我正在使用 supertabular,遇到了两个问题。首先,它从新列开始表格(标题除外,这很奇怪),其次,它在页面上断点太早了。有人对此有任何解决方案吗?
以下是解决我的问题的代码:
Rows in the table highlighted yellow indicate traditional partition methods, those highlighted blue indicate NP ideal solutions, and those highlighted pink represent partitions from the SNN.
\begin{center} \tablecaption{模拟结果} \tablefirsthead{% \toprule \tbsp # 节点 & 分区类型 & 时间 & 切割 & 能量 & 模块化 \ \midrule} \tablehead{% \toprule \multicolumn{6}{l}{\small\sl 接上一页}\ \midrule \tbsp # 节点 & 分区类型 & 时间 & 切割 & 能量 & 模块化 \ \midrule} \tabletail{% \midrule \multicolumn{6}{r}{\small\sl 接下页}\ \bottomrule} \tablelasttail{\hline} \label{tab:results}
\begin{supertabular}{@{} llllll @{}}
\rowcolor{yellow} \textbf{9}
& kernighan-lin & 473.26 \textmu s & -11 & 17 & 0.170 \\
\rowcolor{yellow} & girvan-newman & 2.01 ms & -7 & 20 & 0.180 \\
\rowcolor{cyan} & ideal cut & 46.04 ms & -11 & 19 & 0.186 \\
\rowcolor{cyan} & ideal energy & 46.04 ms & -7 & 20 & 0.180 \\
\rowcolor{cyan} & ideal modularity & 46.04 ms & -11 & 19 & 0.186 \\
\rowcolor{pink} & SNN \#0 & 1.46 ns & -7 & 15 & 0.125 \\
\rowcolor{pink} & SNN \#1 & 1.46 ns & -11 & 16 & 0.186 \\
\rowcolor{pink} & SNN \#2 & 1.46 ns & -11 & 17 & 0.170 \\
\addlinespace
\rowcolor{yellow} \textbf{18}
& kernighan-lin & 715.02 \textmu s & -60 & 83 & 0.284 \\
\rowcolor{yellow} & girvan-newman & 29.86 ms & -64 & 89 & 0.306 \\
\rowcolor{cyan} & ideal cut & 72.48 s & -64 & 89 & 0.305 \\
\rowcolor{cyan} & ideal energy & 72.48 s & 32 & 101 & 0.149 \\
\rowcolor{cyan} & ideal modularity & 72.48 s & -64 & 89 & 0.305 \\
\rowcolor{pink} & SNN \#0 & 5.83 ns & -32 & 67 & 0.245 \\
\rowcolor{pink} & SNN \#1 & 5.83 ns & -32 & 73 & 0.183 \\
\rowcolor{pink} & SNN \#2 & 5.83 ns & -36 & 73 & 0.208 \\
\rowcolor{pink} & SNN \#3 & 5.83 ns & -44 & 74 & 0.247 \\
\addlinespace
\rowcolor{yellow} \textbf{20}
& kernighan-lin & 979.42 \textmu s & -74 & 85 & 0.203 \\
\rowcolor{yellow} & girvan-newman & 44.43 ms & -82 & 85 & 0.224 \\
\rowcolor{pink} & SNN \#0 & 7.20 ns & -42 & 67 & 0.170 \\
\rowcolor{pink} & SNN \#1 & 7.20 ns & -46 & 70 & 0.160 \\
\rowcolor{pink} & SNN \#2 & 7.20 ns & -58 & 74 & 0.184 \\
\addlinespace
\rowcolor{yellow} \textbf{22}
& metis & 1.64 ms & -92 & 91 & 0.177 \\
\rowcolor{yellow} & kernighan-lin & 1.61 ms & -92 & 89 & 0.177 \\
\rowcolor{yellow} & girvan-newman & 84.34 ms & 180 & 101 & -0.00296 \\
\rowcolor{cyan} & ideal cut & 2.09 ks & -92 & 93 & 0.178 \\
\rowcolor{cyan} & ideal energy & 2.09 ks & -36 & 101 & 0.124 \\
\rowcolor{cyan} & ideal modularity & 2.09 ks & -92 & 93 & 0.178 \\
\rowcolor{pink} & SNN \#0 & 8.71 ns & -76 & 81 & 0.152 \\
\rowcolor{pink} & SNN \#1 & 8.71 ns & -76 & 81 & 0.152 \\
\rowcolor{pink} & SNN \#2 & 8.71 ns & -88 & 88 & 0.169 \\
\addlinespace
\rowcolor{yellow} \textbf{24}
& kernighan-lin & 1.32 ms & -104 & 108 & 0.173 \\
\rowcolor{yellow} & girvan-newman & 156.77 ms & -104 & 104 & 0.178 \\
\rowcolor{cyan} & ideal cut & 8.58 ks & -108 & 108 & 0.18 \\
\rowcolor{cyan} & ideal energy & 8.58 ks & -44 & 126 & 0.133 \\
\rowcolor{cyan} & ideal modularity & 8.58 ks & -108 & 108 & 0.18 \\
\rowcolor{pink} & SNN \#0 & 10.37 ns & -96 & 100 & 0.166 \\
\rowcolor{pink} & SNN \#1 & 10.37 ns & -96 & 100 & 0.166 \\
\rowcolor{pink} & SNN \#2 & 10.37 ns & -100 & 103 & 0.172 \\
%\addlinespace
\rowcolor{yellow} \textbf{24}
& metis & 1.36 ms & -120 & 153 & 0.306 \\* % no page break at this line
\rowcolor{yellow} & kernighan-lin & 15.03 ms & -120 & 153 & 0.306 \\
\rowcolor{yellow} & girvan-newman & 113.37 ms & -104 & 142 & 0.272 \\
\rowcolor{cyan} & ideal cut & 11.05 ks & -120 & 150 & 0.306 \\
\rowcolor{cyan} & ideal energy & 11.05 ks & 76 & 178 & 0.125 \\
\rowcolor{cyan} & ideal modularity & 11.05 ks & -120 & 150 & 0.306 \\
\rowcolor{pink} & SNN \#0 & 1.44 ns & -84 & 160 & 0.234 \\
\rowcolor{pink} & SNN \#1 & 1.44 ns & -104 & 163 & 0.287 \\
\rowcolor{pink} & SNN \#2 & 1.44 ns & -116 & 157 & 0.3 \\
\addlinespace
\rowcolor{yellow} \textbf{25}
& kernighan-lin & 56.65 ms & -131 & 121 & 0.202 \\
\rowcolor{yellow} & girvan-newman & 547.38 ms & -135 & 120 & 0.209 \\
\rowcolor{cyan} & ideal cut & 19.97 ks & -135 & 120 & 0.209 \\
\rowcolor{cyan} & ideal energy & 19.97 ks & -59 & 138 & 0.147 \\
\rowcolor{cyan} & ideal modularity & 19.97 ks & -135 & 120 & 0.209 \\
\rowcolor{pink} & SNN \#0 & 11.25 ns & -107 & 106 & 0.184 \\
\rowcolor{pink} & SNN \#1 & 11.25 ns & -103 & 106 & 0.177 \\
\rowcolor{pink} & SNN \#2 & 11.25 ns & -107 & 106 & 0.184 \\
\rowcolor{pink} & SNN \#3 & 11.25 ns & -87 & 103 & 0.155 \\
\rowcolor{pink} & SNN \#4 & 11.25 ns & -107 & 106 & 0.184 \\
\addlinespace
\rowcolor{yellow} \textbf{35}
& kernighan-lin & 1.66 ms & -233 & 324 & 0.294 \\
\rowcolor{yellow} & girvan-newman & 584.88 ms & -185 & 364 & 0.274 \\
\rowcolor{pink} & SNN \#0 & 22.05 ns & -157 & 269 & 0.269 \\
\rowcolor{pink} & SNN \#1 & 22.05 ns & -93 & 251 & 0.218 \\
\rowcolor{pink} & SNN \#2 & 22.05 ns & -117 & 252 & 0.255 \\
\rowcolor{pink} & SNN \#3 & 22.05 ns & -105 & 250 & 0.241 \\
\addlinespace
\rowcolor{yellow} \textbf{50}
& kernighan-lin & 2.02 ms & -356 & 770 & 0.348 \\
\rowcolor{yellow} & girvan-newman & 776.80 ms & -8 & 556 & 0.269 \\
\rowcolor{pink} & SNN \#0 & 45.00 ns & 92 & 522 & 0.240 \\
\rowcolor{pink} & SNN \#1 & 45.00 ns & 108 & 520 & 0.225 \\
\rowcolor{pink} & SNN \#2 & 45.00 ns & 68 & 545 & 0.200 \\
\addlinespace
\rowcolor{yellow} \textbf{50}
& metis & 2.93 ms & -488 & 676 & 0.286 \\
\rowcolor{yellow} & kernighan-lin & 2.65 ms & -480 & 669 & 0.286 \\
\rowcolor{yellow} & girvan-newman & 3.15 s & -424 & 604 & 0.273 \\
\rowcolor{pink} & SNN \#0 & 45.00 ns & -400 & 592 & 0.266 \\
\rowcolor{pink} & SNN \#1 & 45.00 ns & -444 & 611 & 0.282 \\
\end{supertabular} \end{center}
总体而言,使用这种方法模拟的约瑟夫森结在分割图形方面确实表现得非常好。即使图形多达 50 个节点,SNN 也能基本与传统方法一样出色,并且与理想解决方案相差无几。
\subsection{缩放}
在我看来,情况如下: