How to Install and Uninstall libdogleg2 Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 17,2024

1. Install "libdogleg2" package

This is a short guide on how to install libdogleg2 on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libdogleg2
            
                    
    
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2. Uninstall "libdogleg2" package

This is a short guide on how to uninstall libdogleg2 on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                libdogleg2
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libdogleg2 package on Ubuntu 21.10 (Impish Indri)

Package: libdogleg2
Architecture: amd64
Version: 0.15.4-1
Multi-Arch: same
Priority: extra
Section: universe/libs
Source: libdogleg
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 58
Depends: libc6 (>= 2.14), libcholmod3 (>= 1:4.5.2), liblapack3 | liblapack.so.3, libsuitesparseconfig5 (>= 1:5.0.0)
Filename: pool/universe/libd/libdogleg/libdogleg2_0.15.4-1_amd64.deb
Size: 17280
MD5sum: 957b569ee86b2ae02c55f063ee560b01
SHA1: 546925295e419682fe5cf1ab274fd7eb94204dcc
SHA256: c80dd369d06fc0f1c403ed5d998dfc0da2486200e29f2473be734d158fb74b22
SHA512: c971ea147b2a4d4a65eee2d1b2ff607705d816dd199e3c6b1cf093563f2440a387d9317fdc656b3e2320527874f8d26cf285af0f12b1b9f398f2f97ad06beafb
Homepage: https://github.com/dkogan/libdogleg
Description-en: Powell's dog-leg nonlinear least squares solver for sparse matrices
Solves unconstrained nonlinear least squares problems using Powell's dog-leg
method. The user specifies a callback C function that returns the value and
gradients of the model function at a particular operating point. This library
takes a series of dog-leg steps to find a local minimum of the residual
surface.
.
This library works with sparse matrices, which makes it suitable for
efficiently solving very large problems.
Description-md5: 37febc8dd44f0e9d04ee3cbf30f325c0