Package: aghermann Version: 1.0.6-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1530 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libcairo2 (>= 1.2.4), libconfig++9, libfftw3-double3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl0ldbl (>= 1.9), libgtk-3-0 (>= 3.3.16), libitpp8, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 4.9), libunique-3.0-0 (>= 2.90.1), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.6-1~nd15.04+1_i386.deb Size: 540932 SHA256: cdc2e1ec2fba611c1d8d3ab3d6c2f1b6febdd5b132a606343776dc06e429d57a SHA1: 43eda3c37a30e032a9b6060fa8114c63c0a921ad MD5sum: e9ddb58276f7aee41f419481a732d3e9 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: bats Version: 0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest Homepage: https://github.com/sstephenson/bats Priority: optional Section: shells Filename: pool/main/b/bats/bats_0.4.0-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 14510 SHA256: 02b32e81b73dd96324db85f9ed59e8f1a6cb15ba339dd6a2d14c2249679ff43c SHA1: 480cd9730f96ec53e75c9d3cfec8af43b04633ee MD5sum: a3121275ae8b1c2a28f6ed9ee07a0a02 Description: bash automated testing system Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. Bats is most useful when testing software written in Bash, but you can use it to test any UNIX program. Package: biosig-tools Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 697 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libcholmod2.1.2, 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_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 252468 SHA256: d832b4623255572b9d55fa88b741d37e1b6fb0104a393ddc038133430f7e6cc9 SHA1: 2179f27f05ec0a54e69d10898e0298f2bb8fec3f MD5sum: ad519e98e9abd707fc023a742490792c 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: btrbk Version: 0.20.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, perl, libdate-calc-perl, btrfs-tools (>= 3.14) Suggests: openssh-client Homepage: http://www.digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.20.0-1~nd15.04+1_all.deb Size: 32952 SHA256: d08cd56d23798f7eaf17596b76ed3733c712097a034876644bb12c346ce1603e SHA1: 9a3df1c297d6e9ce6de5e2d2948547ff9dcbe9e8 MD5sum: 62102aac8d548e19267fe4c92bfea714 Description: backup tool for btrfs volumes Backup tool for btrfs volumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations at once, with ssh and configurable retention support (daily/weekly/monthly). Package: btrfs-tools Version: 4.1.2-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3614 Depends: neurodebian-popularity-contest, e2fslibs (>= 1.42), libblkid1 (>= 2.17.2), libc6 (>= 2.8), libcomerr2 (>= 1.01), liblzo2-2, libuuid1 (>= 2.16), zlib1g (>= 1:1.2.0) Homepage: http://btrfs.wiki.kernel.org/ Priority: optional Section: admin Filename: pool/main/b/btrfs-tools/btrfs-tools_4.1.2-1~nd15.04+1_i386.deb Size: 522202 SHA256: 3638661fba9de539957e9e838a51bf81cfad23e78bff041cf9600fda47fc10b5 SHA1: f3dccfc42f2b266cf2b313218bbce77198c52fd5 MD5sum: 35f825796b3d9d9dd7904674ab920233 Description: Checksumming Copy on Write Filesystem utilities Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains utilities (mkfs, fsck) used to work with btrfs and an utility (btrfs-convert) to make a btrfs filesystem from an ext3. Package: btrfs-tools-dbg Source: btrfs-tools Version: 4.1.2-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5198 Depends: neurodebian-popularity-contest, btrfs-tools (= 4.1.2-1~nd15.04+1) Homepage: http://btrfs.wiki.kernel.org/ Priority: extra Section: debug Filename: pool/main/b/btrfs-tools/btrfs-tools-dbg_4.1.2-1~nd15.04+1_i386.deb Size: 4321114 SHA256: bdb16973678031f0aef562fb257ee4a0b9c5389555a49925ba9723c6420ee8f3 SHA1: 24a809f1b64687fe2027311e04b41b817e744d52 MD5sum: 7b00061453ff4a1ac99a78d618035281 Description: Checksumming Copy on Write Filesystem utilities (debug) Btrfs is a new copy on write filesystem for Linux aimed at implementing advanced features while focusing on fault tolerance, repair and easy administration. . This package contains the debugging symbols. Package: cde Version: 0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 883 Depends: neurodebian-popularity-contest, libc6 (>= 2.1) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 150372 SHA256: 4b4c7f4a10793ac2f718f189e5ffb17a092ee17b5bbf18abd86bf21ac784180d SHA1: 9efa40bb81803987b6667262ab7f4ccac6b5fa8e MD5sum: 74d94ccba4521ff305821d0199d3901b Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cnrun-tools Source: cnrun Version: 2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 43 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.4.0) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 17140 SHA256: 6f03c142dba32e4834bc8ee3d682376c9713c0296e479baefb9fd748d23f4029 SHA1: 3084b2d9e0498b82d3ebd82864fd73c7d5453dd9 MD5sum: c497d6b6b365dcde90743a00c30ec553 Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: condor Version: 8.4.2~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor_8.4.2~dfsg.1-1~nd15.04+1_all.deb Size: 15766 SHA256: f3c66ffbe3c570cb2d8f34362f98423e3c933913a60c703a7303de48805fbccf SHA1: 2afdc94a82491b74c1ca2cd0ea32d3d52fd400cb MD5sum: 8e651f0c45af56b291f2f0b88bb6b46e Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dbg Source: condor Version: 8.4.2~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-dbg Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dbg_8.4.2~dfsg.1-1~nd15.04+1_all.deb Size: 15774 SHA256: 2700785592c2fd53c3a9342aab6198c57b81115b6e320502719b991ee8ba8963 SHA1: 26c1beaac817a305b8d82f8caa81d04cbb99c8a1 MD5sum: ac5072d26da6fd0f974e61a556479546 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-dev Source: condor Version: 8.4.2~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-dev Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-dev_8.4.2~dfsg.1-1~nd15.04+1_all.deb Size: 15782 SHA256: 3f1372ef34fd88bbfe91ae1d87615a5858482f0f9bd350db91494eacc009ccf7 SHA1: 8230f603052185734f997e6e24a58d5693805103 MD5sum: b07e9237d6fc7824b311dde4081ca8ed Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: condor-doc Source: condor Version: 8.4.2~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 46 Depends: neurodebian-popularity-contest, htcondor-doc Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: oldlibs Filename: pool/main/c/condor/condor-doc_8.4.2~dfsg.1-1~nd15.04+1_all.deb Size: 15776 SHA256: 2f71f6d7ed52413aaa46977f706f5b2c161fca8547307d8a7d234a3b41b68f76 SHA1: f4e4fbd2c67d609731af6b28065ae7b7bc8e8cb4 MD5sum: 1453352a802397ded77de5e340dbbb17 Description: transitional dummy package This package aids upgrades of existing Condor installations to the new project and package name "HTCondor". The package is empty and it can safely be removed. Package: connectome-workbench Version: 1.1.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 37890 Depends: neurodebian-popularity-contest, libc6 (>= 2.11), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.9), libosmesa6 (>= 10.2~), libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.7.0~beta1), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.8.0), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.9), zlib1g (>= 1:1.2.3.4) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.1.1-1~nd15.04+1_i386.deb Size: 19561546 SHA256: 39e089b498303664050d0a1414952255756f1e772ff48ec777fc6a51a7ffe091 SHA1: 852598190f011e57583f76e3d9f611883d9f3255 MD5sum: 2bef51d2df2a93cd901aae3a959063c6 Description: brain visualization, analysis and discovery tool Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. Package: connectome-workbench-dbg Source: connectome-workbench Version: 1.1.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 105759 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.1.1-1~nd15.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.1.1-1~nd15.04+1_i386.deb Size: 104297752 SHA256: f8170c7fae84e22bcc01b14ce365f9903cb3a4514a312db8443ef3120f74b353 SHA1: 52edc9cc50c85231ee2434e2900232c35e8ea1a1 MD5sum: 9184dc52d37ad5ed6a834ea7e9b877e8 Description: brain visualization, analysis and discovery tool -- debug symbols Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. . This package contains debug symbols for the binaries. Package: dcm2niix Version: 0.20150909.1+git1-g8914c07-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 226 Depends: neurodebian-popularity-contest, libc6 (>= 2.4) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_0.20150909.1+git1-g8914c07-1~nd15.04+1_i386.deb Size: 88700 SHA256: 4864b4f8203a72fe69755a9a775d03e129c035f4a024886f20e5c9c6c4fa3e67 SHA1: 2af0486cd2ff2e01aab054341b199219f72ed7f9 MD5sum: 24dc38ca7f5adebc74dd6de9b645261b Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 37130 SHA256: 42173f36f4444a80f77d4712f2050312fb3cec1bebdc4a3535890a7d8355b040 SHA1: 64971478bd360927e96b906125747956e2e7d870 MD5sum: 01f1d186a183fc6e17ffabb62d063e72 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8109 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 7072950 SHA256: 1cfbde4cf5fae7d0e475a8355234b5b271b7bc3da6963d893fdd4010b87d9924 SHA1: 43219f931dd34ac8fc6a1df9315de3fd18671d9f MD5sum: 384c0b575f5c78aade3abc699e1bb28c 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: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1), freeipmi-tools, freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi_1.4.9-1~nd15.04+1_all.deb Size: 1238 SHA256: 02868858b1a774420def3e1dd0c36f04d8e18e9f47eefca722c036a57c5b22ab SHA1: 7bdae04a803618668439829f16ba94f9c1d4a6d2 MD5sum: e7e5715fc60ca81deda28a01fafe4c88 Description: GNU implementation of the IPMI protocol FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This metapackage depends on all separate modules of freeipmi. Package: freeipmi-bmc-watchdog Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 124 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1), freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-bmc-watchdog_1.4.9-1~nd15.04+1_i386.deb Size: 45522 SHA256: 5adca41bed21d20024a278f18e90b61d8b9da282e6e3b339ab7d55a95de642be SHA1: ceb110b5392bca62193be650eb5fd1e007397292 MD5sum: 6cdf68646ace81227dc0eb8f8325b5b9 Description: GNU implementation of the IPMI protocol - BMC watchdog FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a watchdog daemon for hardware BMC watchdogs. Package: freeipmi-common Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 305 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest Suggests: freeipmi-tools Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-common_1.4.9-1~nd15.04+1_all.deb Size: 189252 SHA256: 5b68a797164a829c0a195d58e107bd6e96b163c43e3601e25bd7cd946111999b SHA1: 8f205f8c86b09a8164bb6b2cad9fb5e90d32245b MD5sum: ee76bb2af4da77fa2b7cc7316d913e25 Description: GNU implementation of the IPMI protocol - common files FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package provides configuration used by the rest of FreeIPMI framework and generic documentation to orient the user. Package: freeipmi-ipmidetect Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 108 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.1.5), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmidetect_1.4.9-1~nd15.04+1_i386.deb Size: 39896 SHA256: fabf6eaabf7b5a7c261eadd5d9c688fe490ead140d72f3cb5dd006ada7ca7fb8 SHA1: c321156ea6e8c17fac858daf854c2a468dc97eb8 MD5sum: 9d14523491e23489e61944a6630f7d97 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains a tool and a daemon for detecting IPMI nodes. Package: freeipmi-ipmiseld Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Pre-Depends: dpkg (>= 1.15.7.2~) Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1), sysvinit-utils (>= 2.88dsf-50~) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-ipmiseld_1.4.9-1~nd15.04+1_i386.deb Size: 82302 SHA256: 5a7495240a8199e0aa89ed389e5f1662a7fe1a8c7239837ab2caa791759c53ea SHA1: 7637239e68b0fb1c3398d3b90bf14db5711ae016 MD5sum: a6eb9772d05f63e3a659aaf42957bc64 Description: GNU IPMI - IPMI node detection tool FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains ipmiseld which takes the system event log from the BMC and imports it to syslog Package: freeipmi-tools Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3021 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.9-1~nd15.04+1), libipmiconsole2 (>= 1.4.4), libipmidetect0 (>= 1.1.5), freeipmi-common (= 1.4.9-1~nd15.04+1) Suggests: freeipmi-ipmidetect, freeipmi-bmc-watchdog Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: admin Filename: pool/main/f/freeipmi/freeipmi-tools_1.4.9-1~nd15.04+1_i386.deb Size: 623634 SHA256: efea0d04a6a57b225e8a8b678398e634e903df3b55e7ab29fb63205ba4d8ba1f SHA1: 5d8f8765c8ec855e53412fb2d02d7c2f371e74ec MD5sum: b95c9bddf892576bb47fb131a2ca83ea Description: GNU implementation of the IPMI protocol - tools FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This package contains assorted IPMI-related tools: * bmc-config - configure BMC values * bmc-info - display BMC information * ipmi-chassis - IPMI chassis management utility * ipmi-fru - display FRU information * ipmi-locate - IPMI probing utility * ipmi-oem - IPMI OEM utility * ipmi-pet - decode Platform Event Traps * ipmi-raw - IPMI raw communication utility * ipmi-sel - display SEL entries * ipmi-sensors - display IPMI sensor information * ipmi-sensors-config - configure sensors * ipmiconsole - IPMI console utility * ipmiping - send IPMI Get Authentication Capabilitiy request * ipmipower - IPMI power control utility * pef-config - configure PEF values * rmcpping - send RMCP Ping to network hosts Package: freenect Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-bin, libfreenect-dev, libfreenect0.5, libfreenect-doc Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/freenect_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 8502 SHA256: d7f66c603e6ad43dfc8d39bb8a779b7488e26780589db497c1ebc79074466279 SHA1: 0e7638987036a5e2112c3be40cda5ccc7b5f0097 MD5sum: 7614c0876cd987419f9ba0b26c2d5e81 Description: library for accessing Kinect device -- metapackage libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the metapackage to install all components of the project. Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 108 Depends: neurodebian-popularity-contest, python, python-matplotlib, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-nibabel, python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd15.04+1_all.deb Size: 14056 SHA256: a88c7501dc04fb23357cef898821026a6fb6f8012305baf2d05ee9075848e39b SHA1: b7db1a2f9c523ad45b5b4ad48ae30cf0a4e13611 MD5sum: 2d85159ebbefc1fad913c2b6e03ae21b Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: gcalcli Version: 3.3.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1739 Depends: neurodebian-popularity-contest, python, python-dateutil, python-gflags, python-googleapi Recommends: gxmessage, python-parsedatetime, python-simplejson, python-vobject Homepage: https://github.com/insanum/gcalcli Priority: extra Section: utils Filename: pool/main/g/gcalcli/gcalcli_3.3.2-1~nd15.04+1_all.deb Size: 1669852 SHA256: b7a64e8275fdb8e438cc30f19d2bc74e37bf2f926c610f44ad44a1d65db3dc26 SHA1: 6baa05e70f3bbb019ab3a8d71ef1bf6383e23f91 MD5sum: 355003a4e6d67b7e6bb2d686a5c34926 Description: Google Calendar Command Line Interface gcalcli is a Python application that allows you to access your Google Calendar from a command line. It's easy to get your agenda, search for events, and quickly add new events. Additionally gcalcli can be used as a reminder service to execute any application you want. Package: git-annex-standalone Source: git-annex Version: 5.20151222+gitg9597147-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 402561 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: graphviz, bup, tahoe-lafs, libnss-mdns Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_5.20151222+gitg9597147-1~ndall+1_i386.deb Size: 28605008 SHA256: e5fde480d5fcb6d1b9d294b479357a24bb0296392da1aa2f1ba7c58d44b04642 SHA1: 04a7e3c52689bbbe24c4a4d8d85156030462aab1 MD5sum: 00d42a8f801c9df7b1fc55f672d05049 Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: heudiconv Version: 0.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 79 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd15.04+1_all.deb Size: 10282 SHA256: 0c40fa003e2a2647c77dec3258cbdf256d6642173f9f06e5d273f7d7180220e7 SHA1: 9c6b25a51ae3154c7a60c8870f37fd710891af62 MD5sum: 5ebd4b041958e21d8077e5303aa4e6cc Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: htcondor-doc Source: condor Version: 8.4.2~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 5911 Depends: neurodebian-popularity-contest Breaks: condor-doc (<< 8.0.5~) Replaces: condor-doc (<< 8.0.5~) Homepage: http://research.cs.wisc.edu/htcondor Priority: extra Section: doc Filename: pool/main/c/condor/htcondor-doc_8.4.2~dfsg.1-1~nd15.04+1_all.deb Size: 1067820 SHA256: 72d27b3147c846645f51ee120b6695a1501b3a680c3aa0ca0b8ffd41d729a66c SHA1: 2647a41d81d4124b1f2f7f88b60398e38227145e MD5sum: 479d80027b991f170a3a0b35f8996b4d Description: distributed workload management system - documentation Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. Users submit their serial or parallel jobs to HTCondor; HTCondor places them into a queue. It chooses when and where to run the jobs based upon a policy, carefully monitors their progress, and ultimately informs the user upon completion. . Unlike more traditional batch queueing systems, HTCondor can also effectively harness wasted CPU power from otherwise idle desktop workstations. HTCondor does not require a shared file system across machines - if no shared file system is available, HTCondor can transfer the job's data files on behalf of the user. . This package provides HTCondor's documentation in HTML and PDF format, as well as configuration and other examples. Package: impressive Version: 0.11.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 465 Depends: neurodebian-popularity-contest, python, python-pygame, python-pil | python-imaging, poppler-utils | mupdf-tools | xpdf-utils (>= 3.02-2) Recommends: mplayer, pdftk, perl, xdg-utils Suggests: ghostscript, latex-beamer Conflicts: keyjnote (<< 0.10.2r-0) Replaces: keyjnote (<< 0.10.2r-0) Provides: keyjnote Homepage: http://impressive.sourceforge.net/ Priority: optional Section: x11 Filename: pool/main/i/impressive/impressive_0.11.1-1~nd15.04+1_all.deb Size: 175700 SHA256: 3553cac32e97d151b5b98dae1a3126083cd4c44d57016a4eafaaab3ec1da6924 SHA1: e2a1290b5ea099abe219fa6c81cc880b2411bce1 MD5sum: fd4a66b05007877feefaca702f1d2488 Description: PDF presentation tool with eye candies Impressive is a program that displays presentation slides using OpenGL. Smooth alpha-blended slide transitions are provided for the sake of eye candy, but in addition to this, Impressive offers some unique tools that are really useful for presentations. Some of them are: * Overview screen * Highlight boxes * Spotlight effect * Presentation scripting and customization * Support of movies presentation * Active hyperlinks within PDFs Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 9296 SHA256: 57b3fa509741010f2e4dd7ae46a4ba6868713d095fbd3890f013381b8ba290a5 SHA1: 0ce4c9e82062cb35d32d318560d12ff4639238ba MD5sum: 01908128c6e1c439174825c0ade70f4a 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: insighttoolkit4-examples Source: insighttoolkit4 Version: 4.7.0-1~nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2837 Depends: neurodebian-popularity-contest Suggests: libinsighttoolkit4-dev Conflicts: insighttoolkit-examples Replaces: insighttoolkit-examples Homepage: http://www.itk.org/ Priority: optional Section: devel Filename: pool/main/i/insighttoolkit4/insighttoolkit4-examples_4.7.0-1~nd14.10+1+nd15.04+1_all.deb Size: 2500624 SHA256: ee1b38aa0767758a463eaee5743228c7cecd39094da83e427662890b57530d3e SHA1: 10fcf8b43973e38825012028ff5d90c06082f430 MD5sum: d915c1023278e43df85eccca56780911 Description: Image processing toolkit for registration and segmentation - examples ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. . This package contains the source for example programs. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd15.04+1_all.deb Size: 5074 SHA256: f06f9047839d302dc10f85aaf2236da9c0a17622d707d3efa12dbd5677459c99 SHA1: 217ee012ed1a0c074afb8a1792d956988f053c8e MD5sum: 85264c74695d5b02fa454435884d6d4d Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 430 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.04+1), libboost-program-options1.55.0, libc6 (>= 2.4), libfftw3-single3, libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd15.04+1_i386.deb Size: 129834 SHA256: 31079fa656120680f4998b4c13067912a6219d76f4a5d3b3588d038880bd7dd5 SHA1: d95d4f725a763aee22b22fd6a7ad2ecee2aeb683 MD5sum: 4a89b57bac8e640af911015696571e0d Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: libbiosig-dev Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1374 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 316294 SHA256: 781480f9934293548e2f646f61f79ccb42b68b41e86b9da532752102249610ab SHA1: 789fc966797722372da09614bf35bfc83825c598 MD5sum: 0a08bcbd26c7aa11618bbb7e436288de 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: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 839 Depends: neurodebian-popularity-contest, libc6 (>= 2.7), 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_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 282768 SHA256: 0eed88fb84262476b3a3af345d0c5d8af1923c178c2f37ad2fc024dd954ac5b6 SHA1: 98ec9a4a4148238ae3c7318c53a9a57810903f5b MD5sum: 35ee081bf207103f5b658c8e1140b082 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: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 299 Depends: neurodebian-popularity-contest, libbiosig1 (= 1.4.1-2~nd14.10+1+nd15.04+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig1-dbg_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 70616 SHA256: 5f2c5edb46ab0bd875d7e3ec39da7b0143a76f17b153d9e10a680b3d592e4dfd SHA1: e40e30fcabc83831f3a370c5699d061c9e47e962 MD5sum: bb7c64923f2a1a7f22216ec041ff5e87 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: libcnrun2 Source: cnrun Version: 2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 246 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libstdc++6 (>= 4.6), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 80434 SHA256: 4dd93f47c53dcb01f8f2cfb48f426d22930ac50670fdec8dafadf18a1f9df305 SHA1: 73a91d3ba168691c61b5c21f24e0e1f7b3c4a470 MD5sum: 34d881d78c61656245477032da002fa5 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 110 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 21136 SHA256: 35208abb0a96c84ccb5d99ebfcd95fe3493a4f9f5cf80d31c9ce822af0607c3e SHA1: d8066378a2eeea7c310209f7fb0171a570b89215 MD5sum: b6ad553b68ba5ba859a364f5e2d517dd Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libfreeipmi-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6470 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1), libfreeipmi16 (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libfreeipmi-dev_1.4.9-1~nd15.04+1_i386.deb Size: 904408 SHA256: 8c6fde4e5d3053deae87728618afc4f087e701f85a9c08801d1a95af032571f9 SHA1: 99c5899e2463e4c2c4a93e03a2a6183617c4696c MD5sum: 10c560e860a32fb7bd3e74ef1db11c87 Description: GNU IPMI - development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libfreeipmi. Package: libfreeipmi16 Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4231 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcrypt20 (>= 1.6.1), freeipmi-common (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libfreeipmi16_1.4.9-1~nd15.04+1_i386.deb Size: 747800 SHA256: 0e34803fe56c58a14bcee8e672474ff3df10cb45b7d13982630ca1582a6e5ec4 SHA1: 1c6954357c6b23f1b943d7b7473eb24fec5d4254 MD5sum: 0eed6c593340cb966b3203c63ead9805 Description: GNU IPMI - libraries FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . OpenIPMI, KCS, SMIC, SSIF, LAN drivers, and an IPMI API in a C Library. Package: libfreenect-bin Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 205 Depends: neurodebian-popularity-contest, freeglut3, libc6 (>= 2.4), libfreenect0.5 (>= 1:0.5.2), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.4.0) Breaks: libfreenect-demos (<< 1:0.1.2+dfsg-1) Replaces: libfreenect-demos (<< 1:0.1.2+dfsg-1) Homepage: http://openkinect.org/ Priority: extra Section: utils Filename: pool/main/libf/libfreenect/libfreenect-bin_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 54330 SHA256: cd62389d4c8231c084a513a897cb7fadd815e4caf90a6080be724d1412f81cea SHA1: aa22c68c52f37f4ee1798bf7e88a191093614632 MD5sum: c115590e0532075bbd1e5bb41a0035e3 Description: library for accessing Kinect device -- utilities and samples libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package includes utilities and sample programs for kinect. Package: libfreenect-demos Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 12 Depends: neurodebian-popularity-contest, libfreenect-bin Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-demos_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 8532 SHA256: 13856d1f094da63d04f59672a49c8207d8a7251c0c90e1ec11cf63ac1c4cb1aa SHA1: 8fd505b01ebfe0f3ff18aad62c9c1aff3cbc05a9 MD5sum: 95c93956258ee48fa612c9ef5f88ef83 Description: library for accessing Kinect device -- dummy package libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package is a metapackage to do the transition from libfreenect-demos to libfreenect-bin. This package can be removed after installation. Package: libfreenect-dev Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 62 Depends: neurodebian-popularity-contest, libfreenect0.5 (= 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1), libusb-1.0-0-dev (>= 1.0.18~) Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libdevel Filename: pool/main/libf/libfreenect/libfreenect-dev_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 19280 SHA256: 51b53c7cd2846b2916fa2487eb367474ed6ff1da933eb3468e5aea677fe8448f SHA1: 04ceec83e05480d71a3ff53474b9be4884f6ff73 MD5sum: d0bae5fe0e3d1ef56569faaa449a793d Description: library for accessing Kinect device -- development files libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This is the development package containing the libraries and header for software development with libfreenect. Package: libfreenect-doc Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 786 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://openkinect.org/ Priority: extra Section: doc Filename: pool/main/libf/libfreenect/libfreenect-doc_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_all.deb Size: 133088 SHA256: 0834cd7a553b3ddd2aea16144aa81e7284500b06624e4f38b63b125eaef7e0eb SHA1: b3665cab138b734212d22b1dfd72114ae180b92c MD5sum: dabc71d31109694a198434f25498d5d6 Description: library for accessing Kinect device -- documentation libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the documentation of the API of libfreenect. Package: libfreenect0.5 Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 112 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.7), libusb-1.0-0 (>= 2:1.0.12) Conflicts: libfreenect Multi-Arch: same Homepage: http://openkinect.org/ Priority: extra Section: libs Filename: pool/main/libf/libfreenect/libfreenect0.5_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 45086 SHA256: 3bbbb989fce43bb8d5dd7601919eaf186cba2909257712457c1dde1d8be3ccc2 SHA1: f44a6abf46e7dbbb402622249eb55050ea9b75a7 MD5sum: 66f34244fdba08ebfdf075eb3c1f09f9 Description: library for accessing Kinect device libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package contains the shared library of libfreenect. Package: libipmiconsole-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 434 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1), libipmiconsole2 (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmiconsole-dev_1.4.9-1~nd15.04+1_i386.deb Size: 105824 SHA256: 930f3126e4011e9eabbea33dd00794f204e2e71414e2234bbb60ae3e82f33213 SHA1: b3a9f929c4a25f6f04190cf4c46136fd10dac293 MD5sum: 8d6ae407300a08b0681c341d7baf6c4c Description: GNU IPMI - ipmiconsole development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmiconsole. Package: libipmiconsole2 Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 305 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmiconsole2_1.4.9-1~nd15.04+1_i386.deb Size: 88198 SHA256: 6eb536b7999cb93c7701853a5473f17d0ddb2875f319cf4270aa9bec1bd1df5e SHA1: 038293196c6aa36c0f1e7a48daea8392018a6a9b MD5sum: 5ce901aebe219204a5ec9bce9310e39a Description: GNU IPMI - Serial-over-Lan library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for Serial-over-Lan (SOL). Package: libipmidetect-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1), libipmidetect0 (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmidetect-dev_1.4.9-1~nd15.04+1_i386.deb Size: 33470 SHA256: 3086d2dff2fcc18362d68fe99c8a1d8a369ef02579f72f88852f231fa14328b3 SHA1: e94d3ac8b5b2ccfa27da5bb4442f2dab429b8d98 MD5sum: 1968dd539f5f50d425bd54107ef440f3 Description: GNU IPMI - ipmidetect development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmidetect. Package: libipmidetect0 Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 63 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), freeipmi-common (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmidetect0_1.4.9-1~nd15.04+1_i386.deb Size: 27314 SHA256: 7f65a3e85c193ae79a5aceea474763dcb5b61178af4e6a1b6472194ebf440715 SHA1: e917db94ec169f9a867b8c9825f44aa8c8054054 MD5sum: 41b5ac1f8b5290f11f217734457555dc Description: GNU IPMI - IPMI node detection library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for IPMI node detection. Package: libipmimonitoring-dev Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 283 Depends: neurodebian-popularity-contest, freeipmi-common (= 1.4.9-1~nd15.04+1), libipmimonitoring5a (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libdevel Filename: pool/main/f/freeipmi/libipmimonitoring-dev_1.4.9-1~nd15.04+1_i386.deb Size: 63604 SHA256: 8def71cccf8cd7f73a2e11c4e32c5450fd2ee8f0c471cd3079b5dbdbabfd154f SHA1: 90dc2bb667904d0eb87d0da2ee2a4e897a84d97a MD5sum: ee11e2bd14c5664dd2f14ddac3e3c6e8 Description: GNU IPMI - ipmimonitoring development package FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . This is the development package for libipmimonitoring. Package: libipmimonitoring5a Source: freeipmi Version: 1.4.9-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfreeipmi16 (>= 1.4.4), freeipmi-common (= 1.4.9-1~nd15.04+1) Homepage: http://www.gnu.org/software/freeipmi/ Priority: extra Section: libs Filename: pool/main/f/freeipmi/libipmimonitoring5a_1.4.9-1~nd15.04+1_i386.deb Size: 45566 SHA256: 0c72f216f6b474c147ccaec80881a038be984ce97c68b8c6816938ccb0d99e72 SHA1: 676e194f531489c51e81dc8863f8672f0d9bc452 MD5sum: 46df3b5585910e94efeb712c3a2dd87d Description: GNU IPMI - Sensor monitoring library FreeIPMI is a collection of Intelligent Platform Management IPMI system software. It provides in-band and out-of-band software and a development library conforming to the Intelligent Platform Management Interface (IPMI v1.5 and v2.0) standards. . A library for sensor monitoring. Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 95 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd15.04+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd15.04+1_i386.deb Size: 13862 SHA256: dbf6bf5b81196164c6329598de0b2d2fed1b98aee0b04b140d96e669030e7e54 SHA1: 563cec9fd8d46dbbcc8af35f3eeedf0be67906ed MD5sum: 496a4eaf21cea9324acfb1f3f0f7d0d6 Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1905 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd15.04+1_all.deb Size: 159234 SHA256: 44bfafd717b2b528bb093e7580194b142dd253fb20aba439a742c4a721c2c336 SHA1: 3585d20b7e6eb7c181da2b4dbaec2c13448f3c6e MD5sum: ea2a85b46b120a8ccab0a6f88fd30b33 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 377 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libhdf5-8, libpugixml1 (>= 1.4), libstdc++6 (>= 4.4.0) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd15.04+1_i386.deb Size: 86314 SHA256: b18da7446c7113e823977a082bb79ac13e5fdfdb1de12a9df83c88f44a1d615f SHA1: f0011ab34dcb047d1e07f1047fdf1fb810a1feb7 MD5sum: 2e8f7715844b1df24a5615498b51bc6e Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libmia-2.0-8 Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 21384 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libboost-filesystem1.55.0, libboost-regex1.55.0, libboost-serialization1.55.0, libboost-system1.55.0, libboost-test1.55.0, libc6 (>= 2.4), libdcmtk2 (>= 3.6.0), libfftw3-single3, libgcc1 (>= 1:4.1.1), libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.42.0), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libitpp8, libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.9), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Homepage: http://mia.sourceforge.net Priority: optional Section: libs Filename: pool/main/m/mia/libmia-2.0-8_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 3380396 SHA256: fe019db72dc75d27c41aa0270fdc5fc7ae02ad2ab74e418e40e94d24a16e13cf SHA1: 3c00da66139cbf6b109702ab2fdaeb7ca2e32aed MD5sum: c9756aa872121d8e32e1ccb91c877bd7 Description: library for 2D and 3D gray scale image processing libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. Package: libmia-2.0-8-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 61048 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/libmia-2.0-8-dbg_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 56514370 SHA256: f3149e94d959a3d7a7edc809bd8cf1ab6ae5c97266e78a229acb301a271a5603 SHA1: 7563fedf1446915616c8cc659e0532d53dffea1a MD5sum: 561d2115c2ba97bece0257d29d4df3a6 Description: Debug information for the MIA library libmia comprises a set of libraries and plug.ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. libmia is library for general purpouse 2D and 3D gray scale image processing. This package provides the debug information of the library. Package: libmia-2.0-dev Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1087 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libxml++2.6-dev (>= 2.34.1), libitpp-dev (>= 4.2), libtbb-dev, libgsl0-dev, libboost-all-dev (>= 1.46.1), libfftw3-dev, libblas-dev Recommends: libmia-2.0-doc Homepage: http://mia.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/m/mia/libmia-2.0-dev_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 171354 SHA256: d6b5d60224f0ed4368a637716040bbabe06fc12083bc8983305088dfca51adb7 SHA1: 707c13783dcbd9d3c178fbfccecdbce53b226fff MD5sum: f43f49b52b40082edeb82c0c76b48e31 Description: library for 2D and 3D gray scale image processing, development files libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the development files for the library. Package: libmia-2.0-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15009 Depends: neurodebian-popularity-contest, libjs-jquery Enhances: libmia-2.0-dev Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/libmia-2.0-doc_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 1145952 SHA256: eec23fc789872924dfa1f6ad91b5f121ff036b3c5d6903edccf92b1c04cf6d2a SHA1: dc4ee452a72fc174049d605afe20fa0b55d94b2a MD5sum: 6702ad33379715aeeed5ab4cf930df61 Description: library for 2D and 3D gray scale image processing, documentation libmia comprises a set of libraries and plug-ins for general purpose 2D and 3D gray scale image processing and basic handling of triangular meshes. The libraries provide a basic infrastructure and generic algorithms, that can be specialized by specifying the apropriate plug-ins. This package provides the Doxygen generated API reference. Package: libopenwalnut1 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6588 Depends: neurodebian-popularity-contest, fonts-liberation (>= 1.0.0), libboost-date-time1.55.0, libboost-filesystem1.55.0, libboost-regex1.55.0, libboost-system1.55.0, libboost-thread1.55.0, libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libopenscenegraph100, libopenthreads20, libstdc++6 (>= 4.9) Suggests: nvidia-glx | fglrx-glx Homepage: http://www.openwalnut.org Priority: extra Section: libs Filename: pool/main/o/openwalnut/libopenwalnut1_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 1310372 SHA256: 092896d4acd2bbf4673be8ae666424f8d0f194a4e59076c712d5f43df2128a39 SHA1: 8a65f18d256cdb0564d86d8e608ce6a67b4f170f MD5sum: 25bb514d462edc619394aaa52b8be0c1 Description: Framework for multi-modal medical and brain data visualization OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API of OpenWalnut. Package: libopenwalnut1-dev Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1997 Depends: neurodebian-popularity-contest, libopenwalnut1 (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libgl1-mesa-dev | libgl-dev, libopenscenegraph-dev (>= 3.0.0), libopenthreads-dev (>= 3.0.0), libboost-dev (>= 1.46.0), libboost-program-options-dev (>= 1.46.0), libboost-thread-dev (>= 1.46.0), libboost-filesystem-dev (>= 1.46.0), libboost-date-time-dev (>= 1.46.0), libboost-system-dev (>= 1.46.0), libboost-signals-dev (>= 1.46.0), libboost-regex-dev (>= 1.46.0), libeigen3-dev (>= 3.0.0) Homepage: http://www.openwalnut.org Priority: extra Section: libdevel Filename: pool/main/o/openwalnut/libopenwalnut1-dev_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 249510 SHA256: 8c82534e34df5d7caa9fe870b3e9f40ec5a51496d212ace1bf3c8d8d1a68fc57 SHA1: 88b1be9d10899d82c12dfb3fd5de03f3f2a54970 MD5sum: 4aed913a22ffe8e426943e5ef821eab2 Description: Development files for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the headers for the core API of OpenWalnut. Package: libopenwalnut1-doc Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 48161 Depends: neurodebian-popularity-contest, libjs-jquery Homepage: http://www.openwalnut.org Priority: extra Section: doc Filename: pool/main/o/openwalnut/libopenwalnut1-doc_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 2689446 SHA256: 239e6402859ac1d87461dc8cee6fe3ca7e393e5b01fb9b37d1e9dc02c616ac7f SHA1: 44960c6c33539e8aeb9e4d89eef0d45de7ded0e3 MD5sum: 8ba9f709c27cf22714f22b95dbd409de Description: Developer documentation for the OpenWalnut visualization framework OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the core API documentation of OpenWalnut. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 659 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 141364 SHA256: bb5099a216df263162d52323a1ad2a62b049d84c3a77fa8ca8d91d6c2f396722 SHA1: bddf4ca7346a003115879f4d770855fc8f67eb64 MD5sum: 8207ba4a3bb105c1093d9490b0aeccaa Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 514 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 149006 SHA256: 20e4ec1dd8f9a3584bfc97bab6d6d5cdbf3d89092254677fbd6e768727caa57c SHA1: 4ce345c2e07a4486b8c053e934104940fe31ce63 MD5sum: 8f6429bfa8152d6ab48021fa7d2a3d73 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1198 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 337986 SHA256: 13a78ff8efc6e4c59943f8ccf3b79cd80e9fb10994a98000fb70e2145146c7ea SHA1: 6563a4f50bd12923fb7bca3e0823acf5a03599f7 MD5sum: cc36890d416abf788f52a82d9792c202 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: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 264 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.8 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd15.04+1_i386.deb Size: 73814 SHA256: 327801c3a2883dac72d3dd1c75b78558ae37148ff557fb3420e1e2455ce787db SHA1: 0e487768a78a16e9d21a0da5949c57adaeaae835 MD5sum: 091e2d94c27cdfb913bf21cfef60976d Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1480 Pre-Depends: multiarch-support Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libgdcm2.4, libstdc++6 (>= 4.9), libvtk5.8, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd15.04+1_i386.deb Size: 434276 SHA256: 7c5d3d40e69623a0549470c592dca2b3fd4309a4e3f590e4e0569451b6ee1516 SHA1: 5d2acb5030475733a6d33e6952adc1a68db48e4e MD5sum: 7b790d5ff3b5a9a8af5ec92468a32180 Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 531 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd15.04+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd15.04+1_i386.deb Size: 80876 SHA256: 2a9f8f4dba2bb221063316a4aab74c54917a59927fce094a7c935dc1f91d8ecc SHA1: e8745fbc7c63002bfdfd7b24e5a9bc9fdbbfef86 MD5sum: dd95ce0aa0912a754bc2745480a3b6c4 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.0.1-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 38742 SHA256: 859e3dbbebbfbe9396161a1018027db3b5e9653d4bf307586fcfebdcfe2a098b SHA1: 762d707705f68f655a8f3abe8dda7e7ecbb97273 MD5sum: 1d6772829e727251aca33234ae0cabd8 Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: matlab-support-dev Source: matlab-support Version: 0.0.21~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 39 Depends: neurodebian-popularity-contest Conflicts: matlab-dev (<= 0.0.14~) Replaces: matlab-dev (<= 0.0.14~) Priority: optional Section: devel Filename: pool/main/m/matlab-support/matlab-support-dev_0.0.21~nd15.04+1_all.deb Size: 7590 SHA256: 6a0f25f10a9072a0efe1bcebf7deababf8430d2420a807362a7a3e67ef409139 SHA1: f2705787305a11817d05b7b9fcef7f06de6a9668 MD5sum: 0f6fe1c1f34a343f405f67eefe6b8de8 Description: helpers for packages building MATLAB toolboxes This package provides a Makefile snippet (analogous to the one used for Octave) that configures the locations for architecture independent M-files, binary MEX-extensions, and their corresponding sources. This package can be used as a build-dependency by other packages shipping MATLAB toolboxes. Package: mia-tools Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7626 Depends: neurodebian-popularity-contest, libmia-2.0-8 (= 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libboost-filesystem1.55.0, libboost-regex1.55.0, libboost-serialization1.55.0, libboost-system1.55.0, libboost-test1.55.0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libglibmm-2.4-1c2a (>= 2.42.0), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libjpeg8 (>= 8c), libnlopt0 (>= 2.3), libopenexr6 (>= 1.6.1), libpng12-0 (>= 1.2.13-4), libstdc++6 (>= 4.9), libtbb2, libtiff5 (>= 4.0.3), libvistaio14 (>= 1.2.14), libvtk5.8, libxml++2.6-2 (>= 2.36.0) Recommends: mia-doc Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mia/mia-tools_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 1416172 SHA256: 65653fafbfa97a36ba97e3f848bc2f454ba734baf2bb97957d692203576c34de SHA1: 747afeeb7883e08f6bbccfa7b1a4321e397349bf MD5sum: 4f6c532ce87ec8dc71bf001c7f5e8a23 Description: Command line tools for gray scale image processing Command lines tools to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-dbg Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 27178 Depends: neurodebian-popularity-contest, mia-tools (= 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mia/mia-tools-dbg_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 25453790 SHA256: 83164052f91c7e2409630f295b7f49cd171979623d6a351b21edb03c2cb994c4 SHA1: 703c8f09dd3c4c210e0a5b8015fba2cc200bf630 MD5sum: 38be5ebe70127afec20981cb917f6b56 Description: Debugging information for the MIA command line tools Debug information for the MIA command lines tools. These tools provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statiistics over images. Package: mia-tools-doc Source: mia Version: 2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1138 Depends: neurodebian-popularity-contest Enhances: mia-tools Homepage: http://mia.sourceforge.net Priority: optional Section: doc Filename: pool/main/m/mia/mia-tools-doc_2.0.13-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 72292 SHA256: 92cce88a1b27d71f7eb663c7e558a6e54dccd1f27cb8eeb1e1935a8a90fe4a68 SHA1: 9b3a267bf5c8f73ca78c1a83ce87c33b772ceda2 MD5sum: 4616bc37fbc9cf8c7a50b75196370c31 Description: Cross-referenced documentation of the MIA command line tools Cross referenced documentation of the command line tools and plug-ins that are provided by the MIA gray scale image processing tool chain. These lines tools to provide the means to run general purpose image processing tasks on 2D and 3D gray scale images, and basic operations on triangular meshes interactively from the command line. Supported image processing algorithms are image filtering, combining, image registration, motion compensation for image series, and the estimation of various statistics over images. Package: mriconvert Version: 1:2.0.8-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5360 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), libwxbase3.0-0 (>= 3.0.2), libwxgtk3.0-0 (>= 3.0.2) Homepage: http://lcni.uoregon.edu/~jolinda/MRIConvert/ Priority: optional Section: science Filename: pool/main/m/mriconvert/mriconvert_2.0.8-1~nd15.04+1_i386.deb Size: 824268 SHA256: f56d4bfc8098a547d41276d96178880046a9f5db88384408171785f1873704e5 SHA1: fc66d12020ecf457e6523ba141937b6284eea518 MD5sum: 8545710da4a270472109d0af9fc86eac Description: medical image file conversion utility MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats. Package: mricron Version: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 12491 Depends: neurodebian-popularity-contest, libatk1.0-0 (>= 1.12.4), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.24.0), libpango-1.0-0 (>= 1.14.0), libx11-6, mricron-data Recommends: pigz Suggests: mricron-doc, fsl Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 2060084 SHA256: dea84e77dd2025f8340fbb8508a35be7817dd72cdb38ab25994e0b981e3d1836 SHA1: 0297230c3bff17dbd779ff08ee9b7686698388f8 MD5sum: 7e969a4252b2b48c92b9d58055cdf207 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: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1676 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 1658370 SHA256: 3a0cc08f9c273a3eae09ac5d843094184d4756c0f14d7dbcec6eb34d399cf31e SHA1: e711e9eb9bbbdad7eb9fc866ace4a9bda25f9b41 MD5sum: 3624ac3b3d2ed52978d33bb1e7369fad 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: 0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 980 Depends: neurodebian-popularity-contest Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20140804.1~dfsg.1-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 577378 SHA256: b6a1b67836ca1995b1523a5bfb18d45e1dbac66bd0fb56affc9d0630dbbaea51 SHA1: fe8f8d7e11063bdc1449c7ecff244746bcb4afe8 MD5sum: 64a09dcdc2147a3a86804a1df22f3399 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: mridefacer Version: 0.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 673 Depends: neurodebian-popularity-contest, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.1-1~nd15.04+1_all.deb Size: 637032 SHA256: bb4de0cb9846e4237cf8e0e2dd0b14c2769cf97383c6c01aee94ae431922048f SHA1: 12137ee6ef7c6b33c584d8b3d5e4a15a3291282c MD5sum: 8982f934373003078c67d1308fec9ba1 Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: netselect Version: 0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 46 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 31410 SHA256: 69caffbb0899470d8aae13ad94b2c2e3edd11a44651faacc4575c5371dc0c2e7 SHA1: 2c385e7d3197c6be21dc4ca0d1db611d134908d2 MD5sum: b39f93d399ae5d42076d5592a51a1435 Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 16868 SHA256: e81cf65d7d6444d0b0436350b5b05675d3272864df42b4e8004382b1c9619ab0 SHA1: 517a1b86da9da2a81ea9772568f318a449b7601d MD5sum: 596b0832af2d83d7970f6912c074838a Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 71 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.2~nd15.04+1_all.deb Size: 33408 SHA256: 1c36f207e5ae6a9f93eea4406333b2983094a906040a616cf5cc0bc05a0e8fe6 SHA1: 20c55e48b5b37bdf7b3e95fabad4afa563814d73 MD5sum: eb53c57dfa768dc1bb53f90da5fad09e Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11 Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.2~nd15.04+1_all.deb Size: 10068 SHA256: a8ebb76655ed20d69c63642ade6d68357000fd86b5a71e9de326d10498d6b057 SHA1: 38eea502322918a885e8594e32e7c58b600a7251 MD5sum: 21c6d6392227e3e72729dbaf37e595e9 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.2~nd15.04+1_all.deb Size: 115958 SHA256: 16243167de3bcfb692e790d2cb07166228a3eb20a38c4892f03580b75773bd7c SHA1: b8c360286b94a46c0abff1a5235bcf9d733c099c MD5sum: e38fd9952e1ae7bea51e97d182545682 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 83 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.2~nd15.04+1_all.deb Size: 32252 SHA256: 36f566cf7881e509bac03d7fd4c9767e0c73d5e232486a6a48a1537f606df16a SHA1: ddb9c7876b4852637eb21d19f3cc857241f9b0b3 MD5sum: ac7c245734d42a3f95e5bfdf86c7e076 Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.2~nd15.04+1_all.deb Size: 12164 SHA256: 22b1dd731133cc766f8cbde861d7accd538aafe8f8626aae58927d81df444459 SHA1: 2775eb4bb97ad87c5ae35e07c98afc0120f072b8 MD5sum: 32612af4d4d644ccc5a09b0cd53bfc6d Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . 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 (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.5.16.1+ds-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2726 Depends: neurodebian-popularity-contest, g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.6.6-7~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.16.1+ds-1~nd15.04+1_all.deb Size: 591052 SHA256: d8199846499516b9d2152850bfeaadeba944293c1d0d1c22203fe7c1a7c8e8d4 SHA1: 1b00f9d50a01f7629a853c08a4aae5845cc656a8 MD5sum: 9230474b19e1d7d757668a47f32e8ec5 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: octave-biosig Source: biosig4c++ Version: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), libbiosig1, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), liboctave2 Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 20538 SHA256: 212665132d2bef592e12371c83d306d7cd8f9c701f1fa0cb7a793d3771b76619 SHA1: 7aa10e98fc362a506818cfa9f6ac08fae4e85818 MD5sum: cadcf194099dd2e550a935175c2419d6 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: 3.0.12.20150725.dfgs1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4229 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.7), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), liboctave2, libopenal1 (>= 1.14), libpciaccess0 (>= 0.8.0+git20071002), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.12.20150725.dfgs1-1~nd15.04+1), psychtoolbox-3-lib (= 3.0.12.20150725.dfgs1-1~nd15.04+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_3.0.12.20150725.dfgs1-1~nd15.04+1_i386.deb Size: 845518 SHA256: 238b61065f2300f8e7859073560d0c2a73631f5ec70b85457ae5e00ed3734245 SHA1: 26b969e0819bd0f3ee7baedb98a430a0261493d9 MD5sum: 25ec026b0c871133a754f9c421f1dfd0 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: openwalnut-modules Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 19277 Depends: neurodebian-popularity-contest, libbiosig1, libboost-filesystem1.55.0, libboost-regex1.55.0, libboost-system1.55.0, libboost-thread1.55.0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libnifti2, libopenscenegraph100, libopenthreads20, libopenwalnut1, libstdc++6 (>= 4.9) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-modules_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 3525144 SHA256: 97d421117c26fe62dac04783f28a4353d619edde0bc75c11c54ac28720264c7f SHA1: d4320eb8e23c131fb9a321fc2c5db6b8a5f6720d MD5sum: 5d055aadbbfa76d469e0d8ae04e32794 Description: Loaders, algorithms and visualization modules for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the currently available modules for OpenWalnut. Package: openwalnut-qt4 Source: openwalnut Version: 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2068 Depends: neurodebian-popularity-contest, libboost-filesystem1.55.0, libboost-program-options1.55.0, libboost-regex1.55.0, libboost-system1.55.0, libboost-thread1.55.0, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libopenscenegraph100, libopenthreads20, libopenwalnut1, libqt4-opengl (>= 4:4.6.0), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libqtwebkit4, libstdc++6 (>= 4.9), libx11-6 Recommends: openwalnut-modules (= 1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://www.openwalnut.org Priority: extra Section: science Filename: pool/main/o/openwalnut/openwalnut-qt4_1.4.0~rc1+hg3a3147463ee2-1~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 775764 SHA256: 120b67dbae2b7ed1a6c3bb9b524cfe6ac2c4904467701d3a31888b892ffc674b SHA1: 03c64c893656af7692276fc7308f6f55e3d4b97e MD5sum: 555997549f3df5bba5e3ebd616bf1343 Description: Qt based user interface for OpenWalnut OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs. . This package contains the QT4 GUI for OpenWalnut. Package: psychopy Version: 1.82.02.dfsg-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14481 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libavbin0, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.82.02.dfsg-1~nd15.04+1_all.deb Size: 6063402 SHA256: 17782789402ea78ba5095281d77de2c226e893e0672c4d551451c170e7e928f9 SHA1: 6b7be7599fbaad06f071d6c91839d6ac1023610e MD5sum: c41e21b4016cf42c9bfc298679ab7094 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.12.20150725.dfgs1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 233281 Depends: neurodebian-popularity-contest Recommends: subversion Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.12.20150725.dfgs1-1~nd15.04+1_all.deb Size: 23787558 SHA256: 5b1512ff5f82e4c6718dd86383ff9525bc8d01aeffd33019ed6c5f439a84f815 SHA1: 70e03d3d70c36cecc6c7a9f822562d1511a6549e MD5sum: a2ff9bafe21c8ef059f0e44dea0e98b3 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: 3.0.12.20150725.dfgs1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3475 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.12.20150725.dfgs1-1~nd15.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.12.20150725.dfgs1-1~nd15.04+1_i386.deb Size: 690996 SHA256: 03ed90dc9c19e9997853ffe4a17a9f261ecbf859d68167948844b80af406f4ff SHA1: 3e806048428ed5becc7412f58e2730fc1e778f95 MD5sum: c40384c09ed62305d758fcfe6cd2e02c 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: 3.0.12.20150725.dfgs1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.9.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.12.20150725.dfgs1-1~nd15.04+1_i386.deb Size: 56402 SHA256: 881fcfef9322b17f2e7edf1a8868f642cfcccb31125ffc60297f1f96937cb9c3 SHA1: 1453b4e26b45ed9a27cda81036d6b700d5f928e5 MD5sum: 7f3e88d815c4a98e899cd9ac631cd899 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: 1.4.1-2~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 210 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-support (>= 0.90.0), libbiosig1, libc6 (>= 2.4), libcholmod2.1.2, 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_1.4.1-2~nd14.10+1+nd15.04+1_i386.deb Size: 44532 SHA256: 36c2d4d391312d6e427296e2fe0cd87cb10c4a32b6f343a465d911595aa09a56 SHA1: 0a0f07dca6d09e589232a1db57ad792c447e317d MD5sum: 725d9a82f4ea2d2824cea8d1a8c294b1 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-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python-lxml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python-citeproc_0.3.0-1~nd15.04+1_all.deb Size: 80538 SHA256: e78c5d6b033c60fb1eb954d02a9213c98a0d4c3f5b922406133a43570db326c5 SHA1: e6b0aec260ad4942e8891d4a4ca20a38aa87c1af MD5sum: f9330d678d300a68ff73013a381d5bd3 Description: Citation Style Language (CSL) processor for Python Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python modules. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 516 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd15.04+1_all.deb Size: 78364 SHA256: 76ce758554a0d3ef2b9923d4bc53eaa13e8eb9190cc3c739402983d33c5950bf SHA1: 61851ee716e4311427dbc8d3f87cca4364f8e987 MD5sum: 84cb19726c92df822ddbee954a5fb863 Description: DICOM to Nifti conversion DICOM to Nifti conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a Nifti header extension or written out as a JSON formatted text file. . This package provides the Python package, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dicom Source: pydicom Version: 0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1522 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://pydicom.org/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.9-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 357850 SHA256: 464e7732ae7a71154b8bc2b4b9c0ecb78de2cff7b6264b10e9ef8a552381281c SHA1: f381c431cc2550b40cc7826952b7568cb7d1db10 MD5sum: 65216a1227d059aed3b67923110da4ed 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-dipy Source: dipy Version: 0.9.2-1~nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4609 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-dipy-lib (>= 0.9.2-1~nd14.10+1+nd15.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy_0.9.2-1~nd14.10+1+nd15.04+1_all.deb Size: 2338482 SHA256: af60e09e289d61c286ca64ed5caab8b7f39739d1a77c8b68d8d3f358a0a8fe53 SHA1: c8eb040015cc00375d96dece09867a3612b8bc98 MD5sum: c244c81ba67847bf36cf0022a693c718 Description: toolbox for analysis of MR diffusion imaging data Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. It features: - Reconstruction algorithms, e.g. GQI, DTI - Tractography generation algorithms, e.g. EuDX - Intelligent downsampling of tracks - Ultra fast tractography clustering - Resampling datasets with anisotropic voxels to isotropic - Visualizing multiple brains simultaneously - Finding track correspondence between different brains - Warping tractographies into another space, e.g. MNI space - Reading many different file formats, e.g. Trackvis or NIfTI - Dealing with huge tractographies without memory restrictions - Playing with datasets interactively without storing Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.9.2-1~nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12500 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://nipy.org/dipy Priority: optional Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.9.2-1~nd14.10+1+nd15.04+1_all.deb Size: 10229524 SHA256: 67636668a73b266f95714464d5aeec2ce1fb88dce069c396fcb3927eda99c7a4 SHA1: d5cf3fda3cf51161522a34eb2cf83947c260f885 MD5sum: 8bc1cc163594cc4fcdebce9bf9a543bf Description: toolbox for analysis of MR diffusion imaging data -- documentation Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.9.2-1~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5758 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://nipy.org/dipy Priority: optional Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.9.2-1~nd14.10+1+nd15.04+1_i386.deb Size: 938876 SHA256: 4e1e3fcadd7b7cad5693cc1d884b2b402bf2e358bb7b96532c82c3f0e5328d66 SHA1: f7c745c5f74a095a7724dec535d242eda19aaa3e MD5sum: 20952c1e78858e1c36342e32a4b043d8 Description: toolbox for analysis of MR diffusion imaging data -- extensions Dipy is a toolbox for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-expyriment Version: 0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2389 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-support (>= 0.90.0), python-pygame (>= 1.9.1~), python-opengl (>= 3.0.0), ttf-freefont, libjs-jquery, libjs-underscore Recommends: python-serial (>= 2.5~), python-numpy (>= 1.3.0~) Suggests: python-parallel (>= 0.2), python-pyxid Homepage: http://www.expyriment.org Priority: optional Section: science Filename: pool/main/p/python-expyriment/python-expyriment_0.7.0+git34-g55a4e7e-3~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 697408 SHA256: f74dc892bec012e1c5f95ddca15a82f6fed4a9429a3f169f01e0c4f307627130 SHA1: a5db64adb2e4e61043b162b718ed250b0ffe35a5 MD5sum: 23b727e97cb4f65e8f22843ec447f48d Description: Python library for cognitive and neuroscientific experiments Expyriment is a light-weight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments. The major goal is to provide a well-structured Python library for a script-based experiment development with a high priority on the readability of the resulting programme code. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones. Package: python-freenect Source: libfreenect Version: 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 147 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libc6 (>= 2.4), libfreenect0.5 (= 1:0.5.2+git6-g5455843+dfsg-1~nd15.04+1), libpython2.7 (>= 2.7) Suggests: python-matplotlib, python-opencv Provides: python2.7-freenect Homepage: http://openkinect.org/ Priority: extra Section: python Filename: pool/main/libf/libfreenect/python-freenect_0.5.2+git6-g5455843+dfsg-1~nd15.04+1_i386.deb Size: 46842 SHA256: 8cc02883d50ade55cc823304f3c99d39601646fad22680973bbef39597b2f251 SHA1: ddb83cd9af164701f0274c4d891703955902045c MD5sum: b60b481df313fdd6e249932fce23b4e0 Description: library for accessing Kinect device -- Python bindings libfreenect is a cross-platform library that provides the necessary interfaces to activate, initialize, and communicate data with the Kinect hardware. Currently, the library supports access to RGB and depth video streams, motors, accelerometer and LED and provide binding in different languages (C++, Python...) . This library is the low level component of the OpenKinect project which is an open community of people interested in making use of the Xbox Kinect hardware with PCs and other devices. . This package provides freenect extension to use libfreenect functionality from Python and includes some demo scripts. Package: python-git Version: 1.0.1+git137-gc8b8379-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1498 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-gitdb (>= 0.6.4), git (>= 1:1.7) | git-core (>= 1:1.5.3.7), libjs-jquery Suggests: python-smmap Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_1.0.1+git137-gc8b8379-1~nd15.04+1_all.deb Size: 304728 SHA256: 4ed65e6932df3ae455597d310eab791ab24dcb3888103aa46d52caeb08cb305a SHA1: 9779e7d69612678db90ba4058652e9d823300aa0 MD5sum: a03ef4f481735c68772a1a86c80f43d4 Description: Python library to interact with Git repositories python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. Python-Version: 2.7 Package: python-gitdb Version: 0.6.4-1~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 209 Depends: neurodebian-popularity-contest, python-smmap, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4) Provides: python2.7-gitdb Homepage: https://github.com/gitpython-developers/gitdb Priority: extra Section: python Filename: pool/main/p/python-gitdb/python-gitdb_0.6.4-1~nd14.10+1+nd15.04+1_i386.deb Size: 56280 SHA256: daa8762b661e9ca5835ac0092182fb628f9727f27151baaeaeb24b59014f9731 SHA1: 83b38880ab153cf84a13570967b3c1e5320cc4e3 MD5sum: dd8373bfc424efcda532cddbf6c1865e Description: pure-Python git object database The GitDB project implements interfaces to allow read and write access to git repositories. In its core lies the db package, which contains all database types necessary to read a complete git repository. These are the LooseObjectDB, the PackedDB and the ReferenceDB which are combined into the GitDB to combine every aspect of the git database. Package: python-joblib Source: joblib Version: 0.9.3-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 345 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.9.3-1~nd15.04+1_all.deb Size: 78080 SHA256: 24ecb1f84ab29c369a03199ed49811888fc703c94a19b4e1c13cb4f068a1c1a9 SHA1: f2d2fc415c2813c840e39c4bb27002a18989c2a5 MD5sum: 93c9b2066a5c673a976caade6fe602cd 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. . This package contains the Python 2 version. Package: python-lda Source: lda Version: 1.0.2-9~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1246 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd14.10+1+nd15.04+1_i386.deb Size: 236586 SHA256: c3533d38e10d2aaae7e91bed7f68333bfd81865b843ecbfd194bc96212e95d3d SHA1: 50f0c84e9a3edd8e31a7b2a88f129a276959c790 MD5sum: 98172f1ea345895a7853aa7f01f17578 Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-mne Version: 0.10.1+dfsg-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8878 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-sklearn, python-matplotlib, python-joblib (>= 0.4.5), xvfb, xauth, libgl1-mesa-dri, help2man, libjs-jquery, libjs-jquery-ui Recommends: python-nose, mayavi2 Suggests: python-dap, ipython Provides: python2.7-mne Homepage: http://martinos.org/mne Priority: optional Section: python Filename: pool/main/p/python-mne/python-mne_0.10.1+dfsg-1~nd15.04+1_all.deb Size: 4321838 SHA256: 39b5a720d4b690f76d0a2ca64d5c23d116bd3ddced7f0792382f90512c5c0f57 SHA1: 23a823007fa31f6040576123ec22bd48f3dbd410 MD5sum: 9fd2589bac3f8289e9bccf0750e6e83d Description: Python modules for MEG and EEG data analysis This package is designed for sensor- and source-space analysis of MEG and EEG data, including frequency-domain and time-frequency analyses and non-parametric statistics. Package: python-mvpa2 Source: pymvpa2 Version: 2.4.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8245 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.4.1-1~nd15.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.4.1-1~nd15.04+1_all.deb Size: 5054478 SHA256: ee442cf064d20a41cb3cfd5c087700718dbc71ce9a1286a99f7ae5deb7313718 SHA1: 97fe588967fe6cc4f1b29945a29d4cbe51874c2e MD5sum: 161f0dc006c45d2a13971111f3c56bb4 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.4.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 29664 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.4.1-1~nd15.04+1_all.deb Size: 4767868 SHA256: 97616b34f5734f3fef014853a8349d593afe8e78e2b3ccb5429a1e978d7d7273 SHA1: 72a0f9a918e785d54a5c0986ca6ed7a6f65d7ca7 MD5sum: 2495b69a019b9856838e185cd5f89cdd 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: 2.4.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 171 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.4.1-1~nd15.04+1_i386.deb Size: 47818 SHA256: ea0d32123e1a7374d4539b3cf3bf7a12df444e55078b77218beb010dddd4d50f SHA1: 4306306649500802714a1bdb535dd5e555fe3fc9 MD5sum: efb3443e63830ab4f9a574d6014b43df 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-nibabel Source: nibabel Version: 2.0.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63313 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.0.2-1~nd15.04+1_all.deb Size: 1963356 SHA256: 4db8140f1e96db650aca1f459a9b75e309d54440a1c6edda6a289c5930effa15 SHA1: ef681f024a0b4d0892f0e0c94c0afc5c6dd56706 MD5sum: b4aa337c09070e1dafd6163a8cce194b 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 Package: python-nibabel-doc Source: nibabel Version: 2.0.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5572 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_2.0.2-1~nd15.04+1_all.deb Size: 2684448 SHA256: c1f733db940f0524de666e6c36cc5915eb38c7093b2a276961545861772be165 SHA1: 51e7054d510bad436081553596641960a81c0bb9 MD5sum: 3c95b6f3fd45c64c4dc2c57dcad58a53 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-nilearn Source: nilearn Version: 0.1.4+git3-g60d2a1b~dfsg.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1861 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.6), python-nibabel (>= 1.1.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-scipy (>= 0.9), python-sklearn (>= 0.12.1) Recommends: python-matplotlib Provides: python2.7-nilearn Homepage: https://nilearn.github.io Priority: extra Section: python Filename: pool/main/n/nilearn/python-nilearn_0.1.4+git3-g60d2a1b~dfsg.1-1~nd15.04+1_all.deb Size: 635418 SHA256: fe2c53c9e8d70942a8547f9b7d0648b1d4b801ba07cb239e4da4c92597625377 SHA1: 70dc1bdcb98a1c269e950cf10f92401ff7374562 MD5sum: 68f76c0ca78b5090471ad7392303c759 Description: fast and easy statistical learning on neuroimaging data This Python module leverages the scikit-learn toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. Python-Version: 2.7 Package: python-nipy Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2953 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 725092 SHA256: 160c214858539837cfbdc74fa8865aa863f2c28f6cfa337ac0219ca90323c8f3 SHA1: c8e7ad67f471fdf7f4408164775cd59cfb2f051b MD5sum: 63f71570305f645de43550c5b4c7e455 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10533 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 3212362 SHA256: 7671102c3b5a569976d2dbbd6169ce0c7357e6b7acd462e630d8f9eff3cdec47 SHA1: db431521c7138a32b72fea4e58ab210e55870180 MD5sum: cf3178ecda72225350d12fefb716ccc8 Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2714 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 569542 SHA256: 446b01b2695cba338c6299c555df993a20478aa8c9f5a9e89def74835955de0a SHA1: 6ebc9df58c46ec0651a0c0fcdcae95db1d1e73f0 MD5sum: 299696b0f0b43699ab1fea3b2530015c Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3133 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (>= 2.7), python-dbg (<< 2.8), python-nipy-lib (= 0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.3.0+git262-gbb838d7-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 441194 SHA256: b89a3fd286e7419bfcebfb7e0c590b2ce38cea793c27e7df24ca5a38b8bbfc1d SHA1: 1bb41e871aacfdcfb9d6ac82867a86b39c3682d2 MD5sum: 3a6716a85b808746806c690e6a80494e Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipype Source: nipype Version: 0.11.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7986 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-scipy, python-simplejson, python-traits (>= 4.0) | python-traits4, python-nibabel (>= 1.0.0~), python-networkx (>= 1.3), python-cfflib Recommends: ipython, python-nose, graphviz, python-xvfbwrapper, mayavi2 Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.11.0-1~nd15.04+1_all.deb Size: 1430640 SHA256: dca236dea7e2aa6e791b65b4f81305181e946b3793310e62d210d9c21d245d25 SHA1: 26b85d07cb88b558ea7222df4b99834db458d361 MD5sum: caeeaade8e3b6ca8c2a0dc57f0e2607f Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.11.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23034 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.11.0-1~nd15.04+1_all.deb Size: 9028004 SHA256: 777cbee43b259aa9cb1c60fe8f0ce030e7d25090e9984a233c2305cf31729b96 SHA1: 64913047566ddcb2337476ac2791f38345631205 MD5sum: e86b51c5fcc57a83d4f1d0a612e72fa2 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 446 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (>= 2.7.5-5~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python-numexpr_2.4.3-1~nd15.04+1_i386.deb Size: 122922 SHA256: f2637594f85571ed0d55fbda9f9d3d39efd14735c8c8c8cd00038edaa4985896 SHA1: 6b137d5e3455beeee86a6ad07f01f658758269fe MD5sum: 6e2f8a601c63c4c1d300454f586ecbd0 Description: Fast numerical array expression evaluator for Python and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This is the Python 2 version of the package. Package: python-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numexpr (= 2.4.3-1~nd15.04+1), python-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python-numexpr-dbg_2.4.3-1~nd15.04+1_i386.deb Size: 93522 SHA256: f5f4d47ce0c9c8495ec5b7fbc26169b7dab2454cb259fdd6660595c1f2e4cc8d SHA1: cd10048aa8a0caa8d405de5d3265947c03fa3ec2 MD5sum: 269294875cd32e3794d71f3b32a40b19 Description: Fast numerical array expression evaluator for Python and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 2 debug interpreter. Package: python-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1121 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-jdcal Recommends: python-pytest, python-pil, python-imaging, python-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0~b2-1~nd15.04+1_all.deb Size: 192318 SHA256: 5da04ffa0d29174014bb7123e71cfc407ed5ccfe0a7fa14c833e6e0c34bc283e SHA1: fb8e16db00086311e9b98355c5e47390d004a0ac MD5sum: a4e546abf5c3e283fc6734b52ccc35c5 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.17.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20021 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.17.1-1~nd15.04+1), python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.17.1-1~nd15.04+1_all.deb Size: 2403890 SHA256: 3666a940ad43a80c803d4c310f69bbfc1287b40e6a85a88dda823256304514aa SHA1: 18e3068eb92088ecee0a2644b0c957bc5df87ded MD5sum: d1c9bbb7833f87e8c9eb4389a962b357 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 . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.17.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 50104 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.17.1-1~nd15.04+1_all.deb Size: 10899320 SHA256: 7754346654d0c588dd25f3334d36a1e1f83962730598194b0049cd6865f3dba8 SHA1: ea93ae64564b0a17874e8429936dfb34c77a438d MD5sum: c37b590462e0713d5961f5a85e00298e Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.17.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6760 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.17.1-1~nd15.04+1_i386.deb Size: 1600238 SHA256: 32835c62516cf5f214482cc4f7fdb204e7f2c78006828109afc37ff046fed216 SHA1: b4075e05dbf2b61289d14ff32092cc8e5d322a89 MD5sum: 427fe125cceb2d330b8a5040d0b40b31 Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.4.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 795 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-six, python-numpy Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.4.1-1~nd15.04+1_all.deb Size: 171908 SHA256: 1cda9c9e5ce9adca51ac94b068289918bf441f5f4608dff813a4d5497ef8b723 SHA1: 30178c6e1aab16e64976df63c49c73e4d1b601c5 MD5sum: ee285a9ffbf103a1277fd75c210968d5 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.4.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1365 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.4.1-1~nd15.04+1_all.deb Size: 359064 SHA256: 9f8c7b3beb2c948c5510b6dedb186be30f8e97a7c1aded5fd4f8c6e92ba78213 SHA1: 26891c46e2788a9c62496054eb8338801fa920d1 MD5sum: 9e8b8e4fe78be8367ba515ad99983b4b Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-1+nd0~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 716 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0) Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-1+nd0~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 81970 SHA256: fbe3ab4eeebf2473f3e02e4cba721c67a6bdda5eaa26e5b47edb89804eede189 SHA1: f9d6c5adc7aef904c0da62f1027e4f24864a650d MD5sum: d0325feda6310adeed396c83a80bc49a Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Python-Version: 2.7 Package: python-py Version: 1.4.30-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 269 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pkg-resources Suggests: subversion, python-pytest, python-pytest-xdist Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python-py_1.4.30-1~nd15.04+1_all.deb Size: 66772 SHA256: 35f32e6f04896c734cf36cf563efa5d114fe8d958c9fa233a12b3b065234079c SHA1: 7de1445007ac1441d3b0596184d6ea425e899e57 MD5sum: f910e581ad941b0518e9553e7bb8d039 Description: Advanced Python development support library (Python 2) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 2 modules. Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1370 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 275444 SHA256: ece3839f96bdcee87c5f5c4cab8b12568e5751e3d43fd4cb041429b6ea6e0258 SHA1: c5b7e5490a56460dcca0e1d469db0f26939708bb MD5sum: c650e3164d3c8b8f6aa98fd9c8d06cd0 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 813 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 819470 SHA256: 4141b03991c1ae1733f1455890317059d1aa0b87522f81432f83775b99616c27 SHA1: 15bccebc6144753728e68c52ebb178bd2df0a480 MD5sum: 369149b435a66cd12d0d26065d4a0c36 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pymc Source: pymc Version: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2630 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.11), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, 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_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 526196 SHA256: c5398ee25757c1d3ddfb1def1a562d7662154075b4e52b2d6e91329d95d3331b SHA1: ccb2529b23bbd7f0bc01ecc87567f3b5644a7f75 MD5sum: 1cc01e5f1df2bc1c4d333de7a165a846 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: 2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1860 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_2.3.4+ds-1~nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 839998 SHA256: 212a988a1ef94aff793ad65bdc635fac3dfc440aecf7efdd5f38cbb390acdf34 SHA1: 2e7990989ae789fa2f86732f0f9fd295990de72d MD5sum: 5ac30fa505fb269d8838ce6a8c51d154 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-pynn Source: pynn Version: 0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 763 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0) Recommends: python-jinja2, python-cheetah Suggests: python-neuron, python-brian, python-csa Homepage: http://neuralensemble.org/trac/PyNN Priority: extra Section: python Filename: pool/main/p/pynn/python-pynn_0.7.5-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 123226 SHA256: d409c53ce5df4066f077a76a10d198361c04acd5dd5dbb4ecff4e57887830fd0 SHA1: b4d3fcbacf3b4866b6b93b5351e74beb3e9f1c2b MD5sum: 6f1abf7b60095f3ea2d0b6252095dded Description: simulator-independent specification of neuronal network models PyNN allows for coding a model once and run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). PyNN translates standard cell-model names and parameter names into simulator-specific names. Package: python-pypsignifit Source: psignifit3 Version: 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1545 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), python (<< 2.8), python (>= 2.7), python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy Homepage: http://psignifit.sourceforge.net Priority: extra Section: python Filename: pool/main/p/psignifit3/python-pypsignifit_3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 335260 SHA256: cfe9270108505adb5ee003b95de0da2fa32a765cac13d851091a2f42073bf410 SHA1: 90f770319bb66c76093fcb2d14faade15dfda9c7 MD5sum: 03c1d222338339b1c66c9cc843f96851 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-pytest Source: pytest Version: 2.7.2-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python-pkg-resources, python-py (>= 1.4.29), python, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-mock (>= 1.0.1) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python-pytest_2.7.2-2~nd15.04+1_all.deb Size: 102416 SHA256: 23f6d7792f555272a65266461601998d8e9281415111f8fdd75aaf92c9da67b9 SHA1: ad1262d1fa416f15245ed386823fe6c14b8b8bef MD5sum: 45719b33df858703d60f41b024993501 Description: Simple, powerful testing in Python This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. Package: python-pytest-doc Source: pytest Version: 2.7.2-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2878 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-pytest | python3-pytest Homepage: http://pytest.org/ Priority: optional Section: doc Filename: pool/main/p/pytest/python-pytest-doc_2.7.2-2~nd15.04+1_all.deb Size: 401812 SHA256: b0fcc8b66c86bb5789a9dfac2c443269785a487c69e47e19b7dc5faa0b2326cf SHA1: c4bfef534ce999e00302bf5e2b09a2348690927a MD5sum: 1cd5b95e5bc83e57f57f32840afac210 Description: Simple, powerful testing in Python - Documentation This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package contains the documentation for pytest. Package: python-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python-pytest, python-werkzeug (>= 0.10), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python-pytest-localserver_0.3.4-2~nd15.04+1_all.deb Size: 19310 SHA256: b4839faa96df335abff71a17762604afe7d71f2edb6f6a8ab86b94baa549da3c SHA1: 7c11dc58047e5f367b59d76c00610d94f2e06362 MD5sum: 538400b3e80490327fe8cea90e40709b Description: py.test plugin to test server connections locally (Python 2) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 2. Package: python-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python-pytest, python-tornado, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python-pytest-tornado_0.4.4-1~nd15.04+1_all.deb Size: 5754 SHA256: 822f8211e91ba25e945a05a904f9f827bfe9a7285c3ba2af3e80f556e130a514 SHA1: e3fd32da52114cbd92f05fcd5636f25247b4b179 MD5sum: d482112963438d293bf9f18c27bf77ba Description: py.test plugin to test Tornado applications pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 2 code. Package: python-scikits-learn Source: scikit-learn Version: 0.17.0-3~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 81 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_0.17.0-3~nd15.04+1_all.deb Size: 55554 SHA256: a01005bf1ed784f8e14b62f2cc21beb4e2d11beb6272ece1ca9fec366a902f06 SHA1: 24d5fde8bb223080809b99396a1f8deb3a008505 MD5sum: 36fc26c7587cf4a74b665354cc456b78 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-scrapy Version: 1.0.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 808 Depends: neurodebian-popularity-contest, python-boto, python-cssselect, python-libxml2, python-queuelib, python-twisted-conch, python-twisted-core, python-twisted-mail, python-twisted-web, python-w3lib (>= 1.8), python (>= 2.7), python (<< 2.8) Recommends: ipython, python-django, python-guppy, python-imaging, python-lxml, python-mysqldb, python-pygments Suggests: python-openssl Provides: python2.7-scrapy Homepage: http://scrapy.org/ Priority: optional Section: python Filename: pool/main/p/python-scrapy/python-scrapy_1.0.0-1~nd15.04+1_all.deb Size: 175052 SHA256: 0614c784915bd351babc6467c0daceacf2a1feda70b595c491707fbcffe5b307 SHA1: e15b3e6fb22a2a333e091f84db6890ba9c1091a5 MD5sum: 832715218483c9a595334f1727a26041 Description: Python web scraping and crawling framework Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy script and modules. Package: python-scrapy-doc Source: python-scrapy Version: 1.0.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7013 Depends: neurodebian-popularity-contest Recommends: libjs-jquery, libjs-underscore Homepage: http://scrapy.org/ Priority: optional Section: doc Filename: pool/main/p/python-scrapy/python-scrapy-doc_1.0.0-1~nd15.04+1_all.deb Size: 1520578 SHA256: d96313d26ed726ede0bcef27ad840d10568b6b98745ba14480438b43e75e30eb SHA1: c5725c15631ec7997efcc7864ce54410c0969af8 MD5sum: 0d7e95e51682ca39999a2f611f8afb66 Description: Python web scraping and crawling framework documentation Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. . This package provides the python-scrapy documentation in HTML format. Package: python-seaborn Source: seaborn Version: 0.6.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 676 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-pandas, python-matplotlib Recommends: python-statsmodels, python-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python-seaborn_0.6.0-1~nd15.04+1_all.deb Size: 117816 SHA256: 9b36c9a29beef1e724318efa364acfc897e0baa45db1ce198b9e46d5ab56aaa8 SHA1: 7e099883223770641c2ee02b25d8f433af2430c6 MD5sum: e598e548d3d3bc0850742135f8b435e3 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 2 version of the package. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd15.04+1_all.deb Size: 11116 SHA256: fc7e55a9aeb35b9915d17997bbaac2285366d8988e79a4563a7e0d1278d4ecbf SHA1: bf898ae83cc9862f0601efc88bdf43f2c2ad8f78 MD5sum: d809a46ec4bdf9c7a510ae028a400b77 Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. Package: python-six-whl Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six-whl_1.9.0-3~bpo8+1~nd15.04+1_all.deb Size: 13320 SHA256: 1b7f71fec73b08228f4570ea39513d466b8715046a0cd9d4e61c6c701a44d120 SHA1: 019d89a8d8d80a06846cd57bff82236d18882701 MD5sum: 4d3d73be56dba394305fb07066765c21 Description: Python 2 and 3 compatibility library (universal wheel) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six as a universal wheel. Package: python-sklearn Source: scikit-learn Version: 0.17.0-3~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5274 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.0-3~nd15.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.17.0-3~nd15.04+1_all.deb Size: 1223328 SHA256: 6f635baa24a12a00c3aceb8f3eb4c02c0af424efa5d4f6158fae8f7dd57b1301 SHA1: d51cebb72c0d12c24853490dc90335bdab6a9d70 MD5sum: 933bcc558e22bf949955a56cf97c1b39 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.17.0-3~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23762 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore 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_0.17.0-3~nd15.04+1_all.deb Size: 4069236 SHA256: ac686c2b11aff6922ec82f49cd3570d51f1bd423edd6423b56e3351c5738f694 SHA1: 8cb1943242c7c990b10680f4a59d013784443bb0 MD5sum: 53458e0543fd1a12d43bc87284aad136 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: 0.17.0-3~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 5275 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) 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_0.17.0-3~nd15.04+1_i386.deb Size: 1133502 SHA256: 5c03c9de6efe70ab65f808841db5feeca8b929884c64149ce9bb35cdb0438ba6 SHA1: 4bbe8df74d1a720318f34e2b7f38252f4e2ce5a3 MD5sum: 42b5e60fe62702202cadfa9600a9b496 Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-smmap Version: 0.9.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 68 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-1~nd15.04+1_all.deb Size: 20086 SHA256: 8056d44a58027c554907b9ed773444af0c95dc73608bb458100b9cb65d265856 SHA1: b9b63e32255c98f631f72b3f8f394d9a68209dc4 MD5sum: 3eccd6dd18f185194c6ef539dc09a0a5 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. Package: python-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python-sphinx-rtd-theme_0.1.8-1~nd15.04+1_all.deb Size: 117238 SHA256: 241167342a48b4a3e2abf8cc4a03c286b9532965eb218d1e86753035295e27f6 SHA1: 6a6e4de3b3ccd3c7b1b5dcd9c7e6b50a7140f180 MD5sum: 1c029e3a01effa7c5994ec68488b1ecc Description: sphinx theme from readthedocs.org (Python 2) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 2 version of the package. Package: python-stfio Source: stimfit Version: 0.14.11-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 946 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.8.0), python-numpy-abi9, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.4), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-8, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.9), libbiosig-dev, libsuitesparse-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.14.11-1~nd15.04+1_i386.deb Size: 312682 SHA256: 703d6016918e6980957bd7e30927c36dafb1c19f681dc0d4fd50e8e044f1534c SHA1: d1442a857282d900101a2fe41a93ee29ce0670c8 MD5sum: 7f4722d078e2a8006152956f0aa07107 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-tables Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2711 Depends: neurodebian-popularity-contest, python-numpy, python, python-numexpr, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-tables-lib (>= 3.2.1-1~nd15.04+1), python-tables-lib (<< 3.2.1-1~nd15.04+1.1~), python-tables-data (= 3.2.1-1~nd15.04+1) Suggests: python-tables-doc, python-netcdf, vitables Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables_3.2.1-1~nd15.04+1_all.deb Size: 345168 SHA256: 23e0c4c81d83c6dbcda67ce645ffdd9e1476619aaf6429f19939ea9259778604 SHA1: d814f96ec983770f900eaef05a65acd3ddeaf5db MD5sum: ff36dc7b5212d2e309f27edceaba3011 Description: hierarchical database for Python based on HDF5 PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This is the Python 2 version of the package. Package: python-tables-data Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 922 Depends: neurodebian-popularity-contest Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables-data_3.2.1-1~nd15.04+1_all.deb Size: 51418 SHA256: 6f6947dc5cb0036aa0a19a8629f4915470c7848e01777e0869909cbe01ea68f8 SHA1: 35d18073d42d66cf67ff2b33b16dbf4f21e5db0c MD5sum: 503e9bb7fbb3fd58bb09d479b11281af Description: hierarchical database for Python based on HDF5 - test data PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . This package includes daya fils used for unit testing. Package: python-tables-dbg Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1802 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7~), libbz2-1.0, libc6 (>= 2.4), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1, zlib1g (>= 1:1.1.4), python-tables (= 3.2.1-1~nd15.04+1), python-tables-lib (= 3.2.1-1~nd15.04+1), python-numpy-dbg, python-numexpr-dbg Suggests: python-tables-doc, python-netcdf Homepage: http://www.pytables.org Priority: extra Section: debug Filename: pool/main/p/pytables/python-tables-dbg_3.2.1-1~nd15.04+1_i386.deb Size: 492248 SHA256: 7b0f20e5d685481e5ff0b16e19d002517c72f5551db9071cf5e65860daaa12f2 SHA1: 935404af2b47e793ab5efe86a713077ddec58130 MD5sum: d2dd0917ba7f8b2666754b71847d5711 Description: hierarchical database for Python based on HDF5 (debug extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 2 debug interpreter. Package: python-tables-doc Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8786 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), libjs-jquery-cookie Suggests: xpdf | pdf-viewer, www-browser Homepage: http://www.pytables.org Priority: optional Section: doc Filename: pool/main/p/pytables/python-tables-doc_3.2.1-1~nd15.04+1_all.deb Size: 4247860 SHA256: 29ff1735304d19050bb129ee2d92f35475137e7fce21a4b91906bad4670e2bc8 SHA1: 6bd5d23a1547c3f4844ff0dd3d310d24eec6fcd9 MD5sum: 221e9c82df65b409582dae82fe8e30b1 Description: hierarchical database for Python based on HDF5 - documentation PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . This package includes the manual in PDF and HTML formats. Package: python-tables-lib Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1466 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.8.0), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), libbz2-1.0, libc6 (>= 2.4), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1, zlib1g (>= 1:1.1.4) Recommends: python-tables (= 3.2.1-1~nd15.04+1) Breaks: python-tables (<< 3.0.0-3) Replaces: python-tables (<< 3.0.0-3) Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python-tables-lib_3.2.1-1~nd15.04+1_i386.deb Size: 391986 SHA256: e8068e518d0902d9184fedd77213e68c34c8bb25bd9ab0fcfab982dffbe78825 SHA1: dfd1c6347e74d4098b99a8267a4e24b2401afdd5 MD5sum: 71156338ae3164b5f0c6bee691cfcc37 Description: hierarchical database for Python based on HDF5 (extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 2 interpreter. Package: python-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 482 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.8, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd15.04+1_i386.deb Size: 91310 SHA256: 6c54b37b75229d3d1fe885b7a4fc0f7d6d379bb869962ab776acc163a1296a1d SHA1: a42c4941ec1517398346d1b2dd8520cd4b575f9f MD5sum: 165d20762d9f2b2ea4d8b1bf1465cb98 Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python-w3lib Version: 1.11.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python-six (>= 1.6.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python-w3lib_1.11.0-1~nd15.04+1_all.deb Size: 14200 SHA256: 466ff41a2f0cef0dd0f474e9793f8a5c87372a06350e24de8b90b0ddf8fbc036 SHA1: 42eafdde8f0f7b6c76188862c28ad03720592be4 MD5sum: 9ec87e9b559013ff08911b3060225c9b Description: Collection of web-related functions for Python (Python 2) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 2 version of the package. Package: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-jquery Recommends: python-simplejson | python (>= 2.6), python-openssl, python-pyinotify Suggests: ipython, python-genshi, python-pkg-resources, python-lxml, python-greenlet, python-redis, python-pylibmc | python-memcache, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python-werkzeug_0.10.4+dfsg1-1~nd15.04+1_all.deb Size: 163416 SHA256: 64183383fd2a66d1f2b49a53444d2c55813b04f12cf30a92a48efadb08ef6a58 SHA1: b94fcb6411c480646e9725797d0a6e3abf7d7708 MD5sum: 74e208601582d9138f57efa85a142e97 Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python-werkzeug-doc Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2559 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Conflicts: python-werkzeug (<< 0.9.3+dfsg-2) Replaces: python-werkzeug (<< 0.9.3+dfsg-2) Homepage: http://werkzeug.pocoo.org/ Priority: extra Section: doc Filename: pool/main/p/python-werkzeug/python-werkzeug-doc_0.10.4+dfsg1-1~nd15.04+1_all.deb Size: 880206 SHA256: a42f0a23dfba7bfbb552f59b52ccd9b6476b3ec4fe82e45ffc7a35a5de0bcfd0 SHA1: 40f8b6e41e39915463a63b2cd6b439878719d24d MD5sum: 9882068e7050e3da0ff440a83e0d3218 Description: documentation for the werkzeug Python library Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: python3-citeproc Source: citeproc-py Version: 0.3.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 731 Depends: neurodebian-popularity-contest, python3, python3-lxml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/brechtm/citeproc-py Priority: optional Section: python Filename: pool/main/c/citeproc-py/python3-citeproc_0.3.0-1~nd15.04+1_all.deb Size: 82014 SHA256: 58b7e715fe22c7ca7582fef12c2edd4b96f9de5a130d918c457bcd9bb5a3edb8 SHA1: 409f20d9dbdc0a9377728cc98a61e937e57f0b92 MD5sum: fa1423d015f429068fee440bcfcc53f8 Description: Citation Style Language (CSL) processor for Python3 Citeproc-py is a library that produces formatted bibliographies and citations from bibliographic databases following formatting instructions provided by XML style files written in the Citation Style Language (CSL). . Currently, BibTeX and JSON are supported as input database formats, and plain text, reStructuredText and HTML as output format. . This package contains the Python 3 modules and the CLI tool csl_unsorted. Package: python3-joblib Source: joblib Version: 0.9.3-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 339 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-nose, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.9.3-1~nd15.04+1_all.deb Size: 74986 SHA256: b6c2932ca378bb9094eab293e2a1af106bdf12f94de83064b05e4ddb5f46ecf9 SHA1: 3dc0fd6b945f328d58b98379c06d42a8c2aa54ea MD5sum: 02630b57a3a58f86f88e3251e84ae7c0 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. . This package contains the Python 3 version. Package: python3-lda Source: lda Version: 1.0.2-9~nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1242 Depends: neurodebian-popularity-contest, python3 (<< 3.5), python3 (>= 3.4~), python3-numpy, python3-pbr, libc6 (>= 2.4) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd14.10+1+nd15.04+1_i386.deb Size: 235844 SHA256: 0ca5c5a3924f7573d88a245a8a3fc2cef495a244a97e287fcc7fe5ff7d2b7f06 SHA1: 1da7c5fe52a9d8fd27c1fadb4484554e3ee1d09b MD5sum: 602a1de1e954dc5aef7deb5c6e62a583 Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-nibabel Source: nibabel Version: 2.0.2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 63272 Depends: neurodebian-popularity-contest, python3-numpy, python3-scipy Suggests: python-nibabel-doc, python3-dicom, python3-fuse Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.0.2-1~nd15.04+1_all.deb Size: 1953668 SHA256: e1890266d03a9e59fbf7d79d681b090ca34bfe9151fe3981a7a3dc9129bb9ac2 SHA1: b0326ff60b8ce4e1169d81636d8b943d4f95ec8b MD5sum: 6ca88242008c353fb443bd536555eea4 Description: Python3 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. Package: python3-numexpr Source: numexpr Version: 2.4.3-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 432 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1) Homepage: http://code.google.com/p/numexpr/ Priority: optional Section: python Filename: pool/main/n/numexpr/python3-numexpr_2.4.3-1~nd15.04+1_i386.deb Size: 117154 SHA256: 59bb7de129309483c386d6e8566f363d784b83c2ab8f151388fe647da78fa508 SHA1: 3ec633d48f78cbb641869fd74e029ebda7532a4c MD5sum: b39d72acffe59d27ffde57c6631d7401 Description: Fast numerical array expression evaluator for Python 3 and NumPy Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains numexpr for Python 3. Package: python3-numexpr-dbg Source: numexpr Version: 2.4.3-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 328 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.5), python3-dbg (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numexpr (= 2.4.3-1~nd15.04+1), python3-numpy-dbg Homepage: http://code.google.com/p/numexpr/ Priority: extra Section: debug Filename: pool/main/n/numexpr/python3-numexpr-dbg_2.4.3-1~nd15.04+1_i386.deb Size: 93700 SHA256: 0ecef26f2ab753a66917cfaa9c9386ca33bc8e39d52e719cb6997c87537a9b28 SHA1: 66d6d4f7c24e931bc0c945a3709ab2dc8c69f89e MD5sum: b656b38cf7e902d69f7eb8cd2533a972 Description: Fast numerical array expression evaluator for Python 3 and NumPy (debug ext) Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-openpyxl Source: openpyxl Version: 2.3.0~b2-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1115 Depends: neurodebian-popularity-contest, python3-jdcal, python3:any (>= 3.3.2-2~) Recommends: python3-pytest, python3-pil, python3-lxml Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0~b2-1~nd15.04+1_all.deb Size: 190944 SHA256: 33ac18ccdd62d354aa313b233b0b108050090d091f68eaa4a0cc0dd6e3838a79 SHA1: 2ba1be50ba5bd1de2937e78f9530c9fe5e503444 MD5sum: cf8252814f053d9941fe888ce3236d16 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.17.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20000 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.17.1-1~nd15.04+1) Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-six, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.17.1-1~nd15.04+1_all.deb Size: 2400826 SHA256: c79dbf4cb02be3a767fe918da693bbd7e7f89bffa795b95aa54981694745c4ff SHA1: f10ad946a1cfb0a8959891b73789bcb6c22167ac MD5sum: cc152473b71fbbba1c23204e80c6d24e Description: data structures for "relational" or "labeled" data - Python 3 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 . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.17.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6628 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.17.1-1~nd15.04+1_i386.deb Size: 1569448 SHA256: e802cea25b426508e7aab3e63ca7fd3d06fb9d64e07d6b11a45e448a60c6a185 SHA1: 617992afee288d0dc900c3131618badede2e25ce MD5sum: 8fd083f092af223f342d1b22aeb4b182 Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.4.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 793 Depends: neurodebian-popularity-contest, python3-numpy, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.4.1-1~nd15.04+1_all.deb Size: 170618 SHA256: f88d672501715f85702d1211e410c402714591cfb70550ba1afea7722a080b23 SHA1: e2cf13d3458626f1368afe82ae936beaa3714aa4 MD5sum: cc20c9ff6aeb07e835272b44d688c5e2 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-py Source: python-py Version: 1.4.30-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-pkg-resources Suggests: subversion, python3-pytest Homepage: https://bitbucket.org/pytest-dev/py Priority: optional Section: python Filename: pool/main/p/python-py/python3-py_1.4.30-1~nd15.04+1_all.deb Size: 66838 SHA256: 4e214febd0caf31121ded7dae39868ce386ef8ba3ddb08a820a0b84a54b48dfc SHA1: b109dcac1c0b64d42f409ba35142c96a0f65e3c6 MD5sum: 2f45a639062f4fa28996390cad086a5b Description: Advanced Python development support library (Python 3) The Codespeak py lib aims at supporting a decent Python development process addressing deployment, versioning and documentation perspectives. It includes: . * py.path: path abstractions over local and Subversion files * py.code: dynamic code compile and traceback printing support . This package provides the Python 3 modules. Package: python3-pytest Source: pytest Version: 2.7.2-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 424 Depends: neurodebian-popularity-contest, python3-pkg-resources, python3-py (>= 1.4.29), python3, python3:any (>= 3.3.2-2~) Homepage: http://pytest.org/ Priority: optional Section: python Filename: pool/main/p/pytest/python3-pytest_2.7.2-2~nd15.04+1_all.deb Size: 102554 SHA256: ef5be096433403b409d7337c2738bdf618c693ecdc219137d703db0bf0e7c782 SHA1: 5795f4eb32561bf8736c2d78c5ae4a6342b00fc3 MD5sum: 4e4696b222b9a886ff3d6319cc6024ed Description: Simple, powerful testing in Python3 This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword. . This package provides the Python 3 module and the py3.test script. Package: python3-pytest-localserver Source: pytest-localserver Version: 0.3.4-2~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 82 Depends: neurodebian-popularity-contest, python3-pytest, python3-werkzeug (>= 0.10), python3:any (>= 3.3.2-2~) Homepage: https://bitbucket.org/pytest-dev/pytest-localserver/ Priority: optional Section: python Filename: pool/main/p/pytest-localserver/python3-pytest-localserver_0.3.4-2~nd15.04+1_all.deb Size: 19384 SHA256: d506e0097b754cfc2b5209ec864ec8dc65e4917ee5b3bf868a24eaca2939b363 SHA1: 6f4eb8678d23365142097cdb20bac10286ece3f4 MD5sum: 72bbb569c0e4facb25a9867cc74ea9f4 Description: py.test plugin to test server connections locally (Python 3) pytest-localserver is a plugin for the Pytest testing framework which enables to test server connections locally. . This package contains the modules for Python 3. Package: python3-pytest-tornado Source: pytest-tornado Version: 0.4.4-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python3-pytest, python3-tornado, python3:any (>= 3.3.2-2~) Homepage: https://github.com/eugeniy/pytest-tornado Priority: optional Section: python Filename: pool/main/p/pytest-tornado/python3-pytest-tornado_0.4.4-1~nd15.04+1_all.deb Size: 5830 SHA256: 24a9fb9b036f4557135e30cd451889d1c8ddc4416812d9deadef6a921cdeded4 SHA1: 80efabadf804d1c61de37879f5c2dade1e8ec453 MD5sum: 23e6cc34e05a10fb41a04ea016c8f0db Description: py.test plugin to test Tornado applications (Python 3) pytest-tornado is a plugin for the Pytest testing framework which provides fixtures and markers to simplify testing of Tornado applications (Python web framework and ansynchronous networking library). . This package contains the plugin for Python 3 code. Package: python3-seaborn Source: seaborn Version: 0.6.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 676 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-pandas, python3-matplotlib Recommends: python3-patsy Homepage: https://github.com/mwaskom/seaborn Priority: optional Section: python Filename: pool/main/s/seaborn/python3-seaborn_0.6.0-1~nd15.04+1_all.deb Size: 117852 SHA256: 96eeeb5abd95e910808fde1f3d5cd4cbe39dce8d7be2afc83850e430bf9cc0b2 SHA1: 7006d7ee583567cf4d6bd4a8b3b1a61fb35df3c6 MD5sum: cd28467849d3f7b026327d0f114762c7 Description: statistical visualization library Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. . Some of the features that seaborn offers are . - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations . This is the Python 3 version of the package. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd15.04+1_all.deb Size: 11200 SHA256: 2448500407de73e001990702acb803c5eda1b9225b1e5908b64acf50fe981823 SHA1: 3de9903634937b862d142cc83064f49575e2dfcc MD5sum: aed70178b10a218d513f2d1e9691836a Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-sklearn Source: scikit-learn Version: 0.17.0-3~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5274 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.0-3~nd15.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.17.0-3~nd15.04+1_all.deb Size: 1222592 SHA256: 15452554213fec95011c886425932f248ad8bfc95b7d27fb194de38e5c79ae9b SHA1: 4ff7df52bf6b9a2a75d18d2f37f4fe3a5898eed8 MD5sum: 3e9a893f7e018ebcdc6f464a5a661816 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) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.17.0-3~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4812 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.17.0-3~nd15.04+1_i386.deb Size: 1041720 SHA256: 2f4ca9d14ac02898a3759ceefa06516760c7a56c8208a78255ae807113af87dd SHA1: b81275c620f23c2582eccee3d5b80cb03548d7a7 MD5sum: cbf5a839939acf33b5c164ac8036a391 Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-sphinx-rtd-theme Source: sphinx-rtd-theme Version: 0.1.8-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: neurodebian-popularity-contest, fonts-font-awesome, fonts-lato, libjs-modernizr, python3:any (>= 3.3.2-2~) Recommends: python3-sphinx Homepage: https://github.com/snide/sphinx_rtd_theme Priority: optional Section: python Filename: pool/main/s/sphinx-rtd-theme/python3-sphinx-rtd-theme_0.1.8-1~nd15.04+1_all.deb Size: 117294 SHA256: 365d13896e9229c8d9ffa6d5701d126d657eeaf951022fe48ab07c55bed2e56b SHA1: b52e873a588f29f913b6925673776c9c3bfce477 MD5sum: 2190713250e854576a47d53ee4aa8675 Description: sphinx theme from readthedocs.org (Python 3) This mobile-friendly sphinx theme was initially created for readthedocs.org, but can be incorporated in any project. . Among other things, it features a left panel with a browseable table of contents, and a search bar. . This is the Python 3 version of the package. Package: python3-tables Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2694 Depends: neurodebian-popularity-contest, python3-numpy, python3-numexpr, python3:any (>= 3.3.2-2~), python3-tables-lib (>= 3.2.1-1~nd15.04+1), python3-tables-lib (<< 3.2.1-1~nd15.04+1.1~), python-tables-data (= 3.2.1-1~nd15.04+1) Suggests: python-tables-doc, python-netcdf, vitables Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python3-tables_3.2.1-1~nd15.04+1_all.deb Size: 334886 SHA256: b72060567e46b8ba586d32055e7f9c2bfc8a345e448db6015c620565750763f5 SHA1: 90183f0ae5df3773cdc043c508cb3ae1215346e8 MD5sum: e678b5a92757a187e4906ac8e81c0d8b Description: hierarchical database for Python3 based on HDF5 PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This is the Python 3 version of the package. Package: python3-tables-dbg Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1759 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3-dbg (<< 3.5), python3-dbg (>= 3.4~), libbz2-1.0, libc6 (>= 2.4), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1, zlib1g (>= 1:1.1.4), python3-tables (= 3.2.1-1~nd15.04+1), python3-tables-lib (= 3.2.1-1~nd15.04+1), python3-numpy-dbg, python3-numexpr-dbg Suggests: python-tables-doc, python-netcdf Homepage: http://www.pytables.org Priority: extra Section: debug Filename: pool/main/p/pytables/python3-tables-dbg_3.2.1-1~nd15.04+1_i386.deb Size: 482718 SHA256: 248cd9ea78eb58990bedd86409e2f655c15220857860e07d97fe551e405eb16c SHA1: f5f8c5b6ec86f30a07676b923dcd1857b8647497 MD5sum: db9e49471a0b148658432e305031b79d Description: hierarchical database for Python 3 based on HDF5 (debug extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 3 debug interpreter. Package: python3-tables-lib Source: pytables Version: 3.2.1-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1419 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.8.0), python3-numpy-abi9, python3 (<< 3.5), python3 (>= 3.4~), libbz2-1.0, libc6 (>= 2.4), libhdf5-8, liblz4-1 (>= 0.0~r113), liblzo2-2, libsnappy1, zlib1g (>= 1:1.1.4) Recommends: python3-tables (= 3.2.1-1~nd15.04+1) Breaks: python3-tables (<< 3.0.0-3) Replaces: python3-tables (<< 3.0.0-3) Homepage: http://www.pytables.org Priority: optional Section: python Filename: pool/main/p/pytables/python3-tables-lib_3.2.1-1~nd15.04+1_i386.deb Size: 380096 SHA256: 44d97603f93a6eb399c92d56a13e5b28acb311069a7a67c1c419be5eaf57f7b3 SHA1: bbe4ab3e334a64e6375121d8ff4833f4e6919e7b MD5sum: 48e83b6311fbddb94b75a3320cbac328 Description: hierarchical database for Python3 based on HDF5 (extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 3 interpreter. Package: python3-w3lib Source: python-w3lib Version: 1.11.0-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: neurodebian-popularity-contest, python3-six (>= 1.6.1), python3:any (>= 3.3.2-2~) Homepage: http://pypi.python.org/pypi/w3lib Priority: optional Section: python Filename: pool/main/p/python-w3lib/python3-w3lib_1.11.0-1~nd15.04+1_all.deb Size: 14286 SHA256: 5234acf308d716e4e992ce1e32de3913eadd7ff7d814e8e7b919077233b1c8b8 SHA1: 53b9ed7790ff55cd7726d049c32c08e3a95e5f79 MD5sum: 8538c2b6a93fb76fb7a853db35cd533a Description: Collection of web-related functions for Python (Python 3) Python module with simple, reusable functions to work with URLs, HTML, forms, and HTTP, that aren’t found in the Python standard library. . This module is used to, for example: - remove comments, or tags from HTML snippets - extract base url from HTML snippets - translate entites on HTML strings - encoding mulitpart/form-data - convert raw HTTP headers to dicts and vice-versa - construct HTTP auth header - RFC-compliant url joining - sanitize urls (like browsers do) - extract arguments from urls . The code of w3lib was originally part of the Scrapy framework but was later stripped out of Scrapy, with the aim of make it more reusable and to provide a useful library of web functions without depending on Scrapy. . This is the Python 3 version of the package. Package: python3-werkzeug Source: python-werkzeug Version: 0.10.4+dfsg1-1~nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 727 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), libjs-jquery Recommends: python3-simplejson | python3, python3-openssl, python3-pyinotify Suggests: ipython3, python3-pkg-resources, python3-lxml, python-werkzeug-doc Homepage: http://werkzeug.pocoo.org/ Priority: optional Section: python Filename: pool/main/p/python-werkzeug/python3-werkzeug_0.10.4+dfsg1-1~nd15.04+1_all.deb Size: 163370 SHA256: 236d305d47a66dd096ee55dc15a342d198b1323c22fb99526c08aa742388d889 SHA1: c94963eccdeb3332ba008b76e068ce7d85f968ba MD5sum: a05c4cfadba72ce7e82a9e80b89cd1ce Description: collection of utilities for WSGI applications The Web Server Gateway Interface (WSGI) is a standard interface between web server software and web applications written in Python. . Werkzeug is a lightweight library for interfacing with WSGI. It features request and response objects, an interactive debugging system and a powerful URI dispatcher. Combine with your choice of third party libraries and middleware to easily create a custom application framework. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 18499 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 9749522 SHA256: bee3a8a8d0af681ba91432ac463ec34332831ecdadbfaa1e0c109a56f8a238b8 SHA1: 3c3872cd974ef2eb3c96fc7b06cffb46ada71913 MD5sum: d6409b2fa71161921cae88d7463c1a37 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72987 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 45490194 SHA256: 7cfaaff742fc76511c629cee8e2e378f48d3f2fc89a8cc08990ad1b42b5e3936 SHA1: 6e1accea5582cbb34454b3c4540caad106ca7fcb MD5sum: aee12a1a58cd615510e6a960405dfb3a Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9242 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 8935228 SHA256: 7fff13109743814047c5484270313ba9ccab6f45f94254af4c7868caa9b843e3 SHA1: 755c714e5b684c1436b121dfe5022f9d4bf804d4 MD5sum: 42740eef8ef7c2e6f319320784a3738a 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+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python, python-support (>= 0.90.0), python-numpy, python-matplotlib, python-scipy, python-nifti Recommends: python-dicom Homepage: https://github.com/bbfrederick/stabilitycalc Priority: extra Section: science Filename: pool/main/s/stabilitycalc/stabilitycalc_0.1-1~nd11.04+1+nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 22822 SHA256: 03f99830143fac4d44e7d19f3da19a63f78215aab4e427efe765acd31e6fe223 SHA1: 230b6f40d4e07188d5324e9698ebd9dda213a20b MD5sum: 676750a675b5dbe7a0937e0a88d2511c Description: evaluate fMRI scanner stability Command-line tools to calculate numerous fMRI scanner stability metrics, based on the FBIRN quality assurance test protocal. Any 4D volumetric timeseries image in NIfTI format is support input. Output is a rich HTML report. Python-Version: 2.7 Package: stimfit Version: 0.14.11-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2652 Depends: neurodebian-popularity-contest, libbiosig1, libblas3 | libblas.so.3, libc6 (>= 2.4), libcholmod2.1.2, libfftw3-double3, libgcc1 (>= 1:4.1.1), libhdf5-8, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 4.9), libwxbase3.0-0 (>= 3.0.2), libwxgtk3.0-0 (>= 3.0.2), python-numpy (>= 1:1.8.0), python-numpy-abi9, python2.7, python:any (>= 2.6.6-7~), libbiosig-dev, libsuitesparse-dev, python-wxgtk3.0 | python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.14.11-1~nd15.04+1_i386.deb Size: 758698 SHA256: b5ea85b8f56eff1ae25e69b9f82f507aae002406ab11bce2ff8ce570481fb3d8 SHA1: ed7b912908d350be320312b2f91e63eaa03ea06f MD5sum: e14cf89ca56a7b02a6d2993e37ec6ec3 Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.14.11-1~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 24209 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.14.11-1~nd15.04+1_i386.deb Size: 4455860 SHA256: cb1420f5dde4fbf42cd1d37de65bde9ebca85e0e3c37e92f7be8bbedac966ef2 SHA1: 23b946e8f9c304cc2dd37d48a919bdba98a7036a MD5sum: 5e5a4d05bd87264f0471d01d501e5fd1 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. This package contains the debug symbols for Stimfit. Package: testkraut Version: 0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 359 Depends: neurodebian-popularity-contest, python (>= 2.6), python-support (>= 0.90.0), python-numpy, libjs-underscore, libjs-jquery, python-argparse Recommends: strace, python-scipy, python-colorama, python-apt Homepage: https://github.com/neurodebian/testkraut Priority: extra Section: python Filename: pool/main/t/testkraut/testkraut_0.0.1-1~nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_all.deb Size: 86220 SHA256: 5b1e47fba04d313b1eca80cf698d2aa4b9cd5d24e0428450b2bc56a3ed809f62 SHA1: ea19ee270d5348f70033fabb34c77e3dbb164b25 MD5sum: 13eb82ea4aadd1d37019e0a52499d2ae Description: test and evaluate heterogeneous data processing pipelines This is a framework for software testing. That being said, testkraut tries to minimize the overlap with the scopes of unit testing, regression testing, and continuous integration testing. Instead, it aims to complement these kinds of testing, and is able to re-use them, or can be integrated with them. . In a nutshell testkraut helps to facilitate statistical analysis of test results. In particular, it focuses on two main scenarios: . * Comparing results of a single (test) implementation across different or changing computational environments (think: different operating systems, different hardware, or the same machine before an after a software upgrade). * Comparing results of different (test) implementations generating similar output from identical input (think: performance of various signal detection algorithms). . While such things can be done using other available tools as well, testkraut aims to provide a lightweight, yet comprehensive description of a test run. Such a description allows for decoupling test result generation and analysis – opening up the opportunity to “crowd-source” software testing efforts, and aggregate results beyond the scope of a single project, lab, company, or site. Python-Version: 2.7 Package: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 292 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 50170 SHA256: 42d639d27a0484b22e2bf2dd51fd3f658ff50acb3d86c306640124ea0624830f SHA1: b35f48be3de59d5a3427008fc18fae6d2aaa4958 MD5sum: 7b4d5d562d4f54e94fce2239840681a7 Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3445 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1), vrpn (= 07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1+nd14.10+1+nd15.04+1_i386.deb Size: 864626 SHA256: 1dbcd056cb4cabde7ef52be33b4063d488fde4c71f313c67c23cfde6f3c4f695 SHA1: 2a0aacce6423dc0113178b34b2102ae2d162fd65 MD5sum: d892fe2f2b674368b09efd853b569441 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. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd15.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 245 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), libvtk-dicom0.5, libvtk5.8 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd15.04+1_i386.deb Size: 73212 SHA256: 89e8dcf3e8d803f6ead2a7818f89a842218adfa874be6dc511774dff854fc3a4 SHA1: d9d1f8f2f6287b90e1f73ab2b63129a75d5f57f4 MD5sum: 8890efebf94e411ece287463b3c468fc Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools