How to Install and Uninstall bumps-private-libs Package on Ubuntu 21.10 (Impish Indri)

Last updated: November 25,2024

1. Install "bumps-private-libs" package

Please follow the step by step instructions below to install bumps-private-libs on Ubuntu 21.10 (Impish Indri)


    
        
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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

This guide let you learn how to uninstall bumps-private-libs on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                bumps-private-libs
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the bumps-private-libs package on Ubuntu 21.10 (Impish Indri)

Package: bumps-private-libs
Architecture: amd64
Version: 0.8.0-1
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_0.8.0-1_amd64.deb
Size: 11468
MD5sum: e80961ec4620218dcd22d77ded68459b
SHA1: 18f4b643e0d48b2c6dfe538cb9db69fb6329a685
SHA256: ad74dddbca9df5cf5236d7e977e61cdb9623519eb02098a23d2880821b2a229c
SHA512: 87fb76472fb30cd260caf3639274cac5730fe049e27f94eeb9659d2117a4fbf43e71090fa3fc6412bb98b34886902bca2447fd5f9eb103463f7a07bd6221e21d
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