箱线图在 R 中没有正确着色或绘制标签,为什么?
Boxplots aren't colouring or plotting labels properly in R, why?
My Tukey 测试显着结果标签和绘制为箱线图的颜色不会绘制在每个样本箱线图上。为什么?
似乎标签是沿着相同的 s1(x 轴)在不同的 y 轴上绘制的?
此处可重现的数据集:
library(multcompView)
df <- data.frame('Sample'=c("s1","s1","s1","s1","s1","s2","s2","s2","s2","s2","s3","s3","s3","s3","s4","s4","s5","s5"), 'value'=c(-0.1098,-0.1435,-0.1046,-0.1308,-0.1523,-0.1219,-0.1114,-0.1328,-0.1589,-0.1567,-0.1395,-0.1181,-0.1448,-0.124,-0.1929,-0.1996,-0.1981,-0.1917))
anova_df <- aov(df$value ~ df$Sample )
tukey_df <- TukeyHSD(anova_df, 'df$Sample', conf.level=0.95)
# I need to group the treatments that are not different each other together.
TUKEY <- tukey_df
generate_label_df <- function(TUKEY, variable){
# Extract labels and factor levels from Tukey post-hoc
Tukey.levels <- TUKEY[[variable]][,4]
Tukey.labels <- data.frame(multcompLetters(Tukey.levels)['Letters'])
#I need to put the labels in the same order as in the boxplot :
Tukey.labels$Sample=rownames(Tukey.labels)
Tukey.labels=Tukey.labels[order(Tukey.labels$Sample) , ]
return(Tukey.labels)
}
# Apply the function on my dataset
LABELS <- generate_label_df(TUKEY , "df$Sample")
# A panel of colors to draw each group with the same color :
my_colors <- c(
rgb(143,199,74,maxColorValue = 255),
rgb(242,104,34,maxColorValue = 255),
rgb(111,145,202,maxColorValue = 255))
# Draw the basic boxplot
a <- boxplot(df$value ~ df$Sample , ylim=c(min(df$value) , 1.1*max(df$value)) , col=my_colors[as.numeric(LABELS[,1])] , ylab="Value" , main="")
# I want to write the letter over each box. Over is how high I want to write it.
over <- 0.1*max(a$stats[nrow(a$stats),] )
#Add the labels
text(c(1:nlevels(df$Sample)), a$stats[nrow(a$stats),]+over, LABELS[,1] , col=my_colors[as.numeric(LABELS[,1])] )
当前输出:
想要的情节(颜色和标签):
首先,LABELS$Letters
是一个字符向量。如果你先把它作为一个因素,你可以让 as.numeric(LABELS[,1])
工作。
其次,您的 y 限制需要为负值做一些工作。有一个你可能会觉得有用的函数叫做 extendrange
,它被用在许多绘图函数中。
如果 df$Sample
是一个因素,那么这一行 c(1:nlevels(df$Sample))
也可以工作。
此外,如果您在特定位置绘制 text
,您可以使用 text(..., pos = )
或 text(..., adj = )
调整文本以移动位置。
LABELS$Letters <- factor(LABELS$Letters)
a <- boxplot(df$value ~ df$Sample , ylim = extendrange(df$value), col=my_colors[as.numeric(LABELS[,1])] , ylab="Value" , main="")
text(seq_along(a$names), apply(a$stats, 2, max), LABELS[,1], col=my_colors[as.numeric(LABELS[,1])], pos = 3)
如果您不介意更改工作流程并使用 tidyverse
库,这就是您实现目标的方法:
# join df and LABELS into one data table
inner_join(df, LABELS, by = "Sample") %>%
# calculate max value for each Sample group (it will be used to place the labels)
group_by(Sample) %>%
mutate(placement = max(value)) %>%
ungroup() %>%
# make a plot
ggplot(aes(Sample, value, fill = Letters))+
geom_boxplot()+
geom_text(aes(y = placement, label = Letters, col = Letters), nudge_y = 0.01, size = 6)+
theme_minimal()+
theme(legend.position = "none")
My Tukey 测试显着结果标签和绘制为箱线图的颜色不会绘制在每个样本箱线图上。为什么? 似乎标签是沿着相同的 s1(x 轴)在不同的 y 轴上绘制的?
此处可重现的数据集:
library(multcompView)
df <- data.frame('Sample'=c("s1","s1","s1","s1","s1","s2","s2","s2","s2","s2","s3","s3","s3","s3","s4","s4","s5","s5"), 'value'=c(-0.1098,-0.1435,-0.1046,-0.1308,-0.1523,-0.1219,-0.1114,-0.1328,-0.1589,-0.1567,-0.1395,-0.1181,-0.1448,-0.124,-0.1929,-0.1996,-0.1981,-0.1917))
anova_df <- aov(df$value ~ df$Sample )
tukey_df <- TukeyHSD(anova_df, 'df$Sample', conf.level=0.95)
# I need to group the treatments that are not different each other together.
TUKEY <- tukey_df
generate_label_df <- function(TUKEY, variable){
# Extract labels and factor levels from Tukey post-hoc
Tukey.levels <- TUKEY[[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$Sample=rownames(Tukey.labels)
Tukey.labels=Tukey.labels[order(Tukey.labels$Sample) , ]
return(Tukey.labels)
}
# Apply the function on my dataset
LABELS <- generate_label_df(TUKEY , "df$Sample")
# A panel of colors to draw each group with the same color :
my_colors <- c(
rgb(143,199,74,maxColorValue = 255),
rgb(242,104,34,maxColorValue = 255),
rgb(111,145,202,maxColorValue = 255))
# Draw the basic boxplot
a <- boxplot(df$value ~ df$Sample , ylim=c(min(df$value) , 1.1*max(df$value)) , col=my_colors[as.numeric(LABELS[,1])] , ylab="Value" , main="")
# I want to write the letter over each box. Over is how high I want to write it.
over <- 0.1*max(a$stats[nrow(a$stats),] )
#Add the labels
text(c(1:nlevels(df$Sample)), a$stats[nrow(a$stats),]+over, LABELS[,1] , col=my_colors[as.numeric(LABELS[,1])] )
当前输出:
想要的情节(颜色和标签):
首先,LABELS$Letters
是一个字符向量。如果你先把它作为一个因素,你可以让 as.numeric(LABELS[,1])
工作。
其次,您的 y 限制需要为负值做一些工作。有一个你可能会觉得有用的函数叫做 extendrange
,它被用在许多绘图函数中。
如果 df$Sample
是一个因素,那么这一行 c(1:nlevels(df$Sample))
也可以工作。
此外,如果您在特定位置绘制 text
,您可以使用 text(..., pos = )
或 text(..., adj = )
调整文本以移动位置。
LABELS$Letters <- factor(LABELS$Letters)
a <- boxplot(df$value ~ df$Sample , ylim = extendrange(df$value), col=my_colors[as.numeric(LABELS[,1])] , ylab="Value" , main="")
text(seq_along(a$names), apply(a$stats, 2, max), LABELS[,1], col=my_colors[as.numeric(LABELS[,1])], pos = 3)
如果您不介意更改工作流程并使用 tidyverse
库,这就是您实现目标的方法:
# join df and LABELS into one data table
inner_join(df, LABELS, by = "Sample") %>%
# calculate max value for each Sample group (it will be used to place the labels)
group_by(Sample) %>%
mutate(placement = max(value)) %>%
ungroup() %>%
# make a plot
ggplot(aes(Sample, value, fill = Letters))+
geom_boxplot()+
geom_text(aes(y = placement, label = Letters, col = Letters), nudge_y = 0.01, size = 6)+
theme_minimal()+
theme(legend.position = "none")