Package: afni Version: 16.2.07~dfsg.1-5~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 45416 Depends: neurodebian-popularity-contest, afni-common (= 16.2.07~dfsg.1-5~nd14.04+1), tcsh, gifsicle, libjpeg-progs, freeglut3, libc6 (>= 2.15), libexpat1 (>= 2.0.1), libf2c2, libgiftiio0, libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libglw1-mesa | libglw1, libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libice6 (>= 1:1.0.0), libnetcdfc7, libnifti2, libsm6, libvolpack1 (>= 1.0b3), libx11-6, libxext6, libxm4 (>= 2.3.4), libxmu6, libxt6, xmhtml1 (>= 1.1.7-19~), zlib1g (>= 1:1.1.4) Recommends: nifti-bin, bzip2, ffmpeg, netpbm, qhull-bin Suggests: r-base Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni_16.2.07~dfsg.1-5~nd14.04+1_amd64.deb Size: 12489550 SHA256: 9ab22aa6867ea2cc619d960885c868eedaee5ed584ac0324f48a0add1cb25374 SHA1: fc1dbb7cb99ace317d25297c7ac1e099963d9a54 MD5sum: 5048d1e8f4ef7f4b60dd7a4b6f9f355e Description: toolkit for analyzing and visualizing functional MRI data AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . In addition to its own format, AFNI understands the NIfTI format and is therefore integrates easily with FSL and FreeSurfer. Package: afni-common Source: afni Version: 16.2.07~dfsg.1-5~nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14483 Depends: neurodebian-popularity-contest, python, tcsh Recommends: python-mdp, python-nibabel, afni-atlases Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-common_16.2.07~dfsg.1-5~nd14.04+1_all.deb Size: 9362086 SHA256: bd8b775c9e4185beb98a2b3e9445bdaf615f8100095b96302659c06c875db2b6 SHA1: 2a23742ca328214b179cb0e803344158250ad75e MD5sum: fe8e863524a4dceae1dc1f3007f6bb5f Description: miscellaneous scripts and data files for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provides the required architecture independent parts of AFNI. Package: afni-dbg Source: afni Version: 16.2.07~dfsg.1-5~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38757 Depends: neurodebian-popularity-contest, afni (= 16.2.07~dfsg.1-5~nd14.04+1) Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/debug Filename: pool/contrib/a/afni/afni-dbg_16.2.07~dfsg.1-5~nd14.04+1_amd64.deb Size: 34139930 SHA256: 268641dff3271b47751b9fdb6d0ea8b214de9b38dc4a6da42af7678e53991b04 SHA1: a7b3371f839316e4333d9cc4af26a725a69c4c02 MD5sum: 5a74d809445678ddc316c6e0e27ce4fe Description: debug symbols for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provides debug symbols which could be useful to troubleshoot and report problems with AFNI. Package: afni-dev Source: afni Version: 16.2.07~dfsg.1-5~nd14.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 23916 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dev_16.2.07~dfsg.1-5~nd14.04+1_amd64.deb Size: 4118096 SHA256: b0f7e058fc66e06693d6055f55ed612497010827f3e71009c72a32c7e9f1d176 SHA1: 5617a856fee084e4b84953bdf3e4dfcb163bb5e6 MD5sum: 71afe7fe8b8bd0b724a4b8fb09c0ede6 Description: header and static libraries for AFNI plugin development AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provides the necessary libraries and header files for AFNI plugin development. Package: fsl-5.0-complete Source: fslmeta Version: 5.0.7-3~ndall0 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 12 Depends: fsl-5.0-core (>= 5.0.7-3~ndall0~), fsl-atlases (>= 5.0~), fsl-possum-data (>= 5.0~), fsl-first-data (>= 5.0~) Recommends: fsl-5.0-wiki (>= 5.0.7-3~ndall0~), fsl-5.0-gpu (>= 5.0.7-3~ndall0~), fslview Suggests: fsleyes Homepage: http://www.fmrib.ox.ac.uk/fsl/ Priority: optional Section: contrib/science Filename: pool/contrib/f/fslmeta/fsl-5.0-complete_5.0.7-3~ndall0_all.deb Size: 4014 SHA256: d524bfba85f003dc1b013013927062869d310468a1723cce2f889cd999d0ce34 SHA1: daed795276f955a9c9b179fe1b43d845b47bb799 MD5sum: 22798de378c13c9de7b0f817fa5ac257 Description: metapackage for the entire FSL suite (tools and data) FSL is a comprehensive library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. The suite consists of various command line tools, as well as simple GUIs for its core analysis pipelines. Among others, FSL offers implementations of standard GLM analysis, white matter tractography, tissue segmentation, affine and non-linear co-registration, and independent component analysis. . Installing this meta package yields a complete FSL 5.0 installation, including all tools and data packages. Package: fsl-complete Source: fslmeta Version: 5.0.7-3~ndall0 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 12 Depends: fsl-5.0-complete, fsl-core Homepage: http://www.fmrib.ox.ac.uk/fsl/ Priority: optional Section: contrib/science Filename: pool/contrib/f/fslmeta/fsl-complete_5.0.7-3~ndall0_all.deb Size: 3954 SHA256: 3fc0882881b73b4868405876f3b31addd423672ccc5214e897e19c39c2978e39 SHA1: 21dcda16b2d7bccfc1898d55835f08715b747796 MD5sum: c4d1c94875389ab6b43c0d9e0189cd0a Description: metapackage for the entire FSL suite (tools and data) FSL is a comprehensive library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. The suite consists of various command line tools, as well as simple GUIs for its core analysis pipelines. Among others, FSL offers implementations of standard GLM analysis, white matter tractography, tissue segmentation, affine and non-linear co-registration, and independent component analysis. . Installing this meta package yields a complete installation of the latest FSL version, including all tools and data packages. Package: matlab-eeglab11 Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40738 Depends: neurodebian-popularity-contest, matlab-support Recommends: eeglab11-sampledata Priority: extra Section: contrib/science Filename: pool/contrib/e/eeglab11/matlab-eeglab11_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 11057334 SHA256: 3c693e22752c17312e01fa7ad6cfbb242e54fd7e2c055e533ea045a5d7cc4931 SHA1: 820fe2fbc8a2ba13570b222d3bd3b4e94e5fec58 MD5sum: f60cd3f4e845fb4cbd336b35389dae54 Description: electrophysiological data analysis This is sofwware for processing continuous or event-related EEG or other physiological data. It is designed for use by both novice and expert users. In normal use, the EEGLAB graphic interface calls graphic functions via pop-up function windows. The EEGLAB history mechanism can save the resulting calls to disk for later incorporation into scripts. . This package provides EEGLAB to be used with Matlab. Note that this package depends on Matlab -- a commercial software that needs to be obtained and installed separately. Package: matlab-spm8 Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1164 Depends: neurodebian-popularity-contest, matlab-support, spm8-common (= 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1), make Provides: spm, spm8 Priority: extra Section: contrib/science Filename: pool/contrib/s/spm8/matlab-spm8_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1_all.deb Size: 172144 SHA256: 39d9e1eb0ccd4db9bfef7ee22719122a0191b681488361f83f4a6104ed1e62a9 SHA1: 70bc06ac89469d7ec88a6ef24e7e2e971e749d0f MD5sum: f0900ca3ca73121487e6528ca858b02e Description: analysis of brain imaging data sequences for Matlab 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 SPM to be used with Matlab. Note that this package depends on Matlab -- a commercial software that needs to be obtained and installed separately. Package: matlab-support Version: 0.0.21~nd14.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 170 Depends: neurodebian-popularity-contest, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, sudo Recommends: libstdc++6-4.4-dev | libstdc++-dev Suggests: lsb-core Conflicts: matlab (<= 0.0.14~) Replaces: matlab (<= 0.0.14~) Priority: optional Section: contrib/devel Filename: pool/contrib/m/matlab-support/matlab-support_0.0.21~nd14.04+1_all.deb Size: 31568 SHA256: 6169876b5b99d88276f6b80da68c20d973e7bdad8746371d42cc43a6c144c372 SHA1: c4665f81a8848b84e0754b03af5eb2dce4640711 MD5sum: 5b1821c23708833364efc181a24a7a6e Description: distro integration for local MATLAB installations This package does not provide MATLAB. Instead, it configures an existing MATLAB installation to integrate more comfortably in a Debian installation. . Currently it provides /usr/bin/matlab through the alternatives system, offers to work around incompatibilities between the libraries bundled with MATLAB and system libraries, and provides a helper utility meant to be used by other packages to compile MEX extensions. . Install this if you would like your MATLAB installation to behave more like an ordinary Debian package. Other packages may depend on this one if they install MATLAB code, for example in order to compile MEX extensions. Package: pycharm-community-sloppy Version: 2017.1.2-1~ndall Architecture: amd64 Maintainer: Yaroslav Halchenko Installed-Size: 435185 Depends: python, openjdk-7-jre | java7-runtime Recommends: ipython Suggests: pep8, flake8, python-nose Provides: pycharm-community Homepage: https://www.jetbrains.com/pycharm Priority: optional Section: contrib/python Filename: pool/contrib/p/pycharm-community-sloppy/pycharm-community-sloppy_2017.1.2-1~ndall_amd64.deb Size: 152089260 SHA256: 7620333e5cc87e911acfc5ceb8a04cda3b043c32261bda1bb88db838765b1f00 SHA1: 8b55797f8a23a231ae94bbc2aa5a15a2838bd4d9 MD5sum: e62b5dbcce75dfdf4578e815bb0b7e96 Description: PyCharm IDE (sloppy packaging) PyCharm provides a heavily featured IDE for developing in Python. It features: syntax highlighting, formatter, code navigation and refactoring, built-in debugger, and more. . This package provides a mere container and installer for distributed upstream tarballs. It by no means qualifies as "proper" Debian package and there is no support for it provided by Debian project. Use at your own risk. Package: pycharm-community-sloppy-dbgsym Source: pycharm-community-sloppy Version: 2017.1.2-1~ndall Auto-Built-Package: debug-symbols Architecture: amd64 Maintainer: Yaroslav Halchenko Installed-Size: 12263 Depends: pycharm-community-sloppy (= 2017.1.2-1~ndall) Homepage: https://www.jetbrains.com/pycharm Priority: extra Section: contrib/debug Filename: pool/contrib/p/pycharm-community-sloppy/pycharm-community-sloppy-dbgsym_2017.1.2-1~ndall_amd64.deb Size: 2253910 SHA256: 14a87a4d2d6886e6024050f7f01a28d06a2f130ca3e14d9933a9d4bcc304ca79 SHA1: 19918f72e3391b1ff5f0eb4506f1e2972b2da75b MD5sum: c8fe16aa47fe09df483a11aae022a298 Description: Debug symbols for pycharm-community-sloppy Build-Ids: 015299f292909ebb35ab1d6bdd470e9eadf8bf52 01f486724a2b2c0731d3da03baf9620d7fa3e0b6 06bf5750152818f965fb2b9a8a56b76ef3f0fd5c 06c3193d6015033dd63848f2f71723d9732dfc44 0a89f378bcee7de2dace8a6eabfe0e9a190c5ab1 0b8761fccafa5fa5a14d26359dece4d467b94bc0 0f1285faa381039c11881f14dacd057a9c19ab83 0fa25da0a4024ce56a95811f2be16aac241fa845 1c19aa5bf19ca41e5a9e82d1662cf0271d552041 1c64efe889bf8fa3d0e03833df9b41a8a7a5b939 1d1a2282079c6e92cbe6707f6ee993188852473a 1f7e9ef27190fa71ec94d5a462d127332c21b107 24b4aac17417e057ea81b3fc287842c74d4869c9 2b45be30aee2c34867e0f03ca9c1907a89f0f94d 2f5e445283dae7d61743bc5e08531432627d9cba 2fc3dc0b272867b2f559f993a5baf04cafd33a0d 411e9b2f228cc1373d836f2e119e667aef0f0ba3 4834aad26762f2cbcda04d109f0b869eb0b443c0 5e29b01c40ace080f44ca6810fb73b9b4cedc970 67ae7e52f34fcb0621ba3937e4288b314676bae2 6a01edf524a54f8bf83330a051e2d1b134ef1a3f 6c7f9241b0942896ff8898d5cc34ff8dc84f0235 6ccc063fd5a069ddf905d21b1a3235a96e43866d 7586b16c56f077f6e51277be77831ba8a15df645 7f208a59f0556e8de55e90787256d6ed60431f74 80471f36ec0145077b80612be3c63d8e3e60a40b 818c245b275894e9ba80bd9bea5129ecd1d41ec2 8593af639077833cc0b722469557b92cd51d78dd 8593af639077833cc0b722469557b92cd51d78dd 8b99d7f1e397b36107136389644cd5c4841597e0 8ba9e84048126af2fd87391de5c1cfa4e37ecea6 8f4fb4d82753dacc8f963546ee3cb19750db7c82 9430da8cd0380c8d5c12cd3f73fe02e1502252da 9b4a858f36fc6517b936431112dbd780756d3b32 9cf0ecbfe3ee91e4e2bc9812db4e41f0c7fcf3bd a645bd81ec4195db7301431c372eaa9ef4ab7155 a7612d336a525ef17252025ee1f82dfdabf5957b ab708c70bc1537d860859eed245185da33309185 b83f109a6b80bd56120e4bf8f8b7f5d1eb7b1bc8 b98f3151778ed1357acb2da19ce892a9b55f9a8b bc00f904ec2d6d818af25c88623c72eab34de501 c21d18b3d554b47d038ba6be92495ac226c5ec6c c2656de285ec749f41dce5603c47015033ab7bda c4737f3a7226086ee8af694720fbcbcf459d6a1e c51ee878ac8a58f7bd2361447cc675189857aa38 c771782b708c1b9de75a026c04facb3d01945d42 c8659e197e3a06f0e13288c075d9e1eee4e43653 c8f69f4ff062e25fb7a46d705ff8ca0155323838 ca397c9d9d46236f97fb0a2c49816b4743ded019 ce3e00304dfd2b3c665fc551edd83bad7971156d d0410c8a6c7c633b1f161cf0db50d81143368509 d25029fa5673d86077ee441a6430c0d4fadfebf8 d3b0056a89d9c0bc915fdf6f4a1f9d2f84485470 d5d09e49f7772cf6b24c5579e608d2c1e458c8ea d8a8489f4469c8ab41992360d02656d4bbd704c8 ea788791cc642c3f82f308d1a6d9b00dc1fa907c ed039021f988cdc7377cb4f65a5df1275813680b f377aa67ce98619408379a1a194c43b5e5a3a84b f526bc7181ebed2cc6d126adc4c959ff52dad257 f7d194e28877051dac2b1c7404322508c1324d60 fa6c01f8be09841ff4510a52ff3afa9b5ed3ee45 fde7feafbf78b3be34f4d7589a5ace94a2416733