R中的R图像功能

Question

我在 R 中使用附加的图像功能。我更喜欢将其用作与热图相反的速度，因为我将它用于巨大的矩阵（~ 400000 x 400）。

我的函数中的问题是调色板的动态范围，在我的例子中只有蓝色和黄色。我已经尝试了对 colorramp 线的几处更改，但都没有给我想要的输出。

我尝试的最后一个颜色渐变选项是在 R 中使用了一个名为 ColorRamps 的不错的包，它给出了合理的结果是：

library("colorRamps")
ColorRamp = blue2green2red(400)
ColorLevels <- seq(min, max, length=length(ColorRamp))

但是，仍然不如 matlab 色带选项灵活。

我不太熟悉如何让它看起来更好，范围更广，比如附图中。

请告知我是否可以更改我的图像功能以使我的图像看起来像照片中的那样。

我用于绘制图像的R函数，速度为raster = TRUE如下：

# ----- Define a function for plotting a matrix ----- #
myImagePlot <- function(x, filename, ...){
  dev = "pdf"
  #filename = '/home/unix/dfernand/test.pdf'
  if(dev == "pdf") { pdf(filename, version = "1.4") } else{}
     min <- min(x)
     max <- max(x)
     yLabels <- rownames(x)
     xLabels <- colnames(x)
     title <-c()
  # check for additional function arguments
  if( length(list(...)) ){
    Lst <- list(...)
    if( !is.null(Lst$zlim) ){
       min <- Lst$zlim[1]
       max <- Lst$zlim[2]
    }
    if( !is.null(Lst$yLabels) ){
       yLabels <- c(Lst$yLabels)
    }
    if( !is.null(Lst$xLabels) ){
       xLabels <- c(Lst$xLabels)
    }
    if( !is.null(Lst$title) ){
       title <- Lst$title
    }
  }
# check for null values
if( is.null(xLabels) ){
   xLabels <- c(1:ncol(x))
}
if( is.null(yLabels) ){
   yLabels <- c(1:nrow(x))
}

layout(matrix(data=c(1,2), nrow=1, ncol=2), widths=c(4,1), heights=c(1,1))

 # Red and green range from 0 to 1 while Blue ranges from 1 to 0
 ColorRamp <- rgb( seq(0,1,length=256),  # Red
                   seq(0,1,length=256),  # Green
                   seq(1,0,length=256))  # Blue
 ColorLevels <- seq(min, max, length=length(ColorRamp))

 # Reverse Y axis
 reverse <- nrow(x) : 1
 yLabels <- yLabels[reverse]
 x <- x[reverse,]

 # Data Map
 par(mar = c(3,5,2.5,2))
 image(1:length(xLabels), 1:length(yLabels), t(x), col=ColorRamp, xlab="",
 ylab="", axes=FALSE, zlim=c(min,max), useRaster=TRUE)
 if( !is.null(title) ){
    title(main=title)
 }
# Here we define the axis, left of the plot, clustering trees....
#axis(BELOW<-1, at=1:length(xLabels), labels=xLabels, cex.axis=0.7)
# axis(LEFT <-2, at=1:length(yLabels), labels=yLabels, las= HORIZONTAL<-1,
# cex.axis=0.7)

 # Color Scale (right side of the image plot)
 par(mar = c(3,2.5,2.5,2))
 image(1, ColorLevels,
      matrix(data=ColorLevels, ncol=length(ColorLevels),nrow=1),
      col=ColorRamp,
      xlab="",ylab="",
      xaxt="n", useRaster=TRUE)

 layout(1)
  if( dev == "pdf") {
    dev.off() }
}
# ----- END plot function ----- #

Answer 1

您可以在colorRampPalette 中定义偏差。我还调整了函数来定义color.palette 中颜色之间的步数：

#This is a wrapper function for colorRampPalette. It allows for the
#definition of the number of intermediate colors between the main colors.
#Using this option one can stretch out colors that should predominate
#the palette spectrum. Additional arguments of colorRampPalette can also
#be added regarding the type and bias of the subsequent interpolation.
color.palette <- function(steps, n.steps.between=NULL, ...){

 if(is.null(n.steps.between)) n.steps.between <- rep(0, (length(steps)-1))
 if(length(n.steps.between) != length(steps)-1) stop("Must have one less n.steps.between value than steps")

 fill.steps <- cumsum(rep(1, length(steps))+c(0,n.steps.between))
 RGB <- matrix(NA, nrow=3, ncol=fill.steps[length(fill.steps)])
 RGB[,fill.steps] <- col2rgb(steps)

 for(i in which(n.steps.between>0)){
  col.start=RGB[,fill.steps[i]]
  col.end=RGB[,fill.steps[i+1]]
  for(j in seq(3)){
   vals <- seq(col.start[j], col.end[j], length.out=n.steps.between[i]+2)[2:(2+n.steps.between[i]-1)]  
   RGB[j,(fill.steps[i]+1):(fill.steps[i+1]-1)] <- vals
  }
 }

     new.steps <- rgb(RGB[1,], RGB[2,], RGB[3,], maxColorValue = 255)
 pal <- colorRampPalette(new.steps, ...)
 return(pal)
}

以下是两者的示例（我已经压缩了青色和黄色之间的步数）：

Z <- t(as.matrix(1:100))

pal.1 <- colorRampPalette(c("blue", "cyan", "yellow", "red"), bias=1)
pal.2 <- colorRampPalette(c("blue", "cyan", "yellow", "red"), bias=3)
pal.3 <- color.palette(c("blue", "cyan", "yellow", "red"), n.steps.between=c(10,1,10))

    x11()
par(mfcol=c(1,3))
image(Z, col=pal.1(100))
image(Z, col=pal.2(100))
image(Z, col=pal.3(100))

另外，如果您有兴趣，I wrote a function 会绘制色标并使用与image 相同的参数。如果您正确设置绘图布局，这也是绘制矩阵和相应色标的快速方法。