Package: eyesthatblink Version: 1.0-12 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 6085 Depends: libatkmm-1.6-1v5 (>= 2.24.0), libboost-filesystem1.65.1, libboost-regex1.65.1, libboost-system1.65.1, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libglibmm-2.4-1v5 (>= 2.54.0), libgtkmm-2.4-1v5 (>= 1:2.24.0), libnotify4 (>= 0.7.0), libopencv-core3.2, libopencv-imgproc3.2, libopencv-objdetect3.2, libopencv-videoio3.2, libsigc++-2.0-0v5 (>= 2.2.0), libstdc++6 (>= 7), libxcb-randr0 (>= 1.1), libxcb-util1 (>= 0.4.0), libxcb1 Filename: ./amd64/eyesthatblink_1.0-12_amd64.deb Size: 657764 MD5sum: 45cfc8b8294d0529095c04d12ebdd05f SHA1: d5d48903a23b26e37d4f467f2094b290dc8b98de SHA256: 161acc1be223b9f13cc2227b4047fe0cf0eb2447b3c5bcc7f88bdeda7a71b2ad Section: science Priority: optional Homepage: http://eyesthatblink.com Description: Eyes That Blink Package: moose Source: xppaut Version: 8.0+10.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 2107 Depends: libc6 (>= 2.23), libx11-6 Filename: ./amd64/moose_8.0+10.1_amd64.deb Size: 745752 MD5sum: 9300efe34c808dd8fc8853715aedff95 SHA1: 5199e36c4fbe1a75aa835ff5efcf66bcc82adf89 SHA256: e3983bd428d30a057a065fd7fbcc8a5f01be1f2eb5de14aa0aa2c4f3cd566f2a Section: science Priority: optional Homepage: http://moose.ncbs.res.in Description: XPPAUT is a tool for solving * differential equations, * difference equations, * delay equations, * functional equations, * boundary value problems, and * stochastic equations. The code brings together a number of useful algorithms and is extremely portable. All the graphics and interface are written completely in Xlib which explains the somewhat idiosyncratic and primitive widgets interface. Package: nest Version: 2.16.0+4.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 24156 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.4), libgomp1 (>= 4.9), libgsl23, libgslcblas0, libltdl7 (>= 2.4.6), libpython3.6 (>= 3.6.4~rc1), libreadline7 (>= 6.0), libstdc++6 (>= 5.2), libtinfo5 (>= 6) Recommends: python3-matplotlib, python3-scipy Filename: ./amd64/nest_2.16.0+4.1_amd64.deb Size: 6881800 MD5sum: f9adff5c5340f4205bc58282a0caaae2 SHA1: 92df5ceccbf7329112e9a2261ba018f230ac9926 SHA256: f1aeec224d3597cf1d518cdd5742b1760e89ef8cd3ee490a1436e02ace669bb8 Section: biology Priority: optional Homepage: http://github.com/madhavPdesai/ahir Description: NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons. Package: nest-dbg Source: nest Version: 2.16.0+4.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 7 Filename: ./amd64/nest-dbg_2.16.0+4.1_amd64.deb Size: 1160 MD5sum: 02aecb51c4937dd886800c8e1e47e053 SHA1: 81d87eea82edc3d1642068f0c223eeaadc97eb99 SHA256: 41e4912dfcc261c33b248c84a759fcb6a8a06254b875f23f5c1597bd8f7c4fee Section: debug Priority: extra Homepage: http://github.com/madhavPdesai/ahir Description: debugging symbols for nest Package: nest-dev Source: nest Version: 2.16.0+4.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 2597 Filename: ./amd64/nest-dev_2.16.0+4.1_amd64.deb Size: 320084 MD5sum: 103e394446fc39a4ac0342d446fd62d1 SHA1: b79e3367c35e2bf6b7cec52b43f619a225219c03 SHA256: f9ef3fd33ac5f95708faa3f28da449b893edbc9ace72a2e5a0187efde67bdbd4 Section: libdevel Priority: optional Multi-Arch: same Homepage: http://github.com/madhavPdesai/ahir Description: NEST development package This package contains C++ header files. Package: smoldyn Version: 2.62-1+8.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 6114 Depends: freeglut3, libc6 (>= 2.27), libgcc1 (>= 1:3.3.1), libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 5.2), libtiff5 (>= 4.0.3) Filename: ./amd64/smoldyn_2.62-1+8.1_amd64.deb Size: 999148 MD5sum: d620f22c7d95db7ed4410f607b5f53fe SHA1: 98cbf6a230a9de6ccedafa63c7566fbbbc81114c SHA256: fe49882f220ea58f379d96865ee2d04ab666daff144e344b70cca0a60ae0fb04 Section: science Priority: optional Homepage: http://smoldyn.org Description: is a computer program for cell-scale biochemical simulations. It simulates each molecule of interest individually to capture natural stochasticity and to yield nanometer-scale spatial resolution. It treats other molecules implicitly, enabling it to simulate hundreds of thousands of molecules over several minutes of real time. Simulated molecules diffuse, react, are confined by surfaces, and bind to membranes much as they would in a real biological system. Package: stimfit Version: 0.16.git+37.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 874 Depends: libblas3 | libblas.so.3, libc6 (>= 2.14), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:3.0), libhdf5-100, liblapack3 | liblapack.so.3, libstdc++6 (>= 5.2) Filename: ./amd64/stimfit_0.16.git+37.1_amd64.deb Size: 278348 MD5sum: ccf99979a8b3c1e97258e22df41fe64f SHA1: be66936f33ab567df417a7bb3756de10f6d7343c SHA256: a00374eac964e0f1c474f3484502508d70bff85a2ef27007600c074abd1b666a Section: science Priority: optional Description: A 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: tippecanoe Version: 1.35.0+8.1 Architecture: amd64 Maintainer: Dilawar Singh Installed-Size: 1154 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libsqlite3-0 (>= 3.5.9), libstdc++6 (>= 5.2), zlib1g (>= 1:1.2.0.2) Filename: ./amd64/tippecanoe_1.35.0+8.1_amd64.deb Size: 341664 MD5sum: bb67e82bef400cd677d2995999899b36 SHA1: 7af413fdcefefd3c77046336f64a6a809b69608e SHA256: 5404fccca433959436c68bdeb35ec63f53ec43d8cc2d6a6c07c1a37334baaf5a Section: science Priority: optional Homepage: http://gitlab.com/mapbox/tippecanoe Description: The goal of Tippecanoe is to enable making a scale-independent view of your data, so that at any level from the entire world to a single building, you can see the density and texture of the data rather than a simplification from dropping supposedly unimportant features or clustering or aggregating them.