传说与Radarchart环路(Legend with Radarchart in loop)

作为一个循环的一部分，我创建了几个radarcharts。每个图表是一个国家，在蜘蛛网显示的信息是数年（不同颜色的线）的数据。我想补充一个传奇，其将明确哪些线路（颜色）涉及一年。至于我可以看到，在radarchart帮助文件是在这个沉默。（我看到以前的职位就此事，但不认为这是适用，因为我在这里的工作循环）。我将是任何暗示感激。

下面是关于循环的一个迭代的数据：

require(fmsb)

Radar.tmp<–list(cowc = c("0", "0", "ZIM", "ZIM", "ZIM", "ZIM", 
"ZIM", "ZIM", "ZIM", "ZIM", "ZIM", "ZIM", "ZIM", "ZIM", "ZIM", 
"ZIM"), year = c(0, 0, 1996, 1998, 2000, 2002, 2003, 2004, 2005, 
2006, 2007, 2008, 2009, 2010, 2011, 2012), RoL.Estimate = c(2.5, 
-2.5, -0.82, -0.71, -1.33, -1.59, -1.68, -1.76, -1.77, -1.73, 
-1.78, -1.77, -1.84, -1.81, -1.79, -1.62), GovEff.Estimate = c(2.5, 
-2.5, -0.23, -0.37, -0.78, -0.9, -0.95, -0.95, -1.29, -1.3, -1.27, 
-1.5, -1.52, -1.5, -1.36, -1.21), RegQual.Estimate = c(2.5, -2.5, 
-0.98, -0.79, -1.46, -1.97, -2, -2.03, -2.21, -1.96, -2.16, -2.11, 
-2.1, -2.05, -1.92, -1.83), ControlCorruption.Estimate = c(2.5, 
-2.5, -0.25, -0.65, -0.95, -1.21, -1.25, -1.31, -1.28, -1.33, 
-1.36, -1.31, -1.32, -1.31, -1.38, -1.27), PolStab.Estimate = c(2.5, 
-2.5, -0.53, -0.88, -1.42, -1.6, -1.14, -1.26, -1.24, -0.91, 
-1.11, -1.2, -1.16, -1.12, -0.95, -0.79), VoiceAccount.Estimate = c(2.5, 
-2.5, -0.62, -0.82, -1.11, -1.41, -1.44, -1.55, -1.66, -1.54, 
-1.57, -1.54, -1.54, -1.48, -1.47, -1.45)), .Names = c("cowc", 
"year", "RoL.Estimate", "GovEff.Estimate", "RegQual.Estimate", 
"ControlCorruption.Estimate", "PolStab.Estimate", "VoiceAccount.Estimate"
), row.names = c(1L, 2L, 2689L, 2690L, 2691L, 2692L, 2693L, 2694L, 
2695L, 2696L, 2697L, 2698L, 2699L, 2700L, 2701L, 2702L), class = "data.frame")

此命令为radarchart：

 radarchart(Radar.tmp[,c("RoL.Estimate","GovEff.Estimate","RegQual.Estimate","ControlCorruption.Estimate","PolStab.Estimate","VoiceAccount.Estimate")], 
             axistype=2, seg=10, pcol=1:8, pty=16, plty=1, maxmin=TRUE, axislabcol="grey", title=c)

这是因为它看起来此刻的图表：

需要注意的是岁月的量（行数）将迭代在循环改为迭代。

据我所知，有一些严重的缺点radarcharts，但想请你把它们放在一边的那一刻。

非常感谢任何提示/咨询！

发现我一直在寻找：

legend(1.5,1, legend=unique(Radar.tmp$year), seg.len=0.5, title="year", pch=1, 
    bty="n" ,lwd=3, y.intersp=0.5, horiz=FALSE, col=unique(Radar.tmp$year))