Question

我的问题类似于Fill region between two loess-smoothed lines in R with ggplot 1

但我有两组。

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我想为每个组填充红色和蓝色。

我试过了：

g1<-ggplot(NVIQ_predict,aes(cogn.age, predict, color=as.factor(NVIQ_predict$group)))+
    geom_smooth(aes(x = cogn.age, y = upper,group=group),se=F)+
    geom_line(aes(linetype = group), size = 0.8)+
    geom_smooth(aes(x = cogn.age, y = lower,group=group),se=F)

但它给了我错误：美学必须是长度为1或与dataProblems相同的长度

每次我的geom_ribbon（）数据和ggplot（）数据不同时，我都会得到相同的错误。

有人可以帮我吗？非常感谢！

我的数据如下：

gg1 <- ggplot_build(g1)   
df2 <- data.frame(x = gg1$data[[1]]$x,
                  ymin = gg1$data[[1]]$y,
                  ymax = gg1$data[[3]]$y)     
g1 + geom_ribbon(data = df2, aes(x = x, ymin = ymin, ymax = ymax),fill = "grey", alpha = 0.4)

根据Gregor的说法，我试过inherit.aes = FALSE，错误消失了。但我的情节看起来像：

Answer 1

我们已经获得了所需的所有信息。现在我们只需要，哼，连接点; - ）

首先是输入数据：

NVIQ_predict <- read.table(text = "
                id  cogn.age  predict    upper    lower    group
                 1         7 39.04942  86.68497 18.00000     1
                 2         8 38.34993  82.29627 18.00000     1
                 3        10 37.05174  74.31657 18.00000     1
                 4        11 36.45297  70.72421 18.00000     1
                 5        12 35.88770  67.39555 18.00000     1
                 6        13 35.35587  64.32920 18.00000     1
                 7        14 34.85738  61.52322 18.00000     1
                 8        16 33.95991  56.68024 18.00000     1
                 9        17 33.56057  54.63537 18.00000     1
                 10       18 33.19388  52.83504 18.00000     1
                 11       19 32.85958  51.27380 18.00000     1
                 12       20 32.55752  49.94791 18.00000     1
                 13       21 32.28766  48.85631 18.00000     1
                 14       24 31.67593  47.09206 18.00000     1
                 15       25 31.53239  46.91136 18.00000     1
                 16       28 31.28740  48.01764 18.00000     1
                 17       32 31.36627  50.55201 18.00000     1
                 18       35 31.73386  53.19630 18.00000     1
                 19       36 31.91487  54.22624 18.00000     1
                 20       37 32.13026  55.25721 18.00000     1
                 21       38 32.38237  56.26713 18.00000     1
                 22       40 32.98499  58.36229 18.00000     1
                 23       44 34.59044  62.80187 18.00000     1
                 24       45 35.06804  64.01951 18.00000     1
                 25       46 35.57110  65.31888 18.00000     1
                 26       47 36.09880  66.64696 17.93800     1
                 27       48 36.72294  67.60053 17.97550     1
                 28       49 37.39182  68.49995 18.03062     1
                 29       50 38.10376  69.35728 18.10675     1
                 30       51 38.85760  70.17693 18.18661     1
                 31       52 39.65347  70.95875 18.27524     1
                 32       53 40.49156  71.70261 18.38020     1
                 33       54 41.35332  72.44006 17.90682     1
                 34       59 46.37849  74.91802 18.63206     1
                 35       60 47.53897  75.66218 19.64432     1
                 36       61 48.74697  76.43933 20.82346     1
                 37       63 51.30607  78.02426 23.73535     1
                 38       71 63.43129  86.05467 40.43482     1
                 39       72 65.15618  87.44794 42.72704     1
                 40       73 66.92714  88.95324 45.01966     1
                 41       84 89.42079 114.27939 68.03834     1
                 42       85 91.73831 117.44007 69.83676     1
                 43        7 33.69504  54.03695 15.74588     2
                 44        8 34.99931  53.96500 18.00533     2
                 45       10 37.61963  54.05684 22.43516     2
                 46       11 38.93493  54.21969 24.60049     2
                 47       12 40.25315  54.45963 26.73027     2
                 48       13 41.57397  54.77581 28.82348     2
                 49       14 42.89710  55.16727 30.87982     2
                 50       16 45.54954  56.17193 34.88453     2
                 51       17 46.87877  56.78325 36.83632     2
                 52       18 48.21025  57.46656 38.75807     2
                 53       19 49.54461  58.22266 40.65330     2
                 54       20 50.88313  59.05509 42.52505     2
                 55       21 52.22789  59.97318 44.36944     2
                 56       24 56.24397  63.21832 49.26963     2
                 57       25 57.55394  64.33850 50.76938     2
                 58       28 61.45282  68.05043 54.85522     2
                 59       32 66.44875  72.85234 60.04517     2
                 60       35 69.96560  76.06171 63.86949     2
                 61       36 71.09268  77.06821 65.11714     2
                 62       37 72.19743  78.04559 66.34927     2
                 63       38 73.28041  78.99518 67.56565     2
                 64       40 75.37861  80.81593 69.94129     2
                 65       44 79.29028  84.20275 74.37780     2
                 66       45 80.20272  85.00888 75.39656     2
                 67       46 81.08645  85.80180 76.37110     2
                 68       47 81.93696  86.57689 77.29704     2
                 69       48 82.75920  87.34100 78.17739     2
                 70       49 83.55055  88.09165 79.00945     2
                 71       50 84.30962  88.82357 79.79567     2
                 72       51 85.03743  89.53669 80.53817     2
                 73       52 85.73757  90.23223 81.24291     2
                 74       53 86.41419  90.91607 81.91232     2
                 75       54 87.05716  91.58632 82.52800     2
                 76       59 89.75923  94.58218 84.93629     2
                 77       60 90.18557  95.05573 85.31541     2
                 78       61 90.58166  95.51469 85.64864     2
                 79       63 91.27115  96.31107 86.23124     2
                 80       71 92.40983  98.35031 86.46934     2
                 81       72 92.36362  98.52258 86.20465     2
                 82       73 92.27734  98.67161 85.88308     2
                 83       84 88.66150  98.84699 78.47602     2
                 84       85 88.08846  98.73625 77.44067     2", header = TRUE)
NVIQ_predict$id <- NULL

确保group列是因子变量，因此我们可以将其用作线型。

NVIQ_predict$group <- as.factor(NVIQ_predict$group)

然后建立情节。

library(ggplot2)

g1 <- ggplot(NVIQ_predict, aes(cogn.age, predict, color=group)) + 
             geom_smooth(aes(x = cogn.age, y = upper, group=group), method = loess, se = FALSE) + 
             geom_smooth(aes(x = cogn.age, y = lower, group=group), method = loess, se = FALSE) +
             geom_line(aes(linetype = group), size = 0.8)

最后，提取组1和组2的曲线的(x,ymin)和(x,ymax)坐标。这些对具有相同的x坐标，因此连接这些点会模仿两条曲线之间的区域阴影。这在Fill region between two loess-smoothed lines in R with ggplot中有所解释。这里唯一的区别是我们需要更加谨慎地选择和连接属于正确曲线的点......

gp <- ggplot_build(g1)  

d1 <- gp$data[[1]]
d2 <- gp$data[[2]]

df1 <- data.frame(x    = d1[d1$group == 1,]$x,
                  ymin = d2[d2$group == 1,]$y,
                  ymax = d1[d1$group == 1,]$y)   

df2 <- data.frame(x    = d1[d1$group == 2,]$x,
                  ymin = d2[d2$group == 2,]$y,
                  ymax = d1[d1$group == 2,]$y)   

g1 + geom_ribbon(data = df1, aes(x = x, ymin = ymin, ymax = ymax), inherit.aes = FALSE, fill = "grey", alpha = 0.4) + 
     geom_ribbon(data = df2, aes(x = x, ymin = ymin, ymax = ymax), inherit.aes = FALSE, fill = "grey", alpha = 0.4)

结果如下：

geom_ribbon错误：美学必须是长度一

1 个答案: