寫在前面：作為一個剛開始從業生信的吊車尾，認為生信技能要來自於網羅，舉一反三，加以思考，為自己的目的加以練習。
本次的思路來自於RColorBrewer和ggsci
目標：做一個便於保存自己配色，且隨時進行查看的Rscript，後續考慮實用性，再加以製作R包
下面是一個簡單的基於 Base Plotting System 的繪圖代碼，便於適用於不同版本的base-R
功能：輸入一個色彩向量，自動畫出方格圖，並表上數字，方便自行挑選使用的顏色。
點擊查看代碼
visColor <-function(colorset=c("white","black")){
color_data=data.frame(color_name=paste0("color",c(1:length(colorset))),color_code=colorset)
n=nrow(color_data)
color_data$y <- rep(1:ceiling(n / 10), each = 10)[1:n]
color_data$x <- rep(1:10, length.out = n)
max_x=max(color_data$x)+1
max_y=max(color_data$y)+1
plot(NA, xlim = c(0, max_x), ylim = c(0, max_y), xlab = "", ylab = "", type = "n", axes = FALSE, asp = 1)
for(i in 1:nrow(color_data)) {
rect(
color_data$x[i] - 0.5, color_data$y[i] - 0.5,
color_data$x[i] + 0.5, color_data$y[i] + 0.5,
col = color_data$color_code[i], border = "black"
)
text(
color_data$x[i], color_data$y[i], labels = i, cex = 1.5, col = "black"
)
}
# 添加外邊框
rect(0, 0,max_x, max_y, col = NA, border = "black", lwd = 2)
}
測試visColor。
點擊查看代碼
visColor()
將一段複製好的顏色，作為向量輸入
點擊查看代碼
visColor <-function(colorset=c("white","black")){
color_data=data.frame(color_name=paste0("color",c(1:length(colorset))),color_code=colorset)
n=nrow(color_data)
color_data$y <- rep(1:ceiling(n / 10), each = 10)[1:n]
color_data$x <- rep(1:10, length.out = n)
max_x=max(color_data$x)+1
max_y=max(color_data$y)+1
plot(NA, xlim = c(0, max_x), ylim = c(0, max_y), xlab = "", ylab = "", type = "n", axes = FALSE, asp = 1)
for(i in 1:nrow(color_data)) {
rect(
color_data$x[i] - 0.5, color_data$y[i] - 0.5,
color_data$x[i] + 0.5, color_data$y[i] + 0.5,
col = color_data$color_code[i], border = "black"
)
text(
color_data$x[i], color_data$y[i], labels = i, cex = 1.5, col = "black"
)
}
# 添加外邊框
rect(0, 0,max_x, max_y, col = NA, border = "black", lwd = 2)
}
