geom_vlines每个plot有多个vlines

本文介绍了geom_vlines每个plot有多个vlines的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述 如何让ggplot产生类似于 的 library（ggplot2） library（reshape2） library（ecp） synthetic_control.data< - read.table（/ path / synthetic_control.data.txt，quote =\，comment.char =）n s idx sample2 df = as.data.frame（t（as.matrix（sample2））） ＃计算变化点 changeP< - e.divisive （as.matrix（df [1]），k = 8，R = 400，alpha = 2，min.size = 3） changeP = changeP $ estimated changeP = changeP [-c（1 ，length（changeP））] changePoints = data.frame（changeP，variable = colnames（df）[1]）$ ​​b $ b for（series in 2：ncol（df））{$ （as.matrix（df [series]），k = 8，R = 400，alpha = 2，min.size = 3） changeP = changeP $ estimated changeP = changeP [-c（1，leng （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 p = ggplot（dfMelt，aes（x = id，y = value））+ geom_line（color = $ $ b 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 时出错。 你能指出我在正确的方向，为什么我只在前两个图中获得 vlines ？ 解决方案这是解决方案： libr ary（ggplot2） library（reshape2） library（ecp） synthetic_control.data< - read.table（/ Users / geoHeil / Dropbox / 6.Semester /本科/研究/数据/ synthetic_control.data.txt，quote =\，comment.char =）n s idx sample2 df = as.data.frame（t（as.matrix（sample2））） ＃计算变化点 changeP< - e.divisive（as .matrix（df [1]），k = 8，R = 400，alpha = 2，min.size = 3） changeP = changeP $ estimated changeP = changeP [-c （changeP））] changePoints = data.frame（changeP，variable = colnames（df）[1]）$ ​​b $ b for（series in 2：ncol（df））{$ b $ （换言之，矩阵（df [系列]），k = 8，R = 400，α= 2，min.size = 3） changeP = changeP $估计 changeP = changeP [-c（1，length（changeP））] changePoints = rbind（changePoints，data.frame（changeP，variable = colnames（d f）[系列]））} ＃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'，color ='darkgreen'） How can I get ggplot to produce something similar likelibrary(ggplot2)library(reshape2)library(ecp)synthetic_control.data <- read.table("/path/synthetic_control.data.txt", quote="\"", comment.char="")n <- 2s <- 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 pointschangeP <- e.divisive(as.matrix(df[1]), k=8, R = 400, alpha = 2, min.size = 3)changeP = changeP$estimateschangeP = changeP[-c(1,length(changeP))]changePoints = data.frame(changeP,variable=colnames(df)[1])for(series in 2:ncol(df)){ changeP <- e.divisive(as.matrix(df[series]), k=8, R = 400, alpha = 2, min.size = 3) changeP = changeP$estimates changeP = changeP[-c(1,length(changeP))] changePoints = rbind(changePoints, data.frame(changeP,variable=colnames(df)[2]))}this is the interesting part about the plot:df$id = 1:nrow(df)dfMelt <- reshape2::melt(df, id.vars = "id")p = ggplot(dfMelt,aes(x=id,y=value))+geom_line(color = "steelblue")+ facet_grid(variable ~ ., scales = 'free_y')p + geom_vline(aes(xintercept=changeP), data=changePoints, linetype='dashed')So far my result is: https://www.dropbox.com/s/mysadkruo946oox/changePoint.pdf which means that there is something wrong with my array passed to the geom_vlines.Could you point me in the right direction why I only get vlines in the first 2 plots? 解决方案 This is the solution:library(ggplot2)library(reshape2)library(ecp)synthetic_control.data <- read.table("/Users/geoHeil/Dropbox/6.Semester/BachelorThesis/rResearch/data/synthetic_control.data.txt", quote="\"", comment.char="")n <- 2s <- sample(1:100, n)idx <- c(s, 100+s, 200+s, 300+s, 400+s, 500+s)sample2 <- synthetic_control.data[idx,]df = as.data.frame(t(as.matrix(sample2)))#calculate the change pointschangeP <- e.divisive(as.matrix(df[1]), k=8, R = 400, alpha = 2, min.size = 3)changeP = changeP$estimateschangeP = 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$estimates changeP = changeP[-c(1,length(changeP))] changePoints = rbind(changePoints, data.frame(changeP,variable=colnames(df)[series]))}# plotdf$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') 这篇关于geom_vlines每个plot有多个vlines的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！