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我正在尝试创建一个框架来轻松绘制我们的数据集。当前的想法是启动一个ggplot图形，向其中添加图层，然后显示或保存它。我的代码如下所示：

initPlot <- function(title = "", data = NULL){
    if(is.null(data)) data <- GLOBDATA
    plot <- ggplot(data, aes(jahr))
    plot <- plot + scale_x_continuous(breaks = seq(2001, 2012, 1))
    textTheme <- element_text(size=6, face="plain", color="black", family="AvantGarde")
    lineTheme <- element_line(color="black", size=0)
    plot <- plot + theme(
        text = textTheme, 
        axis.text  = textTheme, 
        axis.ticks = lineTheme,
        axis.line  = lineTheme,
        axis.title = element_blank(),
        plot.background = element_rect(fill="#f0f0f0"),
        strip.background = element_rect(fill="#f0f0f0"),
        panel.background = element_rect(fill="#f0f0f0"),
        panel.grid = element_blank(),
        legend.position = "bottom"
    )
    plot <- plot + guides(color = guide_legend(title = title))
    PLOTGLOB <<- plot
    plot
}

plotConfidence <- function(columns, color = "red", title = "", label = "", plot = NULL){
    plot <- plotLine(columns, "black", label, plot, 1)
    plot <- plot + geom_ribbon(columns, alpha = 0.3, fill = color, linetype=0)
    PLOTGLOB <<- plot
    plot
}

plotLine <- function(column, color = "black", label = "", plot = NULL, size = 1){
    if(is.null(plot)) plot <- PLOTGLOB
    plot <- plot + geom_line(column, color = color, size = size)
    PLOTGLOB <<- plot
    plot
}

然后我这样调用我的代码：

initPlot("title")
plotConfidence( 
    aes(
        y = jSOEP_aqne_ip_fgt060_f_alle, 
        ymin = jSOEP_aqne_ip_lfgt060_f_alle, 
        ymax = jSOEP_aqne_ip_ufgt060_f_alle, color="Alle", fill="Alle"
    ),
    "red")
plotConfidence( 
    aes(
        y = jSOEP_aqne_ip_fgt060_f_mann, 
        ymin = jSOEP_aqne_ip_lfgt060_f_mann, 
        ymax = jSOEP_aqne_ip_ufgt060_f_mann, color="Männer", fill="Männer"
    ),
    "blue", , label="Männer")

这会产生以下图形：

在此处输入图像描述

如您所见，图例颜色与相应的 geom_ribbons 不匹配，实际上，两者都是“蓝色”颜色（通过暂时将 alpha 设置为 1 发现）。我该如何解决？

这是我要绘制的数据：

GLOBDATA <- structure(list(jSOEP_aqne_ip_fgt060_f_alle = c(0.117169998586178, 
0.122670002281666, 0.131659999489784, 0.132029995322227, 0.140119999647141, 
0.142869994044304, 0.136739999055862, 0.140990003943443, 0.146730005741119, 
0.149069994688034, 0.141920000314713, 0.142879992723465), jSOEP_aqne_ip_lfgt060_f_alle = c(0.114249996840954, 
0.119199998676777, 0.128110006451607, 0.12814000248909, 0.136230006814003, 
0.139119997620583, 0.132400006055832, 0.137409999966621, 0.142560005187988, 
0.14478999376297, 0.137840002775192, 0.138579994440079), jSOEP_aqne_ip_ufgt060_f_alle = c(0.120090000331402, 
0.126139998435974, 0.135220006108284, 0.135920003056526, 0.143999993801117, 
0.146630004048347, 0.141090005636215, 0.144580006599426, 0.15090000629425, 
0.153359994292259, 0.146009996533394, 0.147180005908012), jSOEP_aqne_ip_fgt060_f_mann = c(0.100199997425079, 
0.106820002198219, 0.117770001292229, 0.117349997162819, 0.126489996910095, 
0.130469992756844, 0.12601999938488, 0.127340003848076, 0.132960006594658, 
0.135379999876022, 0.132510006427765, 0.13782000541687), jSOEP_aqne_ip_lfgt060_f_mann = c(0.0951400026679039, 
0.101929999887943, 0.112829998135567, 0.112510003149509, 0.121720001101494, 
0.12372999638319, 0.120829999446869, 0.121650002896786, 0.127389997243881, 
0.128470003604889, 0.12533999979496, 0.131980001926422), jSOEP_aqne_ip_ufgt060_f_mann = c(0.105259999632835, 
0.111709997057915, 0.122720003128052, 0.122189998626709, 0.131270006299019, 
0.137209996581078, 0.131219998002052, 0.133019998669624, 0.138539999723434, 
0.142289996147156, 0.139679998159409, 0.143659994006157)), .Names = c("jSOEP_aqne_ip_fgt060_f_alle", 
"jSOEP_aqne_ip_lfgt060_f_alle", "jSOEP_aqne_ip_ufgt060_f_alle", 
"jSOEP_aqne_ip_fgt060_f_mann", "jSOEP_aqne_ip_lfgt060_f_mann", 
"jSOEP_aqne_ip_ufgt060_f_mann"))
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1 回答 1

1

感谢您分享您的数据。不幸的是，它没有运行。GlOBDATA是一个list结构，没有jahr其他遗漏。

该答案不会尝试创建通用功能或修改您的功能，但希望确实提出了另一种构建数据的方法。

通过重组数据，您可以将变量映射到颜色，这将自动生成legend.

library(ggplot2)    

# create dataframe from your list
temp <- do.call(cbind.data.frame, GLOBDATA)

# Change data format
# your data is organised in wide format as mean, upper CI, lower CI (i think) 
# for both 'alle' and 'mann'. By stacking these after renaming for consistent
# column names, we can then easily map aesthetics in ggplot.
# create a grouping variable (grp) to map aesthetics to.

df1 <- setNames(temp[grepl('alle', names(temp))], c('mn', 'lower', 'upper'))
df1$grp <- 'alle'
df2 <- setNames(temp[grepl('mann', names(temp))], c('mn', 'lower', 'upper'))
df2$grp <- 'mann'
df <- rbind(df1, df2)

# add year
df$year <- 2000 + seq(nrow(temp))

# plot
p <- ggplot(df, aes(x=year, y=mn , ymin=lower, ymax=upper, colour=grp, fill=grp)) + 
            geom_line(size = 1, colour="black") + 
            geom_ribbon(alpha = 0.3, linetype=0) + 
            scale_x_continuous(breaks = seq(2001, 2012, 1)) +
            scale_fill_manual(values=c('alle' = 'red', 'mann'='blue'))

p <- p + 
  theme(
  text = element_text(size=6, face="plain", color="black", family="AvantGarde"), 
  axis.text  = element_text(size=6, face="plain", color="black", family="AvantGarde"), 
  axis.ticks = element_line(color="black", size=0.5),
  axis.line  = element_line(color="black", size=0.5),
  axis.title = element_blank(),
  plot.background = element_rect(fill="#f0f0f0"),
  strip.background = element_rect(fill="#f0f0f0"),
  panel.background = element_rect(fill="#f0f0f0"),
  panel.grid = element_blank(),
  legend.position = "bottom",
  legend.title=element_blank()
  )

在此处输入图像描述

因此，通过稍微调整数据的组织方式和函数，您应该能够将变量映射到美学并自动生成图例。

于 2014-07-11T14:15:25.410 回答