Result for 15FAC9B71FF3640B34B50C04ADF0D5FD1B1D6D55

Query result

Key Value
FileName./usr/share/pyshared/brian/__init__.py
FileSize7274
MD5CB12F34955B9A8C6B51A0B4AC359288F
SHA-115FAC9B71FF3640B34B50C04ADF0D5FD1B1D6D55
SHA-2563005D7A8ABB5D76062A3188E20683E865B8D36298704F23FFD9BD3EFF26B0DBD
SSDEEP96:MGhpEl+Z1p680YPnaAqPDKH1P7fqU8ww0UNbscXACSjuc0TA5181P/nqNV+VS5zn:Plp680w168z8Fngohxwxj
TLSHT19DE152720D1E17640131C29E550A966BD322A67B6F3D505278FC851C3FB1FB48BAE2FA
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize391972
MD538B29F07727B3A0A9C593D302D1E440E
PackageDescriptionsimulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-brian
PackageSectionpython
PackageVersion1.3.1-1build1
SHA-1D22A96386DAAAEA729DD4FD466829609044013BA
SHA-2568DDF9628F43F67F9AFEFDEFC72832B8508A76F50009EDFF5A4F6FCE11469A8B0