How to Install and Uninstall python3-klusta.noarch Package on Fedora 38

Last updated: November 26,2024

1. Install "python3-klusta.noarch" package

In this section, we are going to explain the necessary steps to install python3-klusta.noarch on Fedora 38


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                python3-klusta.noarch
            
                    
    
    Copied

2. Uninstall "python3-klusta.noarch" package

Please follow the steps below to uninstall python3-klusta.noarch on Fedora 38:


    
        
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                sudo dnf remove
            
                        
                python3-klusta.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-klusta.noarch package on Fedora 38

Last metadata expiration check: 5:00:30 ago on Sat Mar 16 22:59:57 2024.
Available Packages
Name : python3-klusta
Version : 3.0.16
Release : 22.fc38
Architecture : noarch
Size : 248 k
Source : python-klusta-3.0.16-22.fc38.src.rpm
Repository : fedora
Summary : Spike detection and automatic clustering for spike sorting
URL : https://github.com/kwikteam/klusta
License : BSD
Description : klusta is an open source package for automatic spike sorting of multielectrode
: neurophysiological recordings made with probes containing up to a few dozens of
: sites.
:
: klusta implements the following features:
:
: - Kwik: An HDF5-based file format that stores the results of a spike sorting
: session.
: - Spike detection (also known as SpikeDetekt): an algorithm designed for probes
: containing tens of channels, based on a flood-fill algorithm in the adjacency
: graph formed by the recording sites in the probe.
: - Automatic clustering (also known as Masked KlustaKwik): an automatic
: clustering algorithm designed for high-dimensional structured datasets.