How to Install and Uninstall alfa Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 26,2024

1. Install "alfa" package

Please follow the instructions below to install alfa on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                alfa
            
                    
    
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2. Uninstall "alfa" package

Learn how to uninstall alfa on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                alfa
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the alfa package on Ubuntu 20.10 (Groovy Gorilla)

Package: alfa
Architecture: amd64
Version: 1.0-3build3
Priority: optional
Section: universe/science
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Astronomy Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 426
Depends: libc6 (>= 2.27), libcfitsio9 (>= 3.480~), libgfortran5 (>= 10), libgomp1 (>= 6)
Filename: pool/universe/a/alfa/alfa_1.0-3build3_amd64.deb
Size: 81540
MD5sum: bb81ab4d1ee36db5825a2acb18eb83bf
SHA1: 3f5b39046c1ae307f204f1cd01ae7caf04e07788
SHA256: a54d640b6242e8561e6bcc23851afef006acc09642fb49e1eccc35505a5c83f6
SHA512: 2c4499f08ce319b59ea7f0c283413d19ec3726d38e84b6ee5a775da25987f1fedea3af18da9154f8d4dffb680a732032a11cc6b5916018d383287829802a35ad
Homepage: https://github.com/rwesson/ALFA
Description-en: Automated Line Fitting Algorithm
ALFA measures fluxes in emission line spectra, such as those of planetary
nebulae and HII regions, using a genetic algorithm to rapidly optimise fits
to large numbers of lines simultaneously. It can subtract night sky emission
lines before fitting the nebular lines if necessary. It can read plain text
files containing 1D spectral data, or FITS files containing 1D, 2D or 3D
datasets.
Description-md5: eb7520e82a18ed6e7eea5d4bbf9fde07