How to Install and Uninstall libann0 Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: December 24,2024

1. Install "libann0" package

This tutorial shows how to install libann0 on Ubuntu 20.10 (Groovy Gorilla)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                libann0
            
                    
    
    Copied

2. Uninstall "libann0" package

Please follow the step by step instructions below to uninstall libann0 on Ubuntu 20.10 (Groovy Gorilla):


    
        
            $
        

        
            
                sudo apt remove
            
                        
                libann0
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libann0 package on Ubuntu 20.10 (Groovy Gorilla)

Package: libann0
Architecture: amd64
Version: 1.1.2+doc-7build1
Priority: optional
Section: universe/libs
Source: ann
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 78
Depends: libc6 (>= 2.4), libgcc-s1 (>= 3.0), libstdc++6 (>= 5)
Filename: pool/universe/a/ann/libann0_1.1.2+doc-7build1_amd64.deb
Size: 25956
MD5sum: c1a5d396a8a5ab449d227eb97b8f4bd4
SHA1: 1fb9e464fd87c4d8d0087e4478d20af16cdd2fb4
SHA256: ae1b6ce23c94112c5cfd4c8234e36050305735263884dc2b63858039c199f1be
SHA512: 8506bff84fa7e28756554cc15a47e94e67c1a90dd07f0944e49cf0324e69999f1ab1ab3ef347ce4fa9edb264a7ddc3d20eaf7790c0b9b2088c24f4571fe49442
Homepage: http://www.cs.umd.edu/~mount/ANN/
Description-en: Approximate Nearest Neighbor Searching library
ANN is a library written in C++, which supports data structures and
algorithms for both exact and approximate nearest neighbor searching
in arbitrarily high dimensions. ANN assumes that distances
are measured using any class of distance functions called Minkowski
metrics. These include the well known Euclidean distance, Manhattan
distance, and max distance. ANN performs quite efficiently for point
sets ranging in size from thousands to hundreds of thousands, and in
dimensions as high as 20.
Description-md5: 43ad64911e71bf0591f01f591a2056ac