2017-04-24 59 views
0

我已經成功運行breakout函數,使用breakoutDetection包中的r。這個函數的一個可能的產品是$ plot。在運行breakout之後,是否有可能將多個嵌入列表中的圖組合在一起?我試過par()函數沒有成功。在我用ggplot重現時間序列之前有什麼想法? (基於其他數據)將多個分支圖組合在一起[r]

require(BreakoutDetection) 
df.date = c("01-01-2017", "02-01-2017", "03-01-2017", "04-01-2017", "05-01-2017", "06-01-2017", "07-01-2017", "08-01-2017", "09-01-2017", "10-01-2017") 
df.values = c(1,2,1,1,3,22,34,45,22, 10) 
ts = data.frame(df.date, df.values) 
ts.b = breakout(ts$df.values, min.size=3, method='multi', beta=.008, degree=1, plot=TRUE, xlab = "time") 
ts.b$plot 

欲能夠結合ts.b$plot元件與其他情節一起在AA 2×2矩陣或其他3 * 1矩陣...中:

重現的實例此外,我要重命名的x軸顯示的日期,不是整數(按時間序列的大小)

+0

嘗試提供[重複的例子(http://stackoverflow.com/questions/5963269/how-to-make-a-帶有示例輸入數據和代碼的偉大再現性示例),以便我們可以看到您正在嘗試執行的操作。 – MrFlick

回答

0

如果你去看看the source code of this package,它只是用ggplot2繪製在突圍檢測輸出的df與事。

這裏是下面的代碼工作的例子

# your code 
require(BreakoutDetection) 
df.date = c("01-01-2017", "02-01-2017", "03-01-2017", "04-01-2017", "05-01-2017", "06-01-2017", "07-01-2017", "08-01-2017", "09-01-2017", "10-01-2017") 
df.values = c(1,2,1,1,3,22,34,45,22, 10) 
ts = data.frame(df.date, df.values) 
ts.b = breakout(ts$df.values, min.size=3, method='multi', beta=.008, degree=1, plot=TRUE, xlab = "time") 
ts.b$plot 



# start: 
library(ggplot2) 

# the code in this function is copied from the source code of breakout detection (with small adjustment) 
# you can adjust things 
plot_breakout_detection = function(Z, retList, dateTime = T, x_lab = '', y_lab = '', title0 = ''){ 

    if(class(Z)%in%c('numeric','integer') || ncol(Z) == 1){ 
     dateTime = F 
     Z = data.frame(timestamp=1:length(Z), count = Z) 
    } 


    g = ggplot2::ggplot(Z, ggplot2::aes(x=timestamp, y=count)) + ggplot2::theme_bw() + 
     ggplot2::theme(panel.grid.minor=ggplot2::element_blank(), panel.grid.major=ggplot2::element_blank()) 


    g = g + ggplot2::xlab(x_lab) + ggplot2::ylab(y_lab) + ggplot2::ggtitle(title0) 

    g = g + ggplot2::geom_line() 

    if(!is.null(retList$loc)&& length(retList$loc)>0){ 
     v = retList$loc 
     v = c(0,v) 
     for(j in 2:length(v)){ 
      M = mean(Z$count[(v[j-1]+1):v[j]]) 
      df2 = data.frame(Z$timestamp[v[j]], Z$timestamp[v[j]], -Inf, M) 
      names(df2) = c('x','xend','y','yend') 
      g = g + ggplot2::geom_segment(data=df2,ggplot2::aes(x=x,y=y,xend=xend,yend=yend,color='2'),linetype=2,size=1.2) 
      g = g + ggplot2::guides(color=FALSE) 
     } 
    } 

    if(dateTime){ 
     g = g + scale_x_datetime(expand=c(0,0)) + scale_y_continuous(expand=c(0,0)) 
    } else { 
     g = g + scale_x_continuous(expand=c(0,0)) + scale_y_continuous(expand=c(0,0)) 
    } 

} 



df = data.frame(timestamp = as.POSIXct(df.date, format = '%m-%d-%Y'), count = df.values) 
g = plot_breakout_detection(df, ts.b) 
g 

enter image description here