How to Install and Uninstall python3-neo.noarch Package on Fedora 35

Last updated: September 30,2024

1. Install "python3-neo.noarch" package

Please follow the guidance below to install python3-neo.noarch on Fedora 35


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                python3-neo.noarch
            
                    
    
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2. Uninstall "python3-neo.noarch" package

Learn how to uninstall python3-neo.noarch on Fedora 35:


    
        
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                sudo dnf remove
            
                        
                python3-neo.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-neo.noarch package on Fedora 35

Last metadata expiration check: 1:57:44 ago on Wed Sep 7 02:25:42 2022.
Available Packages
Name : python3-neo
Version : 0.10.1
Release : 1.fc35
Architecture : noarch
Size : 913 k
Source : python-neo-0.10.1-1.fc35.src.rpm
Repository : updates
Summary : Represent electrophysiology data in Python
URL : http://neuralensemble.org/neo/
License : BSD
Description :
: Neo is a package for representing electrophysiology data in Python, together
: with support for reading a wide range of neurophysiology file formats,
: including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and
: support for writing to a subset of these formats plus non-proprietary formats
: including HDF5.
:
: The goal of Neo is to improve interoperability between Python tools for
: analyzing, visualizing and generating electrophysiology data (such as
: OpenElectrophy, NeuroTools, G-node, Helmholtz, PyNN) by providing a common,
: shared object model. In order to be as lightweight a dependency as possible,
: Neo is deliberately limited to represention of data, with no functions for data
: analysis or visualization.
:
: Neo implements a hierarchical data model well adapted to intracellular and
: extracellular electrophysiology and EEG data with support for multi-electrodes
: (for example tetrodes). Neos data objects build on the quantities_ package,
: which in turn builds on NumPy by adding support for physical dimensions. Thus
: neo objects behave just like normal NumPy arrays, but with additional metadata,
: checks for dimensional consistency and automatic unit conversion.
:
: Read the documentation at http://neo.readthedocs.io/