How to Install and Uninstall python3-bumps Package on Ubuntu 21.10 (Impish Indri)
Last updated: November 26,2024
1. Install "python3-bumps" package
Here is a brief guide to show you how to install python3-bumps on Ubuntu 21.10 (Impish Indri)
$
sudo apt update
Copied
$
sudo apt install
python3-bumps
Copied
2. Uninstall "python3-bumps" package
Please follow the instructions below to uninstall python3-bumps on Ubuntu 21.10 (Impish Indri):
$
sudo apt remove
python3-bumps
Copied
$
sudo apt autoclean && sudo apt autoremove
Copied
3. Information about the python3-bumps package on Ubuntu 21.10 (Impish Indri)
Package: python3-bumps
Architecture: all
Version: 0.8.0-1
Priority: optional
Section: universe/python
Source: python-bumps
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1677
Depends: python3-matplotlib (>= 1.0), python3-numpy (>= 1.3.0), python3-scipy (>= 0.7.0), python3-six, python3:any
Recommends: bumps-private-libs, python3-wxgtk4.0
Suggests: python-bumps-doc, python3-sklearn
Filename: pool/universe/p/python-bumps/python3-bumps_0.8.0-1_all.deb
Size: 422684
MD5sum: 24ac52c772a3997bb59b72c8dc33da55
SHA1: abb5df350421edaadd6d21e40ed8c965ae68d491
SHA256: 7d10c41ddce712fbaff41607f6b66fb4c272863a383d2d279d79cdf5867d23a5
SHA512: 990b6ba4859e345467beb40c39335eadc478dcc009bd01f1909b5bd8bf3e31aae0f8afadb486bd50e5aac1ff40b7126419d0b58fa486e2ffb5b83c17a43d638d
Homepage: https://github.com/bumps/bumps
Description-en: data fitting and Bayesian uncertainty modeling for inverse problems (Python 3)
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 library for Python 3.
Description-md5: ee6eb4da73526e9011a5a0b6822c213f
Architecture: all
Version: 0.8.0-1
Priority: optional
Section: universe/python
Source: python-bumps
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1677
Depends: python3-matplotlib (>= 1.0), python3-numpy (>= 1.3.0), python3-scipy (>= 0.7.0), python3-six, python3:any
Recommends: bumps-private-libs, python3-wxgtk4.0
Suggests: python-bumps-doc, python3-sklearn
Filename: pool/universe/p/python-bumps/python3-bumps_0.8.0-1_all.deb
Size: 422684
MD5sum: 24ac52c772a3997bb59b72c8dc33da55
SHA1: abb5df350421edaadd6d21e40ed8c965ae68d491
SHA256: 7d10c41ddce712fbaff41607f6b66fb4c272863a383d2d279d79cdf5867d23a5
SHA512: 990b6ba4859e345467beb40c39335eadc478dcc009bd01f1909b5bd8bf3e31aae0f8afadb486bd50e5aac1ff40b7126419d0b58fa486e2ffb5b83c17a43d638d
Homepage: https://github.com/bumps/bumps
Description-en: data fitting and Bayesian uncertainty modeling for inverse problems (Python 3)
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 library for Python 3.
Description-md5: ee6eb4da73526e9011a5a0b6822c213f