While transforming a simple table into a supertabuler, the compiler kept working for long minutes. After investigating, I find out that \tabcolsep into p{} might be the problem... Could you guys explain to me why it does this behaviour? Maybe it is a bad habit aswell, so tell me otherwise.
Thanks in advance!
MWE:
\documentclass{article}
\usepackage{supertabular, booktabs}
%%These packaged should not interfer imo but I let them in case it has something to do with my problem
\newcommand{\tabitem}{\llap{\textbullet}}
\usepackage{array} %% Array m option in particular (center and sized)
\usepackage{diagbox} %% Array diagonal box
\usepackage{multirow} %for multi row in table
\begin{document}
\begin{center}
\tablefirsthead{%
\toprule{}
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \
\midrule{}
}
\tablehead{%
%\hline\multicolumn{4}{|l|}{\small\sl continued from previous page}\
\toprule{}
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \
\midrule{}
}
\tabletail{%
\bottomrule{}
}
\tablelasttail{%
\bottomrule{}
}
%%Notworking
%\begin{supertabular}{@{}p{0.20\textwidth-\tabcolsep}p{0.22\textwidth-2\tabcolsep}p{0.20\textwidth-2\tabcolsep}p{0.18\textwidth-2\tabcolsep}p{0.20\textwidth-\tabcolsep}@{}}
%%Working
\begin{supertabular}{@{}p{0.20\textwidth}|r@{\hspace{5.5mm}}|r|r|r|}
1 & 1 & 1 & 1 \
2 & 4 & 16 & 2 \
3 & 9 & 81 & 6 \
4 & 16 & 256 & 24 \
[5mm]...19 & 361 & 130321 & 1.21645100E+17\
20 & 400 & 160000 & 2.43290200E+18\
\end{supertabular}
\end{center}
\end{document}
EDIT:
thanks to David Carlisle and this post, i updated the first MWE as follow:
\documentclass{article}
\usepackage{supertabular, booktabs}
\newcommand{\tabitem}{~~\llap{\textbullet}~~}
\usepackage{array} %% Array m option in particular (center and sized)
\usepackage{diagbox} %% Array diagonal box
\usepackage{multirow} %for multi row in table
\begin{document}
\begin{center}
\tablefirsthead{%
\toprule{}
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \ \midrule{} \
}
\tablehead{%
%\hline\multicolumn{4}{|l|}{\small\sl continued from previous page}\
\toprule{}
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \ \midrule{} \
}
\tabletail{%
\bottomrule{}
\multicolumn{5}{}{\small continued on next page} \
\bottomrule{} \
}
\tablelasttail{%
\bottomrule{} \
}
\tablecaption{Publication Distribution with the Design Space}
\label{tab: designSpace}
\begin{supertabular}{@{}p{\dimexpr 0.20\textwidth-\tabcolsep \relax}p{\dimexpr 0.22\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-2\tabcolsep \relax}p{\dimexpr 0.18\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-\tabcolsep\relax }@{}}
%\begin{supertabular}{lllll}
%\endhead
Multi-Agent System (MAS)
&
&
&
&
\
Evolutionary Algorithm (EA)
&
&
&
& \
Simulated Annealing (SA)
&
&
&
& \
Tabu search
&
&
&
& \
Particle Swarm Optimisation
&
&
&
& \
Ant Colony Algorithm
&
&
&
& \
Bee Colony Algorithm
&
&
&
& \
Neural Network (NN)
&
&
&
& \
Deep Deterministic Policy Gradient (DDPG)
&
&
&
& \
Convolutional Neural Networks (CNN)
&
&
&
& \
Deep Q-Network (DQN)
&
&
&
& \
Deep Learning
&
&
&
& \
Autoencoder
&
&
&
& \
Random Forest (RF)
&
&
&
& \
Quantile Regression Forest
&
&
&
& \
Gradient Boosting Machine (GBM)
&
&
&
& \
Support Vector Machine (SVM)
&
&
&
& \
Decision Tree
&
&
&
& \
Fuzzy Logic
&
&
&
& \
Linear Regression
&
&
&
& \
Linear Functional Regression
&
&
&
& \
Linear Discriminant Analysis (LDA)
&
&
&
& \
Quadratic Discriminant Analysis (QDA)
&
&
&
& \
Logistic regression
&
&
&
& \
Binary logistic regression models
&
&
&
& \
Gaussian Mixture Model
&
&
&
& \
Bayesian Network
&
&
&
& \
Recursive Bayesian estimation
&
&
&
& \
k-nearest neighbor (k-NN)
&
&
&
&\
Genetic algorithm
&
&
&
& \
Hierarchical clustering
&
&
&
& \
Dynamic Bayesian Belief Network
&
&
&
& \
BIRCH
&
&
&
& \
DBSCAN
&
&
&
& \
OPTIC
&
&
&
& \
K-means
&
&
&
& \
Non Negative Matrix Factorisation (NMF)
&
&
&
& \
A*
&
&
&
& \
Multi-Layer Perceptron (MLP)
&
&
&
& \
Deep Reinforcement Learning
&
&
&
& \
Recurrent neural network & LSTM
&
&
&
& \
Reinforcement Learning
&
&
&
& \
k-nearest neighbours (kNN)
&
&
&
& \
Principal Component Analysis (PCA)
&
&
&
& \
OPTICS clustering
&
&
&
& \
Not referenced
&
&
&
& \
\end{supertabular}
\end{center}
\end{document}
p{0.20\textwidth-\tabcolsep}is a syntax errorp{\dimexpr 0.20\textwidth-\tabcolsep \relax}(not related to tabcolsep in particular; the same would be true of any length expression. – David Carlisle Jul 15 '21 at 10:30