How to Install and Uninstall texlive-tikz-nef Package on openSUSE Leap
Last updated: December 26,2024
1. Install "texlive-tikz-nef" package
Please follow the instructions below to install texlive-tikz-nef on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
texlive-tikz-nef
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2. Uninstall "texlive-tikz-nef" package
Please follow the steps below to uninstall texlive-tikz-nef on openSUSE Leap:
$
sudo zypper remove
texlive-tikz-nef
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3. Information about the texlive-tikz-nef package on openSUSE Leap
Information for package texlive-tikz-nef:
-----------------------------------------
Repository : Main Repository
Name : texlive-tikz-nef
Version : 2021.189.0.0.1svn55920-150400.17.1
Arch : noarch
Vendor : SUSE LLC
Installed Size : 1.6 KiB
Installed : No
Status : not installed
Source package : texlive-specs-x-2021-150400.17.1.src
Upstream URL : http://www.tug.org/texlive/
Summary : Create diagrams for neural networks constructed with the methods of the Neural Engineering Framework (NEF)
Description :
The nef TikZ library provides predefined styles and shapes to
create diagrams for neural networks constructed with the
methods of the Neural Engineering Framework (NEF). The
following styles are supported: ea: ensemble array ens:
ensemble ext: external input or output inhibt: inhibitory
connection net: network pnode: pass-through node rect:
rectification ensemble recurrent: recurrent connection
-----------------------------------------
Repository : Main Repository
Name : texlive-tikz-nef
Version : 2021.189.0.0.1svn55920-150400.17.1
Arch : noarch
Vendor : SUSE LLC
Installed Size : 1.6 KiB
Installed : No
Status : not installed
Source package : texlive-specs-x-2021-150400.17.1.src
Upstream URL : http://www.tug.org/texlive/
Summary : Create diagrams for neural networks constructed with the methods of the Neural Engineering Framework (NEF)
Description :
The nef TikZ library provides predefined styles and shapes to
create diagrams for neural networks constructed with the
methods of the Neural Engineering Framework (NEF). The
following styles are supported: ea: ensemble array ens:
ensemble ext: external input or output inhibt: inhibitory
connection net: network pnode: pass-through node rect:
rectification ensemble recurrent: recurrent connection