Result for 35A0E82B20DFA28A5F2A6B36E274922CE993936D

Query result

Key Value
FileName./usr/lib/python3/dist-packages/emcee/moves/__init__.py
FileSize483
MD50823C229E5EDA3CA4D39DD463929C328
SHA-135A0E82B20DFA28A5F2A6B36E274922CE993936D
SHA-2563CF6AC9F21DFCA05064D9943696C4B0275811AD4171DEA7E64D876A00B111831
SSDEEP12:icKyujK5oibeFhDLpxRGF+ELMKB53ABibZFtOR3yReI0QtDKpvTtiJVaRA:l6fT9AWRi4I3tDKBTU/aRA
TLSHT115F0A02FB17B365276ADC5C0823B0D39C3FAE4760E94984BA51403BC6BCEE011DA2E15
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
MD5767CD93A1EC92167E45E132C76566B0B
PackageArchnoarch
PackageDescription emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the Astrophysics literature.
PackageMaintainerFedora Project
PackageNamepython3-emcee
PackageRelease5.fc33
PackageVersion3.0.0
SHA-1167664F6BD8C0380F074E2BA09EC1248D27BFFBF
SHA-2562B1180E638B3CBCC590F27E8A0870704BF7C13EC703733AEF5AE1116550163E5
Key Value
FileSize25188
MD5F4662D5709830423CEAA1A03AEC988C5
PackageDescriptionAffine-invariant ensemble MCMC sampling for Python 3 emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-emcee
PackageSectionpython
PackageVersion3.0.0-1
SHA-1649BC3AA84F0C444C1E18BCE6CEAF7451BB81EAE
SHA-256A4E5B7ED1A1A2C92918329CA22D4EF6ABE267BE202E9970B44D1AF21EFC83318
Key Value
MD5734DA00C6D202B86C99826F82F42F79D
PackageArchnoarch
PackageDescription emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the Astrophysics literature.
PackageMaintainerFedora Project
PackageNamepython3-emcee
PackageRelease3.fc32
PackageVersion3.0.0
SHA-1907DAEBF3FB3D2B725FEF9AB43249CC6F0DE08BB
SHA-25646FF3CDE45A72466AA547A6DE7033EC4CF00A68E5E2A53404F57011765072665