python-bumps 0.8.0-1 source package in Ubuntu

Changelog

python-bumps (0.8.0-1) unstable; urgency=medium

  * New upstream release.
  * Update Standards-Version to 4.5.1 (no changes required).
  * Add lintian overrides to improve S/N of lintian.

 -- Stuart Prescott <email address hidden>  Sun, 20 Dec 2020 12:33:21 +1100

Upload details

Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any-amd64 any-i386 all powerpc
Section:
misc
Urgency:
Medium Urgency

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Series Pocket Published Component Section

Builds

Hirsute: [FULLYBUILT] amd64

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File Size SHA-256 Checksum
python-bumps_0.8.0-1.dsc 2.5 KiB 5b5dd0984b60df1ff724f59da48a1f4d1e8bbf69f947fe3f108b9803772b13ab
python-bumps_0.8.0.orig.tar.gz 3.5 MiB 225dd236fd014f9cd15fbaec5badbcb65d4f1e31a96dc62f71f042e4ed091c5b
python-bumps_0.8.0-1.debian.tar.xz 12.7 KiB bbc19f1c1ca1916b83faab61bcad0b11f813d6aab7af75d0f404ed19721e6f8f

Available diffs

No changes file available.

Binary packages built by this source

bumps-private-libs: data fitting and Bayesian uncertainty modeling for inverse problems (libraries)

 Bumps is a set of routines for curve fitting and uncertainty analysis
 from a Bayesian perspective. In addition to traditional optimizers
 which search for the best minimum they can find in the search space,
 bumps provides uncertainty analysis which explores all viable minima
 and finds confidence intervals on the parameters based on uncertainty
 in the measured values. Bumps has been used for systems of up to 100
 parameters with tight constraints on the parameters. Full uncertainty
 analysis requires hundreds of thousands of function evaluations,
 which is only feasible for cheap functions, systems with many
 processors, or lots of patience.
 .
 Bumps includes several traditional local optimizers such as
 Nelder-Mead simplex, BFGS and differential evolution. Bumps
 uncertainty analysis uses Markov chain Monte Carlo to explore the
 parameter space. Although it was created for curve fitting problems,
 Bumps can explore any probability density function, such as those
 defined by PyMC. In particular, the bumps uncertainty analysis works
 well with correlated parameters.
 .
 Bumps can be used as a library within your own applications, or as a
 framework for fitting, complete with a graphical user interface to
 manage your models.
 .
 This package installs the compiled libraries used by the Python modules.

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