我有这张长桌:
\documentclass[12pt, a4paper, onecolumn, oneside, final]{report}
\makeatother
\usepackage{array}
\setlength\extrarowheight{4pt}
\usepackage{tabto}
\newenvironment{tabs}[1]
{\TabPositions{#1}}
\usepackage{longtable}
\newcolumntype{R}[1]{>{\raggedleft\arraybackslash}p{#1}}
\newcolumntype{L}[1]{>{\raggedright\arraybackslash}p{#1}}
\newcolumntype{C}[1]{>{\centering\arraybackslash}m{#1}}
\usepackage{multicol}
\usepackage{multirow}
\begin{document}
\begin{small}
\begin{longtable}{ |p{5cm}|p{3.5cm}|p{3.6cm}| }
\caption{\textit{State of the Art}}\\
\hline
\textbf{Peneliti} & \textbf{Masalah} & \textbf{Metode}\\
\endfirsthead
\multicolumn{3}{c}{\textbf{\tablename~\thetable} \textit{State of the Art} (Lanjutan)}\\
\hline
\textbf{Peneliti} & \textbf{Masalah} & \textbf{Metode}\\
\endhead
\hline
Chitralekha Gupta, et al.; "\textit{Perceptual Evaluation of Singing Quality}" & Melakukan evaluasi rekaman penyanyi berdasarkan 6 parameter: \textit{pitch, rhythm, voice quality, vibrato, volume, pitch dynamic range}, dan memberikan penilaian atas gabungan parameter tersebut &
\begin{enumerate}
\item \textit{PRAAT} untuk pitch.
\end{enumerate}\\
\hline
Jong Wook Kim, et al.; "\textit{CREPE: A Convolutional Representation for Pitch Estimation}". & Melakukan estimasi \textit{fundamental frequency} dari \textit{monophonic sound recording}, mengembangkan metode \textit{pitch estimation} dari algoritme pYIN. &
\begin{enumerate}
\item \textit{Deep convolutional neural network}.
\end{enumerate}\\
\hline
Rachel M. Bittner, et al.; "\textit{Deep Salience Representations for F$_0$ Estimation in Polyphonic Music}" & Membuat model untuk mempelajari representasi unik dari \textit{pitch} dalam rekaman audio polifonik &
\begin{enumerate}
\item \textit{Full Convolutional Neural Network}.
\end{enumerate}\\
\hline
Dongmei Wang, et al.; "\textit{Robust Harmonic Features for Classification-Based Pitch Estimation}" & Melakukan estimasi \textit{pitch} berdasarkan \textit{robust harmonic features} dengan membuat kandidat \textit{pitch} dan melakukan seleksi target \textit{pitch} &
\begin{enumerate}
\item \textit{Neural Network}.
\item Hidden-Markov Model.
\end{enumerate}
\label{tbl:StateoftheArt}\\
\hline
\end{longtable}
\end{small}
\end{document}
在Metode
列中,我希望这些项目\begin{enumerate}
像其他列一样对齐顶部。我应该从 longtable 代码中修改什么?
答案1
我把这个添加到了序言中
\usepackage{enumitem}
\setlist[enumerate]{topsep=0pt,
before={\vspace{-\normalbaselineskip}\raggedright},
leftmargin=14pt}
得到的 MWE:
\documentclass[12pt, a4paper, onecolumn, oneside, final]{report}
\makeatother
\usepackage{array}
\setlength\extrarowheight{4pt}
\usepackage{tabto}
\newenvironment{tabs}[1]
{\TabPositions{#1}}
\usepackage{longtable}
\newcolumntype{R}[1]{>{\raggedleft\arraybackslash}p{#1}}
\newcolumntype{L}[1]{>{\raggedright\arraybackslash}p{#1}}
\newcolumntype{C}[1]{>{\centering\arraybackslash}m{#1}}
\usepackage{multicol}
\usepackage{multirow}
\usepackage{enumitem}
\setlist[enumerate]{topsep=0pt,
before={\vspace{-\normalbaselineskip}\raggedright},
leftmargin=14pt}
\begin{document}
\begin{small}
\begin{longtable}{ |p{5cm}|p{3.5cm}|p{3.6cm}| }
\caption{\textit{State of the Art}}\\
\hline
\textbf{Peneliti} & \textbf{Masalah} & \textbf{Metode}\\
\endfirsthead
\multicolumn{3}{c}{\textbf{\tablename~\thetable} \textit{State of the Art} (Lanjutan)}\\
\hline
\textbf{Peneliti} & \textbf{Masalah} & \textbf{Metode}\\
\endhead
\hline
Chitralekha Gupta, et al.; "\textit{Perceptual Evaluation of Singing Quality}" & Melakukan evaluasi rekaman penyanyi berdasarkan 6 parameter: \textit{pitch, rhythm, voice quality, vibrato, volume, pitch dynamic range}, dan memberikan penilaian atas gabungan parameter tersebut &
\begin{enumerate}
\item \textit{PRAAT} untuk pitch.
\end{enumerate}\\
\hline
Jong Wook Kim, et al.; "\textit{CREPE: A Convolutional Representation for Pitch Estimation}". & Melakukan estimasi \textit{fundamental frequency} dari \textit{monophonic sound recording}, mengembangkan metode \textit{pitch estimation} dari algoritme pYIN. &
\begin{enumerate}
\item \textit{Deep convolutional neural network}.
\end{enumerate}\\
\hline
Rachel M. Bittner, et al.; "\textit{Deep Salience Representations for F$_0$ Estimation in Polyphonic Music}" & Membuat model untuk mempelajari representasi unik dari \textit{pitch} dalam rekaman audio polifonik &
\begin{enumerate}
\item \textit{Full Convolutional Neural Network}.
\end{enumerate}\\
\hline
Dongmei Wang, et al.; "\textit{Robust Harmonic Features for Classification-Based Pitch Estimation}" & Melakukan estimasi \textit{pitch} berdasarkan \textit{robust harmonic features} dengan membuat kandidat \textit{pitch} dan melakukan seleksi target \textit{pitch} &
\begin{enumerate}
\item \textit{Neural Network}.
\item Hidden-Markov Model.
\end{enumerate}
\label{tbl:StateoftheArt}\\
\hline
\end{longtable}
\end{small}
\end{document}