Result for 03866390DC5A9543A724F72BAE8223286CCC9C59

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/neo/io/asciiimageio.py
FileSize3185
MD51F532AD7744640BF8289ECC25CA76741
SHA-103866390DC5A9543A724F72BAE8223286CCC9C59
SHA-256BA2B54AE64431E5304A5A4FEEB022C4F2D1CD753BEF52D80681AE9ED17174A44
SSDEEP96:oqAW8B3DwXwUIw7XaFUph2C1sftLvtpjCu:oo8BzEwUIw602C1GJvtpB
TLSHT18B6142179C7B6402C297D82A0DDA8503B7506637360871A0F5BDE25C2F0DAB0B2F8DED
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

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