 SHA256: 15fcd7185356e476187f9c998f591b069255003d970f50a79da5d6dec383cdc3 SHA1: 09798b551a77dca573c39fdac90643123e4debcf MD5sum: 425ca9b9983ab9de6148f2b8edcac308 Description: distributed workload management system - development files Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides headers and libraries for development of Condor add-ons. Package: condor-doc Source: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6162 Depends: neurodebian-popularity-contest Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: doc Filename: pool/main/c/condor/condor-doc_7.8.6~dfsg.1-1~nd12.10+1_all.deb Size: 1366096 SHA256: 8e15bde9fcf9281260997edd5b863162eb82d944375d46b34107650250876a9b SHA1: b685be312586eae6b6e7d8e068a62d70c528aac1 MD5sum: 39dd139ebe5243ec2e5bceefa5c4c30d Description: distributed workload management system - documentation Like other full-featured batch systems, Condor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to Condor; Condor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, Condor can also effectively harness wasted CPU power from otherwise idle desktop workstations. Condor does not require a shared file system across machines - if no shared file system is available, Condor can transfer the job's data files on behalf of the user. . This package provides Condor's documentation in HTML and PDF format, as well as configuration and other examples. Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-3, 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_amd64.deb Size: 48052 SHA256: b78405fd5c9706c38b65244862e9f2a0b3e076779b3cac0346b96c61dad64063 SHA1: 2072ad81e6367eb0f7382d9073534d64ad7fc0b5 MD5sum: 4e314db6a5b8595b1d4f05f5171c8c16 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 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_all.deb Size: 7224818 SHA256: 25bbf59e6baaa0fd1f795f650fc89e2fc7f1c9bed1172b1adfe766a6a9b64be4 SHA1: 5b471b69135beae6f699377fdfcb606d1fcb972e MD5sum: dd4f89591443db2aab3bfc912c908f2e 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 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_amd64.deb Size: 10998 SHA256: 99be780fef25795fbe1d64c2024749af49de894021e1bea3d14ae57a9d82a826 SHA1: d5caf3eef038a0bad0c8fde49cd6486633654906 MD5sum: 7f5b2d17ebe6df55e920758f8cef1100 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: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+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_all.deb Size: 9726 SHA256: 34850e6858d784f40edaa883e66923b867c1262d92203a3ccde4cd38fc505897 SHA1: efa6a60304adb482d61201f9187f1fb23807d12b MD5sum: 0f86d558162919041ff81fb2e7129410 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: ipython01x Version: 0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4660 Depends: neurodebian-popularity-contest, python-argparse, python-configobj, python-decorator, python-pexpect, python-simplegeneric, python2.7, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Recommends: python-tornado (>= 2.1.0~), python-pygments, python-qt4, python-zmq, python-matplotlib Suggests: ipython01x-doc, python-gobject, python-gtk2, python-numpy, python-profiler Conflicts: ipython-common, python2.3-ipython, python2.4-ipython Replaces: ipython-common, python2.3-ipython, python2.4-ipython Homepage: http://ipython.org/ Priority: optional Section: python Filename: pool/main/i/ipython01x/ipython01x_0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1_all.deb Size: 1284736 SHA256: b33fe2d592d01644998eb2e3bc890c25603a29cce31206f6f29932415951133f SHA1: 3f4113a83607a389037683969e8caade00a5d669 MD5sum: 473207982d79acf9947e95404ea568d8 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This is a non-official, custom build of IPython post 0.11 with notebooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-doc Source: ipython01x Version: 0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16630 Depends: neurodebian-popularity-contest, libjs-jquery, ipython01x Homepage: http://ipython.org/ Priority: optional Section: doc Filename: pool/main/i/ipython01x/ipython01x-doc_0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1_all.deb Size: 7229016 SHA256: 881a444ee2c6d3503358921aaef312a447c836fa73801a27243f5176d13fe5c1 SHA1: 270cbd0fcd103cb0c6d84fcebda1de3932c7865d MD5sum: 444ff6826d670d1fd6f0c4e9589c8109 Description: enhanced interactive Python shell IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs. . This package contains the documentation. . This is a non-official, custom build of IPython post 0.11 with workbooks support. It provides IPython01X module thus not conflicting with system-wide installed IPython Package: ipython01x-notebook Source: ipython01x Version: 0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-notebook_0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1_all.deb Size: 902 SHA256: e419ba065e85ef22cd296029af98564adf14a9332999c17c1132e7f5fc77b330 SHA1: de4ee34412823e15deafb6e01dc025ae17acaccf MD5sum: 57ba052dcaa4a910f24812c728bf2cf6 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships notebook functionality inside. It is made so to stay in line to modularization of official ipython package in Debian. There is no real good reason to install this package. Package: ipython01x-parallel Source: ipython01x Version: 0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: oldlibs Filename: pool/main/i/ipython01x/ipython01x-parallel_0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1_all.deb Size: 832 SHA256: 8f7ffeea044193aff74e58faeb12638ee38d92ce5ffa60433676e6deb1139c4a SHA1: cb740b034905cd12baae6ff52893a8d607438878 MD5sum: 1d2333cd5d2fa1b0c083d93ae024d72f Description: enhanced interactive Python shell This is a transitional package and can be safely removed after the installation is complete. Package: ipython01x-qtconsole Source: ipython01x Version: 0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, ipython01x (>= 0.13.1~git33-gcfc5692-2~) Homepage: http://ipython.org/ Priority: extra Section: python Filename: pool/main/i/ipython01x/ipython01x-qtconsole_0.13.1~git33-gcfc5692-2~nd12.04+1+nd12.10+1_all.deb Size: 914 SHA256: 59433b7f7b77e8489e1af4627b2450943ea10ca88105a27835e997d87a450b04 SHA1: b3ba1be85906ebf378047d8c15dae71f8903c66d MD5sum: 79d9cb7a8cf067f2ecd01a9bb5155d52 Description: enhanced interactive Python shell -- notebook dummy package This is a dummy package depending on ipython01x which ships qt console functionality inside. It is made so to stay in line to modularization of the official ipython package in Debian. There is no real good reason to install this package. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1708 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-1~nd12.10+1_amd64.deb Size: 425832 SHA256: 780d94fa348f10c496093620610831049ae130a923505412a61de2eb6ccb0169 SHA1: ec89cde7e13903c3b3a79df5c8e792f835f1115c MD5sum: 74f765b2d608e57491ecf06b30816d22 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 909 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_amd64.deb Size: 336160 SHA256: e2b53bacd6772d2b61c2c71e4ac865ee2969a4e026340402534a65be9bed7014 SHA1: 6df004788795a1a5428528334fa344f879164e3e MD5sum: 6b1dac68e80a45ae8aeb16282c5720fe 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 378 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-1~nd12.10+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-1~nd12.10+1_amd64.deb Size: 118566 SHA256: 5604f8ac90c359005bce28841065ce24054e21b2f601e565a6adb11230eb30fe SHA1: 6d65cfa49b8465f603f986292a113265ab5fbaf1 MD5sum: ccb4423cbbdb5007719b84465a25c2a0 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: libclassad-dev Source: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2802 Depends: neurodebian-popularity-contest, libclassad3 (= 7.8.6~dfsg.1-1~nd12.10+1) Conflicts: libclassad0-dev Replaces: libclassad0-dev Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: libdevel Filename: pool/main/c/condor/libclassad-dev_7.8.6~dfsg.1-1~nd12.10+1_amd64.deb Size: 521404 SHA256: ec2a4fb1837db0189dd347dc7f25772ad84c05ab8f28e5ae904f7f06d6499c79 SHA1: 41f2294d729efa916ef7913dbc622040a78e7cb7 MD5sum: 6fc8be43702bac8d6e300bcf1b106589 Description: Condor classads expression language - development library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the static library and header files. Package: libclassad3 Source: condor Version: 7.8.6~dfsg.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 883 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpcre3 (>= 8.10), libstdc++6 (>= 4.6) Homepage: http://research.cs.wisc.edu/condor Priority: extra Section: science Filename: pool/main/c/condor/libclassad3_7.8.6~dfsg.1-1~nd12.10+1_amd64.deb Size: 276660 SHA256: eadb1616e3ffc718e4c6f7933f7e3213db4e65c15f3cb25e0ea82b29a7ece681 SHA1: d40fc6bbcc1fe4360c8a0802637f6fc32a797811 MD5sum: 5799186de619738e28649cdaaea89fb9 Description: Condor classads expression language - runtime library Classified Advertisements (classads) are the lingua franca of Condor, used for describing jobs, workstations, and other resources. There is a protocol for evaluating whether two classads match, which is used by the Condor central manager to determine the compatibility of jobs, and workstations where they may be run. . This package provides the runtime library. Package: libmcpanel-dev Source: mcpanel Version: 0.0-1~nd11.10+1+nd12.04+1+nd12.10+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) 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_amd64.deb Size: 2402 SHA256: ecc2c9ce038a1b19411f89ad673c00677fa0d7334543da1e90db12886ed635b5 SHA1: 46de4b6ad096faf310e3711e0ebf268fb3302492 MD5sum: 3f3737ed635126a5f1d08ceb24fe3e78 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 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 (>= 2.31.8), libgtk2.0-0 (>= 2.14.0), libpango1.0-0 (>= 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_amd64.deb Size: 49138 SHA256: 9ddbf9361a5559d529c2ecc6529fc2813b6cc984e81ac0ab0fe96508f5405406 SHA1: 57eaf81dc01db696236f487cab07b95a5475b7a5 MD5sum: 857664762f1b92c862305c31505ab639 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, libmcpanel0 (= 0.0-1~nd11.10+1+nd12.04+1+nd12.10+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_amd64.deb Size: 6722 SHA256: 7fa3c2f653d4413ed0d734bac62a3e152be16b42be1ae7e92f8ec9f647034293 SHA1: 4fc0ea3f52569209dd28c905fcbc4d4d37b91e8c MD5sum: 4ae5f52eed8e4463e0aa636ba45fc66a 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+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_amd64.deb Size: 174136 SHA256: 1dec69716ad91c008bf8fa6b98a35dc6253f53344745c82736620cf0ea39c592 SHA1: 61078a436788fb4302831045b5f2e7afecca0c74 MD5sum: 9854e6264b7acc40ca24660880900178 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 535 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_amd64.deb Size: 182116 SHA256: 55902640dd8606b3e9d53a6b46fd16337a42ea610978d6ba8a7fcc296bbb2a98 SHA1: c934db7e36a2de9be933ba2ad2e0ff637ca9a40a MD5sum: 2af6d9d6faface3011006b06580ee322 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1355 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_amd64.deb Size: 437386 SHA256: b7d37721dde4e1f75850ee5c7119426afa3822d9642dbd8b5fcabf91e82093c8 SHA1: fecd69d00ce34d0e8dfa20c2411969e8eee85cb0 MD5sum: b66293205631c5400431a515a4745102 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: 0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 21362 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), libpango1.0-0 (>= 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_0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1_amd64.deb Size: 6943216 SHA256: 928edce8a5af6edbc0c3f924460429c56ce0c177296ec2b99843a96ebb5c46a3 SHA1: 2a9276eda72e657690dcc0b012ace1faed8a2a6d MD5sum: eb6f8565cb5d2c7c3c4b45580045e620 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: 0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers 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_0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1_all.deb Size: 1664034 SHA256: 67d11d7a26ee669ce218dec8dedd8de442fcc302031ec0801be4f0a36eaf5428 SHA1: 92e4e8dc8cb2c36ee9f5b889b7596f48d8daadf5 MD5sum: 8fa66eab66da9d13c81f4c66008b472a 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: 0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 979 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20120505.1~dfsg.1-1~nd12.04+1+nd12.10+1_all.deb Size: 735764 SHA256: adf029ff7c6e162ead06e7cafca311ac7780e43b95dcb97d3f4d5000ab6d4f3e SHA1: ec103ce1298820abe5e9962ed4d42e07dc7cd8d5 MD5sum: f4300f300106bdebf22685ddda9e4078 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: neurodebian-desktop Source: neurodebian Version: 0.29~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 141 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_0.29~nd12.04+1+nd12.10+1_all.deb Size: 114562 SHA256: 32062fe00ad2ff0b3f8e6a531377bf28b4c0dad0c5ec613e8346566215ca5742 SHA1: e7ae797f8b7f2af5d37adef311914d4d3993d8cb MD5sum: 5c15304c2d12f47d70376e1e8f834739 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: 0.29~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5748 Depends: devscripts, cowbuilder, neurodebian-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.29~nd12.04+1+nd12.10+1_all.deb Size: 5346754 SHA256: 406c53d692181cb734d1cf80188366079184148f47c9e581383e7d593a2d18bd SHA1: 0d1bd090825e5c4a0843af30e5433bbaf6b9f54e MD5sum: 34027c8b2eb10238f4efef375f676f0e 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: 0.29~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 106 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm | gdm3, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.29~nd12.04+1+nd12.10+1_all.deb Size: 14288 SHA256: 866702960f9ed6d2731f3107d84a8db4d52b21f8fd0fe56013e081c0e656c966 SHA1: 6a4fa09c4b33d2a7e0d8445b9bd4867a120003ef MD5sum: 0f8d252eb47e08ba20035796dc1b1aa9 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: 0.29~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.29~nd12.04+1+nd12.10+1_all.deb Size: 6970 SHA256: 85fe1f50f0bc80dba7b7f65502128aba04cf1442ea3b8cea89605ad22c9b317f SHA1: 9a70125a1cca8ff830854548ead84b2987e3b77f MD5sum: ef08f25b0a9624afecdda0d9490dd8cb 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: 0.29~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.29~nd12.04+1+nd12.10+1_all.deb Size: 6140 SHA256: 0fa222006537a1b517ed356efdebe755272476ca9910ec8b43e838eea9ac2bc8 SHA1: fa9cf85cae6ea3d90c86ac5ac31bf85140d2b0ff MD5sum: 60adf40efe4c5d4cf7eecde6101df637 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: 0.4.5-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2113 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit3.20, libstdc++6 (>= 4.6), nifti2dicom-data (= 0.4.5-1~nd12.04+1+nd12.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/nifti2dicom_0.4.5-1~nd12.04+1+nd12.10+1_amd64.deb Size: 475298 SHA256: 93cd5416e1add1ce63fcc3e66f866bb1cfc1e1deee012d2a9705f17e09985e48 SHA1: 6b4b0d8f31f050c60a89cca93cb8d35df8319d5c MD5sum: 189c5f1a0c6f4a0ebb8db81544288b26 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: 0.4.5-1~nd12.04+1+nd12.10+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_0.4.5-1~nd12.04+1+nd12.10+1_all.deb Size: 615000 SHA256: 272ed3d474a443b383fc5f818890d71d703a6860d58ab6fad247607126fe0442 SHA1: a1e46e31f600d80a861cc6fe5af6a78182b356e6 MD5sum: 61cff1026ec14a6dca81be2aef8d6fe3 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: 0.3.25+ds-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1377 Depends: neurodebian-popularity-contest, g++-4.6 (>= 4.6.1) | g++-4.5 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python (>= 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_0.3.25+ds-1~nd12.10+1_all.deb Size: 349442 SHA256: b4323504302b965a3d1a75bc4559bd887afe9cee706212233a4811a4899abca6 SHA1: cfa3e917a94f1194fcb9bb5b1730a0ef3357f06e MD5sum: bbfbbc29b39c82d5a194604c9c2240de 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 to pure Python objects at all. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 69 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.14), liboctave1 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-1~nd12.10+1_amd64.deb Size: 24024 SHA256: 01dcaf9df7d3e590e1f26f18f28a7bc8bf69b7dbc67026f2b771561e36b74c29 SHA1: 5c25e2447d0cc2a7f737b7f2b50a6da08d31cf27 MD5sum: dd827364b36bb9c0c078dd5ab10a559a 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: 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2503 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, libglew1.8 (>= 1.8.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.24), liboctave1, libopenal1 (>= 1:1.13), libpciaccess0 (>= 0.8.0+git20071002), libstdc++6 (>= 4.1.1), libusb-1.0-0 (>= 2:1.0.8), libx11-6 (>= 2:1.2.99.901), libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1), psychtoolbox-3-lib (= 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+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_3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1_amd64.deb Size: 851098 SHA256: 364cdc687542d20707925e61d16f22b098ff609c7a2f3abdc314ecb2812600f3 SHA1: 521315b3ca94a26c9fa21900b2ea556378f9dc07 MD5sum: fe4e4acdf69b515cc62d73b2c34fc779 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. . This package contains bindings for Octave. Package: opensesame Version: 0.25-1~nd11.10+1+nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4136 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 Recommends: python-serial (>= 2.3~), psychopy (>= 1.64.0), python-pyaudio (>= 0.2.4), python-imaging (>= 1.1.7), python-opengl (>= 3.0.1) Homepage: http://www.cogsci.nl/software/opensesame Priority: extra Section: science Filename: pool/main/o/opensesame/opensesame_0.25-1~nd11.10+1+nd12.04+1+nd12.10+1_all.deb Size: 2839210 SHA256: 6ade3c8a844117b6969e4109d786d88a82909f659ef3734b82de0048c4293c03 SHA1: 6d74ddaeaf8a74342ec4de39244cf5564860a66e MD5sum: 1ee444df1bc05108060f211f466a91dd 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. Python-Version: 2.7 Package: psychopy Version: 1.74.03.dfsg-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5203 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, libavbin0, ipython Suggests: python-iolabs, python-pyxid Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.74.03.dfsg-1~nd12.04+1+nd12.10+1_all.deb Size: 3102320 SHA256: 825080ff79bbbd5ac1ea5e58a979acf4e351e753d2e9b38328caea762bf65e18 SHA1: 72f3982ab85940d99481d52b50a98f902131f22e MD5sum: 59edb5e68abec01737402c6ffc8761c8 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47050 Depends: neurodebian-popularity-contest Recommends: subversion Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1_all.deb Size: 19434084 SHA256: 8ecf9cd9d55ef7201eda01b7238df269c520192b5caa638dcebb9051fb58cc30 SHA1: d80cc6b6ad02dd9a8519f5ca5dda158f0a8e3522 MD5sum: b466f1367795115bfacf30664b07e9d5 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: 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2541 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1_amd64.deb Size: 844682 SHA256: 3fe3f9598a700844d03221748a5095f44388cb3a44f209fba3442a2d4378a6e8 SHA1: af900b5b25fb0c60c77c8b664880aa4adf893a64 MD5sum: 8cd39a6953071327ddebb97c021020d1 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: 3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 265 Depends: neurodebian-popularity-contest, libc6 (>= 2.2.5), 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 Suggests: 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_3.0.9+svn2579.dfsg1-1~nd12.04+1+nd12.10+1_amd64.deb Size: 121962 SHA256: 55c88b587c741abec15f5fd8b0989875d04513818c3d2435d24fe54eb6071757 SHA1: d3aa9628eecb796e1927062a7a08129006c472db MD5sum: d0ba7617c65546b622ea64cf343e0eae 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 206 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), 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_amd64.deb Size: 55748 SHA256: 49c44ea0def0bb6344d6cbcc8088eed0a879bd4c2a1a7ca8b29314ea63378fed SHA1: 81aa94b1d87208ced723adbda2eea9f5dc7f1baf MD5sum: fd00e444d43d07f0be1ea347d70b717e 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: 1.4.0-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2139 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-brian-lib (>= 1.4.0-1~nd12.04+1+nd12.10+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_1.4.0-1~nd12.04+1+nd12.10+1_all.deb Size: 503240 SHA256: 51357e842efadc5bb97f1842c7b5269fed5e668a6d5d9f89550d2ac2d624ac0a SHA1: d2bb4f2f816f32e4c53b01ce1e336d717daebed8 MD5sum: 18ef5b7b8eb127e34855a44fec92fe1a 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: 1.4.0-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6133 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_1.4.0-1~nd12.04+1+nd12.10+1_all.deb Size: 2179816 SHA256: c3a02bcfbbe6eff889c509b8b261d4c32759d7c5801ef546b02113cd520cd0dc SHA1: 44477ae2af4a058ea08c193390b55a6198ad990e MD5sum: 63863d69005f9f9ab8cee59d40c71fd8 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: 1.4.0-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 152 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), 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_1.4.0-1~nd12.04+1+nd12.10+1_amd64.deb Size: 60898 SHA256: 6648368097b7e009ab4c96b3380ec0948e8d514f2f7fb159d8c2aa8c30c65fab SHA1: 08d961d025d03fc5d80e9f71187b3ad97b885df3 MD5sum: 615057ad0c17e8de20b68394bfa0462f 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-dicom Source: pydicom Version: 0.9.7-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1790 Depends: neurodebian-popularity-contest, python2.7, python (>= 2.7.1-0ubuntu2), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.7-1~nd12.04+1+nd12.10+1_all.deb Size: 419248 SHA256: f3f77a173128d07565fa883296bb7e2e6ac71c2c063503b35dd203af84045cc3 SHA1: 4cb7eb491eb9c51dfffa5af9f9c962df613bc137 MD5sum: 843bc43a1ba02475ab7b61e3ca6ceb07 Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-joblib Source: joblib Version: 0.6.5-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 175 Depends: neurodebian-popularity-contest, python (>= 2.5), 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_0.6.5-1~nd12.04+1+nd12.10+1_all.deb Size: 52690 SHA256: 7cdd6f6998be06124635d64c1993ec41abc7520c83d71a6de17cd104833a6fdc SHA1: 9f19da28d98df6a76983d00eb64b3b6de2f9f8f6 MD5sum: 408d1245807b0d85afdbb3aa835bfc4b 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-mpi4py Source: mpi4py Version: 1.3+hg20120611-2~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1150 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.3, python2.7, python (>= 2.7.1-0ubuntu2), python (<< 2.8), mpi-default-bin Suggests: python-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python-mpi4py_1.3+hg20120611-2~nd12.10+1_amd64.deb Size: 379548 SHA256: 1894cd27d9ba98af27514e3232b0fbaaab19ab320eb6827e19f7492c467ac842 SHA1: 742606295b2352c7507bac99d0d3c7c4a05f6806 MD5sum: c725879e5e18baf71fc04e264a0c5b1a Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python-mpi4py-dbg Source: mpi4py Version: 1.3+hg20120611-2~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4232 Depends: neurodebian-popularity-contest, python-mpi4py (= 1.3+hg20120611-2~nd12.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python-mpi4py-dbg_1.3+hg20120611-2~nd12.10+1_amd64.deb Size: 1043476 SHA256: db781b7ad786bd14aff6f5192915b8aef2700d017521f8dcdeb515f8965ff47a SHA1: cdeb65d508e3c180a9a5b588424c732801cc58a8 MD5sum: 70c851f8cd8520c101e11d44de366e93 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: python-mpi4py-doc Source: mpi4py Version: 1.3+hg20120611-2~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 284 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-mpi4py Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: doc Filename: pool/main/m/mpi4py/python-mpi4py-doc_1.3+hg20120611-2~nd12.10+1_all.deb Size: 82524 SHA256: a71a3e30acd4ca335666f96ef827fdca039a1873e8a2dd45f579aed595d561ec SHA1: b3b21af55fab7ce1775ba864328d0023b53af1a2 MD5sum: 305217a25234435dd5ae7761c214dee8 Description: bindings of the MPI standard -- documentation MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides HTML rendering of the user's manual. Package: python-mvpa2 Source: pymvpa2 Version: 2.2.0-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4241 Depends: neurodebian-popularity-contest, python (>= 2.4), python-numpy, python-support (>= 0.90.0), python-mvpa2-lib (>= 2.2.0-1~nd12.04+1+nd12.10+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, shogun-python-modular, liblapack-dev Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.2.0-1~nd12.04+1+nd12.10+1_all.deb Size: 2399986 SHA256: e77909b0dccaa44717beab4afe9e83c2c86ff46d9197e562ed27fcca4aca0f22 SHA1: f49f7edfd5c1c294464b7c97cd3243748aa118a9 MD5sum: 7240798423edc4a1d318d8aa34a9d3c0 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.2.0-1~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 17215 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.2.0-1~nd12.04+1+nd12.10+1_all.deb Size: 5140662 SHA256: e2632da5ca320dbdd3fab7f532c4fa11990e312979190db16e918ef30dc0e841 SHA1: ba6389d7ed10f3a6bf29eabba44936dbe7bafa6b MD5sum: 505c6dcc506aa9d7bce4a2c8e91bf82c Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.2.0-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.2.0-1~nd12.04+1+nd12.10+1_amd64.deb Size: 49444 SHA256: 35f7105c10c4a6911978c5591410b4ef1cdd7793769d4879f2d9848c832b5166 SHA1: 3f6c3e5046443b2ffcf0ab4567211e60c81eb98f MD5sum: c6b6cac422e2e3530623d875beb5e927 Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neo Source: neo Version: 0.2.0-2~nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2181 Depends: neurodebian-popularity-contest, python2.7, python (>= 2.7.1-0ubuntu2), python (<< 2.8), python-numpy (>= 1:1.3~), python-quantities (>= 0.9.0~) Recommends: python-scipy (>= 0.8~), python-tables (>= 2.2~), libjs-jquery, libjs-underscore Homepage: http://neuralensemble.org/trac/neo Priority: extra Section: python Filename: pool/main/n/neo/python-neo_0.2.0-2~nd12.04+1+nd12.10+1_all.deb Size: 1385368 SHA256: 375ed30dc0a3483275a8a5de9bceb98bba3103aefc5cbf3f2930bba6da785728 SHA1: 5369e5dd2ebd52de4f1de809e3f23cecb7d92fc0 MD5sum: 60a4482c8b65f20f8d05753351d5d5f9 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-nibabel Source: nibabel Version: 1.3.0-1~nd12.04+1+nd12.10+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_all.deb Size: 1816340 SHA256: f4393634a41ed4334f5833115835ac674f8fd2f0aaac8a8acecaed5d841b37f2 SHA1: 6e07b237d683b17e0807de6d3faaf078698e2968 MD5sum: 3ec51142db5c228429cb67563faa3222 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 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2440 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_all.deb Size: 444170 SHA256: 01df549d5c4ea10fc4712a4ee44ba0d4f6eb3ac668043365cd5a1063bcfc7bbf SHA1: 229ecd36ecd5903eafc04e3553ba1609d861e9c1 MD5sum: 84cbf46b773013a504beb30c532bd5b4 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-pandas Source: pandas Version: 0.9.1-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3051 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy (>= 1:1.6~), python-dateutil, python-pandas-lib (>= 0.9.1-1~nd12.10+1) Recommends: python-scipy, python-matplotlib, python-tables, python-tz, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.9.1-1~nd12.10+1_all.deb Size: 690086 SHA256: efd89585ec6ab659da7d514efa076ec6869e20d8401d50638704fe2c9d884cb5 SHA1: e105c05bcf5ff6e8dce2efdf8393aed6e7bf8fe7 MD5sum: dd9a7bb34e94a576266bda44ea027a71 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure Package: python-pandas-lib Source: pandas Version: 0.9.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2884 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.9.1-1~nd12.10+1_amd64.deb Size: 1118048 SHA256: cf34b3f9ca66c10e2ba4373dd7bd5fd85282dbc3b0ce81db31c9da83832f9e46 SHA1: 2250aa0b392012b1cdc3a89dd6c75ac987d604f5 MD5sum: ccbfabaa70b76921dd5e9092e96c0dde Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. Python-Version: 2.7 Package: python-pymc Source: pymc Version: 2.2+ds-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1879 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0), libblas3 | libblas.so.3 | libatlas3-base, libc6 (>= 2.14), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3 | libatlas3-base, python-scipy, python-matplotlib, python-nose Recommends: python-tables Suggests: python-pydot, ipython Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: python Filename: pool/main/p/pymc/python-pymc_2.2+ds-1~nd12.10+1_amd64.deb Size: 589206 SHA256: cef680c42f093fa974247a2b30ea76a3fc7f74977f2258986fc836291bb772f4 SHA1: dc26487146620aa553f45d8433d717148293493f MD5sum: 4eceffe6fcd1344a750bd3aefe8da988 Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. Package: python-pymc-doc Source: pymc Version: 2.2+ds-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1840 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Homepage: http://pymc-devs.github.com/pymc/ Priority: extra Section: doc Filename: pool/main/p/pymc/python-pymc-doc_2.2+ds-1~nd12.10+1_all.deb Size: 906858 SHA256: 59074e78f8759a1d2cc3f7798cac2ae5c9991ecf4fd266909ef1252e91bfe6fe SHA1: 0cc0b5fb138b9896e1905ba8f80e97b338fab08b MD5sum: 0073ef238c61a59b8ff50c2f2534d15b Description: Bayesian statistical models and fitting algorithms PyMC is a Python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics. . This package provides the documentation in HTML format. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1595 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_amd64.deb Size: 445790 SHA256: ec9f28c7206d7fd3c08dbbc6ab39ac9b8daa31c7c6f7d14e3700f15c7aefbce3 SHA1: def333aee110ded32ce8ed68d1b88b54066735af MD5sum: 40eadd4291a5654aa1d471cddbb39378 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-scikits-learn Source: scikit-learn Version: 0.12.1-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 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_0.12.1-1~nd12.10+1_all.deb Size: 24320 SHA256: 53562647783d0fe36251258f18495a9e939259d0911a6285f13b949bd59fa8c2 SHA1: c9650b75753d8e0c9c15195ddad04b33a3d5d406 MD5sum: b6265933cbb7f828d5b9ed4011c60fd6 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-sklearn Source: scikit-learn Version: 0.12.1-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2658 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, python-scipy, python-sklearn-lib (>= 0.12.1-1~nd12.10+1) Recommends: python-nose, python-matplotlib, python-joblib (>= 0.4.5) 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_0.12.1-1~nd12.10+1_all.deb Size: 927428 SHA256: bd77b892fd384ae768929142639cb75386808d7e990f5633cc6f073609c157ae SHA1: 4735f3c5d34cd437ace954e1bbf9295df17f425c MD5sum: c04922c009ff2b3f86a73b7214eba32d 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) Python-Version: 2.7 Package: python-sklearn-doc Source: scikit-learn Version: 0.12.1-1~nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36628 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_0.12.1-1~nd12.10+1_all.deb Size: 26700106 SHA256: 06b2598b3858652b552cf0b9a924a3c08b1a06f5e33171a20a6a365dcaa8dbb3 SHA1: b653e46c1102a100e1a6b0f26d54743b2bec31ec MD5sum: 89edff9adee18d7d86fd350e22137310 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: 0.12.1-1~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1965 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.6.1), python-numpy-abi9, python-support (>= 0.90.0) 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_0.12.1-1~nd12.10+1_amd64.deb Size: 771928 SHA256: b97b4fe3eb44cb6333c590bd476ff08468b88d0e17bd3d3e949e453390b90a74 SHA1: 9b8f72ed94226c208f50f71d4bb7480fcc78eee3 MD5sum: 74b10f9316f9c4ab43672f0165d246d4 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. Python-Version: 2.7 Package: python-surfer Source: pysurfer Version: 0.3+git15-gae6cbb1-1~nd12.04+1+nd12.10+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_all.deb Size: 28082 SHA256: 2a0d8f7bea7b8e7fbe80619282bcd1c0b6874fbc2569c3248451c752f1cdc4dc SHA1: 186db3b9114826618485059e3582945a132d76f5 MD5sum: 7cc577897180b73015b7f99b17c6d04f 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 Architecture: amd64 Bugs: mailto:bugs@neuro.debian.net Maintainer: NeuroDebian Team Installed-Size: 1675 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_amd64.deb Size: 342538 SHA256: 7e9eb17627c4e095ba287ca65e4b3d7963037df5fbb0387d785ceadb3e4715a3 SHA1: 5532ecf00ec5e61e53d54ced5d2cd281ae38a4e1 MD5sum: 9fb5262187c14bbb30d15b301459d8fb 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-mpi4py Source: mpi4py Version: 1.3+hg20120611-2~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1108 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libopenmpi1.3, python3 (>= 3.2.3-3~), python3 (<< 3.3) Recommends: mpi-default-bin Suggests: python3-numpy Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: python Filename: pool/main/m/mpi4py/python3-mpi4py_1.3+hg20120611-2~nd12.10+1_amd64.deb Size: 371386 SHA256: 75c6a5ba6d5bd8e39b0ec06d99ae6f90f71cffe5e5a65d1159ef090d6b10d71d SHA1: 8d204bcfa949352eca9ded551d497cb1c90d3d1e MD5sum: 06dd14a78560bd494939084bedfa6771 Description: bindings of the Message Passing Interface (MPI) standard MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). Package: python3-mpi4py-dbg Source: mpi4py Version: 1.3+hg20120611-2~nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4191 Depends: neurodebian-popularity-contest, python3-mpi4py (= 1.3+hg20120611-2~nd12.10+1) Homepage: http://code.google.com/p/mpi4py/ Priority: extra Section: debug Filename: pool/main/m/mpi4py/python3-mpi4py-dbg_1.3+hg20120611-2~nd12.10+1_amd64.deb Size: 1037672 SHA256: 2b5072fc59e05b81dbbf63ce7d6e601fba61644563a57dfbbf22eb58f7021805 SHA1: f95df752516652beb6127b51d71742361386c2de MD5sum: 051c50ddac0d6cc09d2a396c4f980149 Description: bindings of the MPI standard -- debug symbols MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. . mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects). . This package provides debug symbols. Package: qnifti2dicom Source: nifti2dicom Version: 0.4.5-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3055 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgdcm2.2, libinsighttoolkit3.20, libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.6), libvtk5.8, libvtk5.8-qt4, nifti2dicom (= 0.4.5-1~nd12.04+1+nd12.10+1), nifti2dicom-data (= 0.4.5-1~nd12.04+1+nd12.10+1) Homepage: https://github.com/biolab-unige/nifti2dicom Priority: optional Section: science Filename: pool/main/n/nifti2dicom/qnifti2dicom_0.4.5-1~nd12.04+1+nd12.10+1_amd64.deb Size: 662896 SHA256: 5c74dc761710140fb356ba0bd5203a0ab0267e9b3f16f5a7777cb21518c45267 SHA1: 6ee01c5c74b20f70699e997cbc6b3f2758419664 MD5sum: 01db0cecb2c900918dc2fe3446e078c9 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: remake Version: 3.82+dbg0.9+dfsg-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 293 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libreadline6 (>= 6.0) Homepage: http://bashdb.sourceforge.net/remake Priority: extra Section: devel Filename: pool/main/r/remake/remake_3.82+dbg0.9+dfsg-1~nd12.04+1+nd12.10+1_amd64.deb Size: 178240 SHA256: 44b2d94ca7af2bbe47e723b0d33814f6a9cd042776b3206ec31e2b551b904d7f SHA1: 10f16b182a0f5c8a976d8c965f9631a67837cbf4 MD5sum: 2538e4d9d077d5104d40105c7e6da90e Description: GNU make fork with improved error reporting and debugging Modernized version of GNU make utility that adds improved error reporting, the ability to trace execution in a comprehensible way, and a debugger. Some of the features of the debugger are: * see the target call stack * set breakpoints on targets * show and set variables * execute arbitrary "make" code * issue shell commands while stopped in the middle of execution * inspect target descriptions * write a file with the commands of the target expanded Package: spm8-common Source: spm8 Version: 8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 18467 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1_all.deb Size: 10573812 SHA256: 8eeb69c28d8bc812d050a03f643ef47fd9ca61da620c2dce61916c1589f981d5 SHA1: 7c3aeb64beb10f554efbb6f00795fbb7b8edb359 MD5sum: aaabf7bc6f7bdc4d8b09c4f3637bc671 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: 8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1_all.deb Size: 52167766 SHA256: 97af636dd454562917c7776bf29eeda02133b789f72ca0c1574c0b69c34a84ce SHA1: 0bcb986496f0f413dba9b18e9c7b40c59486bf5f MD5sum: d9298224fbbc0496778f68f83eb5d24b 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: 8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4667~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1_all.deb Size: 8990964 SHA256: de8e156a6572ef9234441722cd628b7d0a2f541deb3a7e1875f7c0bf9c73c885 SHA1: 50b16592314302803dfa31ac6ca03d2bed203b50 MD5sum: f040994ba7e7c8c9f4a211e19ab683f2 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: stabilitycalc Version: 0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+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_all.deb Size: 28774 SHA256: 49039b7b76aa244e4ab34fb04efe43f167aa10e762799ff318276089bf7c2acf SHA1: f2a5e4c70779898ef2164710d40febc1320a6116 MD5sum: 03a808a4acccdd5a48c6b8d10f8b96e5 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: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 322 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), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+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_amd64.deb Size: 66750 SHA256: 7549cd91ada9eb015bb8e708cfd79a7ccda1873facfc2fb701efa8910ed8f9fa SHA1: dfe7527fb24e0d8e5f69763156d6b2b260281dc7 MD5sum: 6255914a610f81cf5ec2916d82f2a382 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 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5745 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+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_amd64.deb Size: 1770122 SHA256: a53315e1d5a528d60638976fbe2665f3576d3fa322322712d92b344bb325a8ce SHA1: ca4ba7a0ec18b968f916982ed0f38d62d603e697 MD5sum: c9284cdac0ca1e91b68a5cd8a612d056 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.