How to Install and Uninstall python-brian-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 21,2024

1. Install "python-brian-doc" package

This is a short guide on how to install python-brian-doc on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                python-brian-doc
            
                    
    
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2. Uninstall "python-brian-doc" package

This tutorial shows how to uninstall python-brian-doc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python-brian-doc
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-brian-doc package on Ubuntu 21.10 (Impish Indri)

Package: python-brian-doc
Architecture: all
Version: 2.4.2-6
Priority: optional
Section: universe/doc
Source: brian
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 18170
Depends: libjs-jquery, libjs-mathjax
Suggests: python3-brian
Filename: pool/universe/b/brian/python-brian-doc_2.4.2-6_all.deb
Size: 1469244
MD5sum: 396f26d1eb07e260f9f3ddd604a36d48
SHA1: 350ed6c2d242315c1fc12b57c653e33b98a834aa
SHA256: 0f7917d7fc68e8d8fc0b219bb40c4ee8f2af04f4e7719782d9066e2bd4692214
SHA512: 7fc8560df39293317173e83a172dbc2b1835b69ad09be6b83607ad51bad6a4908d5d0ba76f4199c4f6dec095e87338928d0e4d4635355e31593e2ae893ddb180
Homepage: http://www.briansimulator.org/
Description-en: simulator for spiking neural networks - documentation
Brian is a clock-driven simulator for spiking neural networks. It is
designed with an emphasis on flexibility and extensibility, for rapid
development and refinement of neural models. Neuron models are
specified by sets of user-specified differential equations, threshold
conditions and reset conditions (given as strings). The focus is
primarily on networks of single compartment neuron models (e.g. leaky
integrate-and-fire or Hodgkin-Huxley type neurons).
.
This package provides user's manual (in HTML format), examples and
demos.
Description-md5: b2060b2f00ee78d5f2e8f55f92acc6ed