删除某些因素级别的图例条目 [英] Remove legend entries for some factors levels

问题描述

是否可以去除某些因子水平对应的图例元素?

Is it possible to remove legend elements corresponding to certain factor levels?

在我的示例中，我希望删除灰度因子级别 (1-5) 的图例条目，并仅保留级别最佳"、建议"和最差".

In my example, I wish to remove legend entries for the grey factor levels (1-5), and only keep the levels "Best", "Suggested", and "Worst".

我已经尝试了许多技巧，但其中大多数要么去掉了条形的灰色(每组 25 个)，要么只剩下我涂成红色、黄色和绿色的条形.

I have tried a number of hacks already, but most of them have either removed the grey coloring of the bars (in groups of 25 each) or only left me with the bars that I colored red, yellow, and green.

# ggplot2
barplot <- ggplot(training_results.barplot, mapping=aes(x=name, fill=factor(a))) # filling based on a column ##mapping=aes(x=name, fill=factor(a))
barplot <- barplot + geom_histogram(stat = "identity", aes(name,wer)) ##colour="black"
barplot <- barplot + scale_fill_manual(values=c("#555555", "#777777", "#555555", "#777777", "#555555", color.best, color.suggested, color.worst), labels=c(NA,NA,NA,NA,NA,"Best","Suggested","Worst")) # 6th = best; 7th = suggested; 8th = worst
barplot <- barplot + everyNthLabel(training_results$name,5) # only show every 5th label on x-axis
barplot <- barplot + theme_minimal()
barplot <- barplot + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5),legend.position=c(.5, .9)) # rotate labels on x-axis ##, legend.position="none"
barplot <- barplot + coord_cartesian(ylim = c(35, 45))
# Legend
barplot <- barplot + guides(fill = guide_legend(title="Models", title.position="top", direction="horizontal"))
# Axis labels
barplot <- barplot + xlab("Number of EM-Training Iterations") + opts(axis.title.x = theme_text(vjust=-0.3))
barplot <- barplot + ylab("Word Error Rate (WER)") + opts(axis.title.y = theme_text(vjust=0.2))

我使用的数据如下所示，a 是填充颜色应该依赖的因素；a = 6、7 和 8 标记突出显示的案例(分别为绿色、黄色和红色).

The data I'm using looks as follows, with a being the factor that the filling color should depend on; a = 6, 7, and 8 mark the highlighted cases (green, yellow, and red, respectively).

    a b c  name  corr   acc    H   D    S   I    N   wer
1   1 1 1 1+1+1 66.63 59.15 4167 238 1849 468 6254 40.85
2   1 1 2 1+1+2 66.66 59.29 4169 235 1850 461 6254 40.71
3   1 1 3 1+1+3 66.81 59.42 4178 226 1850 462 6254 40.58
4   8 1 4 1+1+4 66.57 59.08 4163 223 1868 468 6254 40.92
5   1 1 5 1+1+5 66.89 59.34 4183 226 1845 472 6254 40.66
6   1 2 1 1+2+1 66.63 59.10 4167 240 1847 471 6254 40.90
7   1 2 2 1+2+2 66.82 59.45 4179 228 1847 461 6254 40.55
8   1 2 3 1+2+3 66.74 59.31 4174 225 1855 465 6254 40.69
9   1 2 4 1+2+4 67.00 59.50 4190 226 1838 469 6254 40.50
10  1 2 5 1+2+5 66.90 59.19 4184 230 1840 482 6254 40.81
11  1 3 1 1+3+1 66.68 59.16 4170 227 1857 470 6254 40.84
12  1 3 2 1+3+2 66.76 59.23 4175 226 1853 471 6254 40.77
etc.

推荐答案

首先，由于用于 fill 的变量是数字，然后将其转换为因子(例如具有不同名称 a2)并设置根据需要标记因子水平(每个水平需要不同的标签，因此对于前五个数字，我使用相同的数字).

First, as your variable used for the fill is numeric then convert it to factor (for example with different name a2) and set labels for factor levels as you need (each level needs different label so for the first five numbers I used the same numbers).

training_results.barplot$a2 <- factor(training_results.barplot$a,
                                      labels = c("1", "2", "3", "4", "5", "Best", "Suggested", "Worst"))

现在将这个新变量用于 fill =.这将根据需要制作图例中的标签.使用 scale_fill_manual() 中的参数 breaks=，您可以设置需要在图例中显示的级别，但删除参数 labels =.两个参数只有在长度相同时才能使用.

Now use this new variable for the fill =. This will make labels in legend as you need. With argument breaks= in the scale_fill_manual() you cat set levels that you need to show in legend but remove the argument labels =. Both argument can be used only if they are the same lengths.

ggplot(training_results.barplot, mapping = aes(x = name, y = wer, fill = a2))  + 
  geom_bar(stat = "identity") +
  scale_fill_manual(breaks = c("Best", "Suggested", "Worst"),
                    values = c("#555555", "#777777", "#555555", "#777777", 
                            "#555555", "green", "orange", "red")) 

这是用于此答案的数据:

Here is a data used for this answer:

training_results.barplot<-structure(list(a = c(1L, 2L, 1L, 8L, 3L, 4L, 5L, 6L, 7L, 1L, 
1L, 1L), b = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L
), c = c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L), name = structure(1:12, .Label = c("1+1+1", 
"1+1+2", "1+1+3", "1+1+4", "1+1+5", "1+2+1", "1+2+2", "1+2+3", 
"1+2+4", "1+2+5", "1+3+1", "1+3+2"), class = "factor"), corr = c(66.63, 
66.66, 66.81, 66.57, 66.89, 66.63, 66.82, 66.74, 67, 66.9, 66.68, 
66.76), acc = c(59.15, 59.29, 59.42, 59.08, 59.34, 59.1, 59.45, 
59.31, 59.5, 59.19, 59.16, 59.23), H = c(4167L, 4169L, 4178L, 
4163L, 4183L, 4167L, 4179L, 4174L, 4190L, 4184L, 4170L, 4175L
), D = c(238L, 235L, 226L, 223L, 226L, 240L, 228L, 225L, 226L, 
230L, 227L, 226L), S = c(1849L, 1850L, 1850L, 1868L, 1845L, 1847L, 
1847L, 1855L, 1838L, 1840L, 1857L, 1853L), I = c(468L, 461L, 
462L, 468L, 472L, 471L, 461L, 465L, 469L, 482L, 470L, 471L), 
    N = c(6254L, 6254L, 6254L, 6254L, 6254L, 6254L, 6254L, 6254L, 
    6254L, 6254L, 6254L, 6254L), wer = c(40.85, 40.71, 40.58, 
    40.92, 40.66, 40.9, 40.55, 40.69, 40.5, 40.81, 40.84, 40.77
    )), .Names = c("a", "b", "c", "name", "corr", "acc", "H", 
"D", "S", "I", "N", "wer"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12"))

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