How to Install and Uninstall bumps-private-libs Package on Kali Linux

Last updated: November 07,2024

1. Install "bumps-private-libs" package

This tutorial shows how to install bumps-private-libs on Kali Linux


    
        
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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 tutorial shows how to uninstall bumps-private-libs on Kali Linux:


    
        
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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 Kali Linux

Package: bumps-private-libs
Source: python-bumps
Version: 0.9.1-2
Installed-Size: 37
Maintainer: Debian Science Maintainers
Architecture: amd64
Depends: libc6 (>= 2.29), libgomp1 (>= 4.9)
Size: 11808
SHA256: dd9936001c739cd521cd5d39d15e397a6c85b1f6453493eb2acaa40dc8b23ca5
SHA1: d11feec74461037a066f70bb284640baea668d75
MD5sum: 971e20782530dedaa2a42c68a1fe4cd9
Description: 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.
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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.
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This package installs the compiled libraries used by the Python modules.
Description-md5:
Homepage: https://github.com/bumps/bumps
Tag: role::shared-lib
Section: libs
Priority: optional
Filename: pool/main/p/python-bumps/bumps-private-libs_0.9.1-2_amd64.deb