计算在sapply中的迭代

我使用sapply和绘图。但我无法给我使用sapply绘制的每一行提供不同的颜色。有没有一种方法可以让我增加每次sapply一个变量被调用，使用该变量（变量）改变使用plot_colors [变量]颜色计算在sapply中的迭代

plot_colors <- c("blue","red","forestgreen","black") 
    sapply(unique(ab$region[ab$region]), FUN=graphplot, REG=ab, tl=z, num=num+1) 
    graphplot <- function(l, REG, tl, num) { 
      dl <- REG[REG$region == l, tl] 
      datel <- REG[REG$region == l, "date"] 
      dl <- cbind(as.numeric(rownames(REG[REG$region == l, ])), REG[REG$region == l, tl]) 
      lines(dl, type="l", pch=2, col=plot_colors[num]) 
      num <- num + 1 
    }

下面是完整的代码。

avg_data <- read.table("qes.tbl", header=T, sep=",") 
    avg_data 
    #  dl <- avg_data[avg_data$region == "prod", "AveElapsedTime"] 
      #datel <- avg_data[avg_data$region == "prod", "date"] 
    #Creating the graph pdf in the below path to give as a link in the mail 
    FL <- 20120631 
    file <- paste("graph", FL, "pdf", sep=".") 
    plot_colors <- c("blue","red","forestgreen","black") 
    pdf(file, height=4.5, width=9.5, onefile=TRUE) 
    graphplot <- function(l, REG, tl, num) { 
      dl <- REG[REG$region == l, tl] 
      datel <- REG[REG$region == l, "date"] 
      dl <- cbind(as.numeric(rownames(REG[REG$region == l, ])), REG[REG$region == l, tl]) 
      lines(dl, type="l", pch=2, col=plot_colors[num]) 
      num <- num + 1 
    } 
    drawGraph <- function(ab, y, z, s) { 
      #Creating X axis 
      x <- ab[ab$region == "Beta", z] 
      y <- ab[,1] 
      g_range <- range(0,x[!is.na(x)]) 
      plot(NA, type="l", col="orange", xlim= c(1, length(y)), ylim=g_range,axes=FALSE, ann=FALSE) 
      num=1 
      sapply(unique(ab$region[ab$region]), FUN=graphplot, REG=ab, tl=z, num) 
      box() 
      axis(1, at=1:length(y), lab=FALSE) 
      text(1:length(y), par("usr")[3] - 2, srt=45, adj=1.2, labels=y, xpd=T, cex=0.3) 
      scale <- s 
      axis(2, las=1, at=scale*0:g_range[2], cex.axis=0.3) 
      main_title<-as.expression(z) 
      #Caculationg Mean, Upper limit and lower limit using the below commands 
      MEANLIMIT <- seq(length=length(y), from=mean(x), by=0) 
      ULIMIT <- seq(length=length(y), from=mean(x) + 2.66*sum(abs(diff(x)))/length(x), by=0) 
      LLIMIT <- seq(length=length(y), from=mean(x) - 2.66*sum(abs(diff(x)))/length(x), by=0) 
      lines(MEANLIMIT, type="l", col="black") 
      lines(ULIMIT, type="l", pch=2, lty=2, col="grey") 
      lines(LLIMIT, type="l", pch=2, lty=2, col="black") 
      title(main=main_title, col.main="red", font.main=4) 
      title(xlab="Test Execution Date", col.lab=rgb(0,0.5,0)) 
      title(ylab="Millisecond", col.lab=rgb(0,0.5,0)) 
      legend("topright", g_range[2], main_title, cex=0.4, col=c("blue"), lty=1); 
    } 
    lab<-as.character(avg_data$date) 
    AET <- avg_data$AveElapsedTime 
    MTitle <- "AveElapsedTime" 
    #Creating graph for Average Elapsed time 
      drawGraph(avg_data, lab, MTitle, 5)

这里是qes.tbl ..

date,region,AveElapsedTime 
    5/1/2012,preprod,23 
    5/2/2012,prod,76 
    5/3/2012,Beta,34 
    5/4/2012,prod,30 
    5/5/2012,Beta,22 
    5/6/2012,preprod,32 
    5/7/2012,Beta,21 
    5/8/2012,prod,44 
    5/9/2012,preprod,45 
    5/10/2012,Beta,23 
    5/11/2012,prod,50 
    5/13/2012,Beta,26 
    5/14/2012,preprod,33 
    5/15/2012,Beta,75 
    5/16/2012,preprod,56 
    5/17/2012,Beta,32 
    5/18/2012,preprod,67 
    5/19/2012,prod,40 

    structure(list(date = structure(c(3, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 4, 5, 6, 7, 8, 9, 10), .Label = c("5/10/2012", "5/11/2012", "5/1/2012", "5/13/2012", "5/14/2012", "5/15/2012", "5/16/2012", "5/17/2012", "5/18/2012", "5/19/2012", "5/2/2012", "5/3/2012", "5/4/2012", "5/5/2012", "5/6/2012", "5/7/2012", "5/8/2012", "5/9/2012"), class = "factor"), region = structure(c(2, 3, 1, 3, 1, 2, 1, 3, 2, 1, 3, 1, 2, 1, 2, 1, 2, 3), .Label = c("Beta", "preprod", "prod"), class = "factor"), AveElapsedTime = c(23, 76, 34, 30, 22, 32, 21, 44, 45, 23, 50, 26, 33, 75, 56, 32, 67, 40)), .Names = c("date", "region", "AveElapsedTime"), class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18"))

来源

2012-07-12 Tamilan

发布一个可重复的版本，我可能会看看。我明白你不想使用ggplot，但你看过晶格而不是基础图形吗？ – Andrie 2012-07-12 10:29:59

不是粘贴数据，而是将'dput（qes.tbl）'的结果粘贴到您的问题中。如果你想让我解决这个问题，请重新制作它。如果我可以复制并粘贴你的代码，并且它在我的R会话中有效，我会看一看，否则我就继续前进。有关如何执行此操作的更多帮助，请参阅http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example。 – Andrie 2012-07-12 10:52:52

好，你正在取得进展。你只需要几步就可以重新制作。现在在'structure ...'之前添加'avg_data < - '，然后将它放在代码的顶部。然后开始一个干净的R会话，复制并粘贴你的代码。如果它正确运行（复制任何你想让我们看到的行为），那么我应该可以做到这一点。 – Andrie 2012-07-12 11:25:50

以下的想法可以用来

sapply(as.list(rep("w",20)),function(x){gsub("[^0-9]","",deparse(substitute(x)))})

得到一个指数

或者您可以使用mapply

另一个例子

sapply(as.list(letters[1:20]),function(x){index<-gsub("[^0-9]","",deparse(substitute(x)));paste("i am index",index,"for letter",x)})

来源

2012-07-12 11:30:37 shhhhimhuntingrabbits

为什么不直接使用sapply（1:20，function（i）i）'？ – Andrie 2012-07-12 12:56:59

过分复杂，在我看来：'x < - letters [1:20]; sapply（seq_along（x），function（i）paste（“我是索引”，i，“为字母”，x [i]））'' – Andrie 2012-07-12 13:13:13

计算在sapply中的迭代

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