How to Install and Uninstall python312-fastcluster Package on openSuSE Tumbleweed

Last updated: May 20,2024

1. Install "python312-fastcluster" package

Please follow the guidance below to install python312-fastcluster on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python312-fastcluster
            
                    
    
    Copied

2. Uninstall "python312-fastcluster" package

Please follow the instructions below to uninstall python312-fastcluster on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python312-fastcluster
            
                    
    
    Copied

3. Information about the python312-fastcluster package on openSuSE Tumbleweed

Information for package python312-fastcluster:
----------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python312-fastcluster
Version : 1.2.6-1.8
Arch : x86_64
Vendor : openSUSE
Installed Size : 139.2 KiB
Installed : No
Status : not installed
Source package : python-fastcluster-1.2.6-1.8.src
Upstream URL : https://github.com/dmuellner/fastcluster
Summary : Hierarchical clustering routines for Python
Description :
This library provides Python functions for hierarchical clustering.
It generates hierarchical clusters from distance matrices or from
vector data.
Part of this module is intended to replace the functions
linkage, single, complete, average, weighted, centroid, median, ward
in the module scipy.cluster.hierarchy with the same functionality but
much faster algorithms. Moreover, the function 'linkage_vector'
provides memory-efficient clustering for vector data.
The interface is very similar to MATLAB's Statistics Toolbox API to
make code easier to port from MATLAB to Python/Numpy. The core
implementation of this library is in C++ for efficiency.