TeX - LaTeX Asked on December 26, 2020
I have an acronym list using printglossary[type=acronymtype, style=super, nonumberlist]
which looks like the following however there is no space between ML and MPC as seen from the below picture:
Is there a way to have equal spacing for all?
documentclass{memoir}
usepackage[acronym]{glossaries}
newacronym{ml}{ML}{Machine Learning}
newacronym{rl}{RL}{Reinforcement Learning}
newacronym{eeprom}{EEPROM}{electrically erasable programmable read-only memory}
newacronym{lfd}{LfD}{Learning from Demonstration}
newacronym{mpc}{MPC}{Model Predictice Control}
newacronym{pearl}{PEARL}{Probabilistic embeddings for actor-critic RL}
newacronym{ffnn}{FFNN}{Feed forward neural networks}
newacronym{bo}{BO}{Bayesian Optimization}
newacronym{mdp}{MDP}{Markov decision process}
newacronym{pomdp}{POMDP}{Partial observable markov decision process}
makeglossaries
glsaddall
begin{document}
printglossary[type=acronymtype, style=super, nonumberlist]
end{document}
nogroupskip
removes the vertical space between entries with different first letters. renewcommand*{arraystretch}{2}
adds space between all entries (works because the super
style is based on supertabular
)
documentclass{memoir}
usepackage[ngerman, english]{babel}
usepackage{titling}
usepackage{fancyhdr}
usepackage[acronym]{glossaries}
makeglossaries
newacronym{ml}{ML}{Machine Learning}
newacronym{rl}{RL}{Reinforcement Learning}
newacronym{eeprom}{EEPROM}{electrically erasable programmable read-only memory}
newacronym{lfd}{LfD}{Learning from Demonstration}
newacronym{mpc}{MPC}{Model Predictice Control}
newacronym{pearl}{PEARL}{Probabilistic embeddings for actor-critic RL}
newacronym{ffnn}{FFNN}{Feed forward neural networks}
newacronym{bo}{BO}{Bayesian Optimization}
newacronym{mdp}{MDP}{Markov decision process}
newacronym{pomdp}{POMDP}{Partial observable markov decision process}
begin{document}
glsaddall
renewcommand*{arraystretch}{2}
printglossary[type=acronymtype, style=super, nonumberlist, nogroupskip] .
end{document}
Correct answer by leandriis on December 26, 2020
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