R-一个绘图中有多个图形，但图形上重叠部分的透明度不起作用

我正在R中创建一些高度数据的频率/密度图。下面的代码用于在一个图中获得两个不同的变量，每个密度和频率。所以它总共有两个条形图和两条直线

问题是，条形图相互重叠，我无法使用“alpha”正确设置透明度。这是我需要帮助的地方。我想这是一个非常简单的问题

我已经在代码中的不同位置尝试了

alpha

函数，但它不起作用

hist(Lake_DF1[[6]], col=c("#006CFF"), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), xlab = "Height [m]", main = "DTLB 6")

lines(density(na.omit(Lake_DF1[[6]])), lwd = 2)

hist(Buffer_DF1[[6]], col = c("#FF9900", alpha=0.4), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), add=TRUE)

lines(density(na.omit(Buffer_DF1[[6]])), lwd = 2)

我能得到的唯一结果是第二个变量的条纹条，而不是透明条，见下图。我想让橙色的条透明，以看到蓝色的条和线通过。

---

考虑使用允许alpha参数的

？rgb

。此外，为了更好地进行颜色比较，请使用不同alpha值的相同颜色

蓝色

# CONVERSION: #006CFF --> rgb(0,108,255)
hist(Lake_DF1[[6]], col = rgb(0/255, 108/255, 255/255, 0.4), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), xlab = "Height [m]", main = "DTLB 6")

lines(density(na.omit(Lake_DF1[[6]])), lwd = 2)

hist(Buffer_DF1[[6]], col = rgb(0/255, 108/255, 255/255, 0.3), 
     border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), add=TRUE)

# CONVERSION: #FF9900 --> rgb(255,153,0)
hist(Lake_DF1[[6]], col = rgb(255/255, 153/255, 0/255, 0.4), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), xlab = "Height [m]", main = "DTLB 6")

lines(density(na.omit(Lake_DF1[[6]])), lwd = 2)

hist(Buffer_DF1[[6]], col = rgb(255/255, 153/255, 0/255, 0.3), 
     border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), add=TRUE)

lines(density(na.omit(Buffer_DF1[[6]])), lwd = 2)

---

橙色

# CONVERSION: #006CFF --> rgb(0,108,255)
hist(Lake_DF1[[6]], col = rgb(0/255, 108/255, 255/255, 0.4), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), xlab = "Height [m]", main = "DTLB 6")

lines(density(na.omit(Lake_DF1[[6]])), lwd = 2)

hist(Buffer_DF1[[6]], col = rgb(0/255, 108/255, 255/255, 0.3), 
     border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), add=TRUE)

# CONVERSION: #FF9900 --> rgb(255,153,0)
hist(Lake_DF1[[6]], col = rgb(255/255, 153/255, 0/255, 0.4), border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), xlab = "Height [m]", main = "DTLB 6")

lines(density(na.omit(Lake_DF1[[6]])), lwd = 2)

hist(Buffer_DF1[[6]], col = rgb(255/255, 153/255, 0/255, 0.3), 
     border = "black", prob = TRUE, 
     # show densities instead of frequencies
     breaks = 60, xlim = c(14,17), add=TRUE)

lines(density(na.omit(Buffer_DF1[[6]])), lwd = 2)

---

数据

set.seed(8302019)
data_tools <- c("sas", "stata", "spss", "python", "r", "julia")

#################
### DATA BUILD
#################
Lake_DF1 <- data.frame(
  group = sample(data_tools, 500, replace=TRUE),
  int = sample(1:15, 500, replace=TRUE),
  num1 = rnorm(500),
  num2 = runif(500),
  num3 = rnorm(500),
  num4 = runif(500),
  num5 = rnorm(500),
  num6 = runif(500)
)

Buffer_DF1 <- data.frame(
  group = sample(data_tools, 500, replace=TRUE),
  int = sample(1:15, 500, replace=TRUE),
  num1 = runif(500, 14, 17),
  num2 = runif(500, 14, 17),
  num3 = runif(500, 14, 17),
  num4 = runif(500, 14, 17),
  num5 = runif(500, 14, 17),
  num6 = runif(500, 14, 17)
)

set.seed（8302019）
数据工具