Question

我已遵循以下问题的答案：Tukey test results on geom_boxplot with facet_grid

太好了，但是我也想比较它们之间的方面。换句话说，首先对所有结果进行字母排序，然后将其划分为多个方面（我同时拥有水平和垂直方面）。我怎样才能做到这一点？另外，如何重新排序字母，使其从第一个方面的第一个变量的“ a”开始，然后从第二个变量的“ b”开始，依此类推？我尝试了以下操作，但由于无法订购而无法正常工作。

TUKEY <- TukeyHSD(ANOVA, ordered = TRUE)

这是可复制的代码（用于生成图的代码是从上面的链接中获取的），数据是从此链接中获取的（http://sape.inf.usi.ch/quick-reference/ggplot2/facet）

d=expand.grid(obs=0:10, benchmark=c('antlr', 'bloat', 'chart'), gc=c('CopyMS', 'GenCopy', 'GenImmix'), opt=c('on', 'off', 'valid'), heapSize=seq(from=1.5, to=4, by=0.5))
d$time = rexp(nrow(d), 0.01)+1000
d$time = d$time + abs(d$heapSize-3)*100
d$time[d$opt=='on'] = d$time[d$opt=='on']-200

d$time[d$opt=='on' & d$benchmark=='bloat'] = d$time[d$opt=='on' & d$benchmark=='bloat'] + 190

generate_label_df <- function(TUKEY, variable){

  # Extract labels and factor levels from Tukey post-hoc 
  Tukey.levels <- variable[,4]
  Tukey.labels <- data.frame(multcompLetters(Tukey.levels)['Letters'])

  #I need to put the labels in the same order as in the boxplot :
  Tukey.labels$treatment=rownames(Tukey.labels)
  Tukey.labels=Tukey.labels[order(Tukey.labels$treatment) , ]
  return(Tukey.labels)
}


TUKEYplot <- function(df){

  p<-ggplot(data=df)+
    aes(x = opt, y = time, colour = opt) +
    geom_boxplot() +
    facet_grid(gc~benchmark) +
    theme_linedraw() +
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    ylim(min(df$time),max(df$time)+0.05) +
    labs(x = "type", y= "time", color = "state") +
    theme(strip.background = element_rect(colour = "black", fill = "white")) +
    theme(strip.text = element_text(colour = "black", size=12)) +
    theme(axis.text=element_text(size=12)) +
    theme(legend.text=element_text(size=12)) +
    theme(legend.title=element_text(size=12,face="bold")) +
    theme(axis.title=element_text(size=14,face="bold")) +
    scale_color_npg()
  for (facetk2 in as.character(unique(df$gc))) {   
    for (facetk in as.character(unique(df$benchmark))) {   
      subdf <- subset(df, df$benchmark==facetk & df$gc==facetk2)
      model=lm(time ~ opt, data=subdf)
      ANOVA=aov(model)
      # Tukey test to study each pair of treatment :
      TUKEY <- TukeyHSD(ANOVA)
      print(TUKEY)
      labels <- generate_label_df(TUKEY , TUKEY$`opt`)
      names(labels) <- c('Letters', 'opt')
      yvalue <- aggregate(.~opt, data=subdf, quantile, probs=.75)  
      final <- merge(labels, yvalue)
      final$benchmark <-  facetk
      final$gc <-  facetk2

      p <- p + geom_text(data = final,  aes(x=opt, y=time, label=Letters), 
                         vjust=-1.2, hjust=-.5, show.legend = FALSE, size=5)
    }
  }
  return (p)
}

p1<-TUKEYplot(d)
p1

更新：视觉帮助：

原始图：

Original

所需的部分情节：

Partial update

Answer 1

我终于想出了办法，所以我发布了答案！基本上，将Tukey的计算从循环中移出，在交互上使用ANOVA并在允许的情况下应用Tukey。然后将标签分成几列（确保您的数据不包含“：”，如果包含，则可以使用重值），然后将其遍历数据级别。

TUKEYplot <- function(df){

  p<-ggplot(data=df)+
    aes(x = opt, y = time, colour = opt) +
    geom_boxplot() +
    facet_grid(gc~benchmark) +
    theme_linedraw() +
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    ylim(min(df$time),max(df$time)+0.05) +
    labs(x = "type", y= "time", color = "state") +
    theme(strip.background = element_rect(colour = "black", fill = "white")) +
    theme(strip.text = element_text(colour = "black", size=12)) +
    theme(axis.text=element_text(size=12)) +
    theme(legend.text=element_text(size=12)) +
    theme(legend.title=element_text(size=12,face="bold")) +
    theme(axis.title=element_text(size=14,face="bold")) +
    scale_color_npg()

  model=lm(time ~ gc*benchmark*opt, data=df)
  ANOVA=aov(model)
  # Tukey test to study each pair of treatment :
  TUKEY <- TukeyHSD(ANOVA)
  all_labels <- generate_label_df(TUKEY , TUKEY$`gc:benchmark:opt`)
  sep_labels<- all_labels %>% separate(col=treatment, into= c("gc", "benchmark", "opt"), sep=":")

  for (facetk2 in as.character(unique(df$gc))) {   
    for (facetk in as.character(unique(df$benchmark))) {   
      subdf <- subset(df, df$benchmark==facetk & df$gc==facetk2)
      labels <- subset(sep_labels, sep_labels$benchmark==facetk & sep_labels$gc==facetk2)
      labels <- subset(labels, select = -c(gc,benchmark))

      names(labels) <- c('Letters', 'opt')
      yvalue <- aggregate(.~opt, data=subdf, quantile, probs=.75)  
      final <- merge(labels, yvalue)
      final$benchmark <-  facetk
      final$gc <-  facetk2

      p <- p + geom_text(data = final,  aes(x=opt, y=time, label=Letters), 
                         vjust=-1.2, hjust=-.5, show.legend = FALSE, size=5)
    }
  }
  return (p)
}

生成的图像：（由于我的信誉不足，所以无法嵌入图像。）

Result

ggplot上Tukey字母图的各个方面一致的字母

1 个答案: