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geom_vlines每个绘图的多个vlines

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我怎样才能让ggplot产生像
Example
这样的东西

library(ggplot2)
library(reshape2)
library(ecp)

synthetic_control.data <- read.table("/path/synthetic_control.data.txt", quote="\"", comment.char="")
n <- 2

s <- sample(1:100, n)
idx <- c(s, 100+s, 200+s, 300+s, 400+s, 500+s)
sample2 <- synthetic_control.data[idx,]
df = as.data.frame(t(as.matrix(sample2)))

#calculate the change points
changeP <- e.divisive(as.matrix(df[1]), k=8, R = 400, alpha = 2, min.size = 3)
changeP = changeP$estimates
changeP = changeP[-c(1,length(changeP))]

changePoints = data.frame(changeP,variable=colnames(df)[1])
for(series in 2:ncol(df)){
  changeP <- e.divisive(as.matrix(df[series]), k=8, R = 400, alpha = 2, min.size = 3)
  changeP = changeP$estimates
  changeP = changeP[-c(1,length(changeP))]
  changePoints = rbind(changePoints, data.frame(changeP,variable=colnames(df)[2]))
}

这是关于情节的有趣部分：

df $ id = 1：nrow（df）dfMelt < - reshape2 :: melt（df，id.vars =“id”）p = ggplot（dfMelt，aes（x = id，y = value））geom_line（color =“ steelblue“）facet_grid（变量〜 . ，scale ='free_y'）p geom_vline（aes（xintercept = changeP），data = changePoints，linetype ='dashed'）

到目前为止我的结果是：https://www.dropbox.com/s/mysadkruo946oox/changePoint.pdf这意味着我的数组传递给 geom_vlines 有问题 .

你能指出我正确的方向，为什么我只能在前两个地块得到 vlines ？

r ggplot2 time-series timeserieschart

1 回答

  • 0

    这是解决方案：

    library(ggplot2)
library(reshape2)
library(ecp)

synthetic_control.data <- read.table("/Users/geoHeil/Dropbox/6.Semester/BachelorThesis/rResearch/data/synthetic_control.data.txt", quote="\"", comment.char="")
n <- 2

s <- sample(1:100, n)
idx <- c(s, 100+s, 200+s, 300+s, 400+s, 500+s)
sample2 <- synthetic_control.data[idx,]
df = as.data.frame(t(as.matrix(sample2)))

#calculate the change points
changeP <- e.divisive(as.matrix(df[1]), k=8, R = 400, alpha = 2, min.size = 3)
changeP = changeP$estimates
changeP = changeP[-c(1,length(changeP))]

changePoints = data.frame(changeP,variable=colnames(df)[1])
for(series in 2:ncol(df)){
  changeP <- e.divisive(as.matrix(df[series]), k=8, R = 400, alpha = 2, min.size = 3)
  changeP = changeP$estimates
  changeP = changeP[-c(1,length(changeP))]
  changePoints = rbind(changePoints, data.frame(changeP,variable=colnames(df)[series]))
}

# plot
df$id = 1:nrow(df)
dfMelt <- reshape2::melt(df, id.vars = "id")
p = ggplot(dfMelt,aes(x=id,y=value))+geom_line(color = "steelblue")+ facet_grid(variable ~ ., scales = 'free_y')
p + geom_vline(aes(xintercept=changeP), data=changePoints, linetype='dashed', colour='darkgreen')
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