How to Install and Uninstall liblevmar2 Package on openSuSE Tumbleweed

Last updated: February 03,2025

1. Install "liblevmar2" package

In this section, we are going to explain the necessary steps to install liblevmar2 on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                liblevmar2
            
                    
    
    Copied

2. Uninstall "liblevmar2" package

Here is a brief guide to show you how to uninstall liblevmar2 on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                liblevmar2
            
                    
    
    Copied

3. Information about the liblevmar2 package on openSuSE Tumbleweed

Information for package liblevmar2:
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Repository : openSUSE-Tumbleweed-Oss
Name : liblevmar2
Version : 2.6-2.5
Arch : x86_64
Vendor : openSUSE
Installed Size : 147.6 KiB
Installed : No
Status : not installed
Source package : levmar-2.6-2.5.src
Upstream URL : http://users.ics.forth.gr/~lourakis/levmar/
Summary : Levenberg-Marquardt nonlinear least squares algorithm
Description :
levmar is a native ANSI C implementation of the Levenberg-Marquardt
optimization algorithm. Both unconstrained and constrained (under linear
equations, inequality and box constraints) Levenberg-Marquardt variants are
included. The LM algorithm is an iterative technique that finds a local
minimum of a function that is expressed as the sum of squares of nonlinear
functions. It has become a standard technique for nonlinear least-squares
problems and can be thought of as a combination of steepest descent and the
Gauss-Newton method. When the current solution is far from the correct on,
the algorithm behaves like a steepest descent method: slow, but guaranteed
to converge. When the current solution is close to the correct solution, it
becomes a Gauss-Newton method