Result for 0F07881FBAF5CB40FBB15009D9A70E730FA091F4

Query result

Key Value
FileName./usr/lib/python3/dist-packages/neo/test/iotest/test_plexonio.py
FileSize535
MD52BF9B707BE87339E5AD165BB9D0B39E5
SHA-10F07881FBAF5CB40FBB15009D9A70E730FA091F4
SHA-256C8A7AF4BDEE55EFD5EC418630BDE6A3990D9B5259C7D5907F5AC65D4A6461C12
SSDEEP12:icKyp/APRjCyzAyJ+idvucdgHcGwQ5z4wShn4wYa4wWY5s2pV7u:ll/APR2BgluWgeQR4jn4W4EHpVS
TLSHT12BF0B437C827158157E951CEAF1465607232D94F4FC05439BFDCC3285F8291457A8A9C
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize1138884
MD5983A0AA5E55D95BB3BC0BAF2C39B5D8E
PackageDescriptionPython IO library for electrophysiological data formats NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples. . NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab). . Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-neo
PackageSectionpython
PackageVersion0.7.2-2
SHA-1967E0A9367A243B475794753EADBC0454D54C742
SHA-256B2A9448C493E9FFB0A5B7A245A13F0BB33BEC7B35CA1E850080C51B2626A7F47
Key Value
MD5DE172C5661ECE64EC747AD005B3BADA9
PackageArchnoarch
PackageDescription Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and support for writing to a subset of these formats plus non-proprietary formats including HDF5. The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, NeuroTools, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. Neo implements a hierarchical data model well adapted to intracellular and extracellular electrophysiology and EEG data with support for multi-electrodes (for example tetrodes). Neos data objects build on the quantities_ package, which in turn builds on NumPy by adding support for physical dimensions. Thus neo objects behave just like normal NumPy arrays, but with additional metadata, checks for dimensional consistency and automatic unit conversion. Read the documentation at http://neo.readthedocs.io/
PackageMaintainerFedora Project
PackageNamepython3-neo
PackageRelease2.fc32
PackageVersion0.8.0
SHA-1002FE731F130D730F3F1A94C931B421220E5E349
SHA-256201604F118591909D133C29268E99BFAD3826A16BF730C0049D6B21E1884E679
Key Value
MD5E7B46548AA59CF6E2FF2CD62E7CE29D2
PackageArchnoarch
PackageDescription Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and support for writing to a subset of these formats plus non-proprietary formats including HDF5. The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, NeuroTools, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. Neo implements a hierarchical data model well adapted to intracellular and extracellular electrophysiology and EEG data with support for multi-electrodes (for example tetrodes). Neos data objects build on the quantities_ package, which in turn builds on NumPy by adding support for physical dimensions. Thus neo objects behave just like normal NumPy arrays, but with additional metadata, checks for dimensional consistency and automatic unit conversion. Read the documentation at http://neo.readthedocs.io/
PackageMaintainerFedora Project
PackageNamepython3-neo
PackageRelease4.fc33
PackageVersion0.8.0
SHA-1E594B3C91800995BA90A566B1444F74B3F90C1C1
SHA-25612B8AC557E6D9108892461F15334F06BA5F946357604B4203B785122792F669A