R-一個圖中有多個圖，但是圖上重疊部分的透明度不起作用

Question

我正在R中創建一些海拔數據的頻率/密度圖。下面的代碼非常適合在一張圖中獲取兩個不同的變量，每個密度和頻率。 因此，總共有兩個條形圖和兩條線。

問題是，條形圖彼此重疊，我無法正確設置“ alpha”的透明度設置。 這是我需要幫助的地方。 我想這是一個非常簡單的問題。

我已經在代碼中的不同位置嘗試了alpha函數，但是沒有用。

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)

我唯一能得到的結果是第二個變量的條形而不是透明的條形，請參見下圖。 我想讓橙色條透明，以查看藍色條和穿過的線。

Answer 1

考慮使用允許r參數的?rgb 。 另外，為了更好地進行顏色比較，請使用不同alpha值的相同顏色。

藍色

# 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)

---

橙子

# 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)

---

數據

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)
)