R 基于相同组中的组和点的回归线颜色不'；在ggplot2中不匹配

我试图绘制一个图表，显示整个数据集的回归线（在我的例子中，不同品系雄性小鼠的血液学数据）以及单个品系的回归线。我看到了一篇类似的帖子（），但它并没有涉及回归线的颜色，所以它并没有真正的帮助。我给每个菌株分配了一种来自彩虹的颜色，以便在图表上区分它们。因此，理想情况下，应变点的颜色和该应变回归线的颜色应该匹配

编辑：很抱歉，Jaap，我删除了所有的ML$，并且我得到了找不到的变量的错误。我添加了data=ML，但仍然不起作用。另外，当我添加group=Color时，颜色仍然是错误的。 这是原始数据ML：

ML <- structure(list(Strain = structure(c(15L, 15L, 15L, 15L, 33L, 
33L, 33L, 33L, 33L, 33L, 33L, 33L, 17L, 17L, 17L, 17L, 18L, 18L, 
18L, 9L, 9L, 9L, 35L, 35L, 35L, 35L, 28L, 28L, 28L, 28L, 2L, 
2L, 2L, 2L, 1L, 1L, 1L, 1L, 12L, 12L, 12L, 12L, 23L, 23L, 23L, 
21L, 21L, 21L, 8L, 8L, 8L, 8L, 22L, 22L, 22L, 11L, 11L, 11L, 
11L, 13L, 13L, 13L, 13L, 3L, 3L, 3L, 3L, 14L, 14L, 14L, 22L, 
22L, 22L, 22L, 29L, 29L, 29L, 29L, 32L, 32L, 32L, 32L, 21L, 21L, 
21L, 21L, 24L, 24L, 24L, 24L, 16L, 16L, 16L, 3L, 3L, 3L, 3L, 
6L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 6L, 6L, 14L, 14L, 14L, 
14L, 31L, 31L, 20L, 20L, 26L, 26L, 26L, 26L, 4L, 4L, 4L, 5L, 
18L, 18L, 18L, 18L, 23L, 23L, 23L, 23L, 27L, 27L, 8L, 8L, 29L, 
29L, 29L, 29L, 17L, 17L, 34L, 27L, 27L, 27L, 27L, 9L, 9L, 9L, 
9L, 10L, 10L, 10L, 10L, 6L, 6L, 6L, 4L, 4L, 7L, 7L, 7L, 7L, 20L, 
20L, 20L, 20L, 25L, 25L, 25L, 25L, 30L, 30L, 30L, 30L, 19L, 19L, 
19L, 19L), .Label = c("129X1/SvJ", "A/J", "AXB10/PgnJ", "AXB13/PgnJ", 
"AXB15/PgnJ", "AXB19a/PgnJ", "AXB4/PgnJ", "AXB8/PgnJ", "BALB/cByJ", 
"BALB/cJ", "BTBRT+tf/J", "BXA1/PgnJ", "BXA12/PgnJ", "BXA13/PgnJ", 
"BXA14/PgnJ", "BXA16/PgnJ", "BXA4/PgnJ", "BXA8/PgnJ", "BXD40/TyJ", 
"BXD5/TyJ", "BXD75/RwwJ", "BXH10/TyJ", "BXH14/TyJ", "BXH8/TyJ", 
"C3H/HeJ", "C57BL/6J", "C58/J", "CXB12/HiAJ", "CXB2/ByJ", "DBA/2J", 
"LP/J", "NOD/ShiL_+J", "NOR/LtJ", "NZB/BINJ", "SJL/J"), class = "factor"), 
    Color = structure(c(9L, 9L, 9L, 9L, 28L, 28L, 28L, 28L, 28L, 
    28L, 28L, 28L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 20L, 20L, 
    20L, 26L, 26L, 26L, 26L, 19L, 19L, 19L, 19L, 31L, 31L, 31L, 
    31L, 25L, 25L, 25L, 25L, 14L, 14L, 14L, 14L, 2L, 2L, 2L, 
    4L, 4L, 4L, 22L, 22L, 22L, 22L, 3L, 3L, 3L, 16L, 16L, 16L, 
    16L, 7L, 7L, 7L, 7L, 32L, 32L, 32L, 32L, 8L, 8L, 8L, 3L, 
    3L, 3L, 3L, 21L, 21L, 21L, 21L, 29L, 29L, 29L, 29L, 4L, 4L, 
    4L, 4L, 1L, 1L, 1L, 1L, 10L, 10L, 10L, 32L, 32L, 32L, 32L, 
    35L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 35L, 35L, 8L, 8L, 8L, 
    8L, 30L, 30L, 5L, 5L, 15L, 15L, 15L, 15L, 33L, 33L, 33L, 
    34L, 12L, 12L, 12L, 12L, 2L, 2L, 2L, 2L, 17L, 17L, 22L, 22L, 
    21L, 21L, 21L, 21L, 11L, 11L, 27L, 17L, 17L, 17L, 17L, 20L, 
    20L, 20L, 20L, 18L, 18L, 18L, 18L, 35L, 35L, 35L, 33L, 33L, 
    24L, 24L, 24L, 24L, 5L, 5L, 5L, 5L, 13L, 13L, 13L, 13L, 23L, 
    23L, 23L, 23L, 6L, 6L, 6L, 6L), .Label = c("#000FFFFF", "#003AFFFF", 
    "#0066FFFF", "#0092FFFF", "#00BDFFFF", "#00E9FFFF", "#00FF0FFF", 
    "#00FF3AFF", "#00FF66FF", "#00FF92FF", "#00FFBDFF", "#00FFE9FF", 
    "#1D00FFFF", "#1DFF00FF", "#4900FFFF", "#49FF00FF", "#7500FFFF", 
    "#75FF00FF", "#A000FFFF", "#A0FF00FF", "#CC00FFFF", "#CCFF00FF", 
    "#F800FFFF", "#F8FF00FF", "#FF0000FF", "#FF002CFF", "#FF0057FF", 
    "#FF0083FF", "#FF00AFFF", "#FF00DBFF", "#FF2C00FF", "#FF5700FF", 
    "#FF8300FF", "#FFAF00FF", "#FFDB00FF"), class = "factor"), 
    y = c(48.4, 48.3, 49.9, 47.4, 48, 43, 41.6, 41.5, 43.4, 42.7, 
    42.3, 42.6, 54.2, 58.8, 60.1, 56.8, 41.6, 43.1, 43.1, 51.5, 
    54.2, 50.6, 46.2, 57, 52.1, 51.1, 59.8, 65.9, 58.8, 58.1, 
    54.6, 52.3, 53.9, 54.6, 51.8, 53.8, 60.5, 50.8, 41.7, 40.2, 
    40.6, 38.8, 47.6, 48.8, 46.9, 50.8, 48.5, 49.1, 39.4, 41.4, 
    41.1, 40.2, 43.6, 39.3, 45.2, 47.8, 59, 60.3, 45.8, 38.8, 
    39.1, 39.9, 40, 48.3, 49.5, 46.3, 45.6, 58.8, 57.7, 59.3, 
    56.1, 54.3, 46.6, 42.4, 47.9, 46.2, 43.9, 47.9, 61.3, 50.3, 
    49.1, 58.1, 47, 44.9, 48.1, 51.9, 58.9, 56.3, 61.9, 58.2, 
    50, 52.2, 45.9, 44.2, 47.2, 48.5, 44.8, 41.6, 46.1, 43.9, 
    49.5, 49.4, 50.7, 47.6, 48, 41.5, 39.9, 59.7, 59.1, 58, 57.4, 
    48.7, 55.4, 43.5, 46.4, 41.2, 45.5, 39.3, 47.3, 51.9, 48.8, 
    56.7, 51, 42.5, 41.6, 40.6, 41.5, 48.8, 47.9, 48.9, 47, 40.4, 
    41.7, 39.8, 41.6, 50.9, 46.6, 49.9, 45.3, 52.4, 59.6, 54.7, 
    39.5, 42.8, 39.9, 40.9, 54.3, 53.8, 53.6, 54.8, 53.6, 56.7, 
    56.7, 54.1, NA, NA, NA, NA, NA, 47.8, 51.6, 46.7, 47.5, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
    ), x = c(26.6, 29.4, 26.8, 22.9, 9.5, 7.8, 5.6, 7.8, 9.1, 
    8.3, 8.3, 6.8, 24.9, 29, 30.7, 46.2, 26.7, 29.6, 25.5, 29.5, 
    34, 44.8, 6, 9.1, 7.2, 15.2, 44.1, 27.4, 43.5, 36.6, 37.5, 
    40, 34, 39.5, 25.3, 38, 25.8, 23.8, 22.9, 21.6, 16.4, 16.9, 
    28.1, 27.5, 36.2, 8.5, 17.9, 26.1, 13.9, 14.3, 27.6, 25.2, 
    26.4, 16, 17.5, 5, 6.6, 6.1, 3.9, 16.2, 17.5, 20.1, 13.4, 
    13.9, 18.6, 10.1, 11.7, 32.2, 35.9, 31.7, 19.8, 27.8, 17, 
    18.3, 36.2, 26.5, 20.6, 22.6, 11.3, 12.4, 7.4, 8.5, 16.2, 
    17.3, 19.7, 9.3, 20.3, 17.5, 44.9, 26.4, 21.4, 10.4, 13.6, 
    12.1, 20.6, 34.8, 5.5, 12.8, 18.3, 12.6, 18, 20.3, 19, 21.5, 
    17.1, 11.8, 10.6, 47, 45.5, 50.4, 46.4, 5.6, 6.1, 22.9, 21.7, 
    8.3, 9, 7.2, 11.2, 14.2, 12.8, 41.4, 10.4, 29.9, 17.2, 16.7, 
    20.9, 25.1, 17.1, 18.2, 11.2, 4.8, 7.4, 14.5, 13.5, 23.4, 
    19.1, 20, 18, 33.8, 15.8, 4.1, 7.2, 4.9, 5, 6, 40.3, 39.2, 
    25.8, 31.5, 48.2, 45.8, 43.3, 53.6, NA, NA, NA, NA, NA, 18.9, 
    18.5, 22, 24, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA)), .Names = c("Strain", "Color", "y", 
"x"), row.names = c(NA, -179L), class = "data.frame")

Here are the other variables that will be mentioned in my code.

#35, because there're 35 strains
#I did NameY and NameX since I was to put this thing into a loop to plot for may other variables   
MyRainbow <- rainbow(35)
NameY <- "MCV(fl)"
NameX <- "HCT(%)"

创建的图像：

以下是点具有正确颜色的代码，但是回归线的颜色与点的颜色不匹配，并且回归线的颜色与前面scinario中的颜色相同：

ggplot(ML, aes(y=y, x=x)) + 
  geom_point(na.rm=T, color=ML$Color) +
  geom_smooth(method="lm", na.rm=T, se=F, formula=y~x, aes(color=ML$Color)) +
  geom_smooth(method="lm", na.rm=T, se=T, formula=y~x, color="black", lwd=0.8) +
  scale_color_manual("Strain", values=MyRainbow, labels=ML$Strain, guide=F) +
  geom_text(x=(max(ML$x,na.rm=T)+min(ML$x,na.rm=T))/2, y=max(ML$y, na.rm=T), label=lm_eqn(ML), size=4, parse=T) +
  labs(x=paste(NameX), y=paste(NameY))

可在此处找到生成的图像：

那么当我这样做的时候：

ggplot(ML, aes(y=y, x=x)) + 
  geom_point(na.rm=T, color=ML$Color) +
  geom_smooth(method="lm", na.rm=T, se=F, formula=y~x, color=ML$Color) +
  geom_smooth(method="lm", na.rm=T, se=T, formula=y~x, color="black", lwd=0.8) +
  scale_color_manual("Strain", values=MyRainbow, labels=ML$Strain, guide=F) +
  geom_text(x=(max(ML$x,na.rm=T)+min(ML$x,na.rm=T))/2, y=max(ML$y, na.rm=T), label=lm_eqn(ML), size=4, parse=T) +
  labs(x=paste(NameX), y=paste(NameY))

我得到一个错误：设置美学：颜色的长度不兼容 这里怎么了？如何将回归线转换为正确的颜色

---

非常感谢你的帮助

使用您在问题中提供的数据（以及绘图下方的代码）

---

没有数据是很难帮助的！几点：1）您可以从

ggplot

代码中删除

ML$

部分，它们是不必要的。2） 您可以尝试添加

group=Color

是否会产生不同的结果。3） 请添加一些示例数据（按照链接获取有关如何操作的一些说明）。@Jaap是正确的。请勿在

aes

内部使用

$

。这可能是你的全部问题。对不起，Eric，我可以让线条的颜色与点的颜色匹配，但我进一步的问题是，它不是我在数据框中用名为color的变量指定的颜色，而是ggplot2指定的颜色。我明白了，你可以与

dput（）共享某个日期吗

？如果您有机会使用

dput（）

共享您的数据，则可以更轻松地获取数据。好的，感谢您的耐心等待。现在，我已经将

dput（）。
ggplot(ML, aes(y=y, x=x)) + 
  geom_point(na.rm=T, color=ML$Color) +
  geom_smooth(method="lm", na.rm=T, se=F, formula=y~x, color=ML$Color) +
  geom_smooth(method="lm", na.rm=T, se=T, formula=y~x, color="black", lwd=0.8) +
  scale_color_manual("Strain", values=MyRainbow, labels=ML$Strain, guide=F) +
  geom_text(x=(max(ML$x,na.rm=T)+min(ML$x,na.rm=T))/2, y=max(ML$y, na.rm=T), label=lm_eqn(ML), size=4, parse=T) +
  labs(x=paste(NameX), y=paste(NameY))

# create new dataset without missing data
df.ML <- na.omit(ML) 

ggplot(df.ML,aes(y = y, x = x)) +
     geom_point(aes(colour = Strain), size = 1, alpha = .8) + 
     guides(col = guide_legend(nrow = 16)) +
     geom_smooth(method="lm", se= F, aes(colour = Strain, group = Strain)) +
     geom_smooth(method = 'lm', colour = 'black', se = T)  +
     scale_colour_manual(values = df.ML$Color)

set.seed(1)
library(plyr)
alldata <- ddply(data.frame(group = letters[1:5], x = rnorm(50)), 'group', 
                 mutate, y=runif(1,-1,1) * x +rnorm(10))
library(ggplot2)
ggplot(alldata,aes(y = y, x = x)) +
     geom_point(aes(colour = group, shape = group), size = 3, alpha = .8) + 
     geom_smooth(method="lm", se= F, size = 1, aes(linetype = group, colour = group, group = group)) +
     geom_smooth(method = 'lm',size = 1, colour = 'black', se = F) + theme_bw()