How to Install and Uninstall bumps-private-libs Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 22,2024

1. Install "bumps-private-libs" package

This guide covers the steps necessary to install bumps-private-libs on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                bumps-private-libs
            
                    
    
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2. Uninstall "bumps-private-libs" package

Please follow the guidance below to uninstall bumps-private-libs on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                bumps-private-libs
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the bumps-private-libs package on Ubuntu 20.10 (Groovy Gorilla)

Package: bumps-private-libs
Architecture: amd64
Version: 0.7.16-1
Priority: optional
Section: universe/libs
Source: python-bumps
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 37
Depends: libc6 (>= 2.29), libgomp1 (>= 4.9)
Filename: pool/universe/p/python-bumps/bumps-private-libs_0.7.16-1_amd64.deb
Size: 11668
MD5sum: 0897752ee80a7f4f6d65dc35c139f6cb
SHA1: cbf9cac85c05b123b03546e9b277c55dbe25c225
SHA256: f07dbee59cd4915a4b36df8d7e23f73a36bf5be32f887a2a2b1e68df0bde33db
SHA512: 3cc19555dc8c1185d4e636699002c393fdee5ba957e7053183f883ae5eb3d318fdd380d6694a6fb24647f540c90ee856f6e51e1c45f642419a8b5eeb08722835
Homepage: https://github.com/bumps/bumps
Description-en: 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.
Description-md5: 16f34adb9a91abb350eaff82feff9898