我正在尝试使用发散的调色板在R中创建一个简单的热图。我想使用渐变,以便将低于阈值N的所有数字指定为颜色(比如紫色),并且将高于阈值的所有数字指定为另一种颜色(例如橙色)。数字离阈值越远,颜色越暗。
以下是一个示例数据集:
Division,COL1,COL2,COL3,COL4,COL5,COL6,COL7
Division 1,31.9221884012222,75.8181694429368,97.0480443444103,96.295954938978,70.5677134916186,63.0451830103993,93.0396212730557
Division 2,85.7012346852571,29.0621076244861,16.9130333233625,94.6443660184741,19.9103083927184,61.9562198873609,72.3791105207056
Division 3,47.1665125340223,99.4153356179595,8.51091076619923,79.1276383213699,41.915355855599,7.45079894550145,24.6946100145578
Division 4,66.0743870772421,24.6163331903517,78.694460215047,42.04714265652,50.2694897353649,73.0409651994705,87.3745442833751
Division 5,29.6664374880493,35.4036891367286,19.2967326845974,5.48460693098605,32.4517334811389,15.5926876701415,76.0523204226047
Division 6,95.4969164915383,8.63230894319713,61.7535551078618,24.5590241160244,25.5453423131257,56.397921172902,44.4693325087428
Division 7,87.5015622004867,28.7770316936076,56.5095080062747,34.6680747810751,28.1923673115671,65.0204187724739,13.795713102445
Division 8,70.1077231671661,72.4712177179754,38.4903231170028,36.1821102909744,97.0875509083271,17.184783378616,78.2292529474944
Division 9,47.3570406902581,90.2257485780865,65.6037972308695,77.0234781783074,25.6294377148151,84.900529962033,82.5080851092935
Division 10,58.0811711959541,0.493217632174492,58.5604055318981,53.5780876874924,9.12552657537162,20.313960686326,78.1371118500829
Division 11,34.6708688884974,76.711881859228,22.6064443588257,22.1724311355501,5.48891355283558,79.1159523651004,56.8405059166253
Division 12,33.6812808644027,44.1363711375743,70.6362190190703,3.78900407813489,16.6075889021158,9.12654218263924,39.9711143691093
以下是根据上述数据生成热图的简单代码段
data <- read.csv("dataset.csv", sep=",")
row.names(data) <- data$Division
data <- data[,2:7]
data_matrix <- data.matrix(data)
heatmap(data_matrix, Rowv=NA, Colv=NA, col = heat.colors(256), scale="column", margins=c(5,10))
如何修改上述代码以生成:
[[编辑]]
我刚看到这个question on SO,这似乎非常相似。答案使用ggplot(我没有经验),到目前为止,我无法使ggplot解决方案适应我稍微复杂的数据。
答案 0 :(得分:8)
这应该可以帮到你。 (请注意,如果您希望绘制的颜色与单元格的实际(而不是重新调整的)值相对应,则需要设置scale="none"
。
ncol <- 100
## Make a vector with n colors
cols <- RColorBrewer:::brewer.pal(11,"PuOr") # OR c("purple","white","orange")
rampcols <- colorRampPalette(colors = cols, space="Lab")(ncol)
rampcols[(n/2) + 1] <- rgb(t(col2rgb("green")), maxColorValue=256)
## Make a vector with n+1 breaks
rampbreaks <- seq(0, 100, length.out = ncol+1)
## Try it out
heatmap(data_matrix, Rowv = NA, Colv = NA, scale="none",
col = rampcols, breaks = rampbreaks)
修改强>
为了更好地控制阈值的位置,我建议创建两个单独的调色板 - 一个用于小于阈值的值,一个用于高于阈值的值 - 然后将它们“缝合”在一起。尝试这样的事情,使用Min
,Max
,Thresh
等的不同值:
nHalf <- 50
Min <- 0
Max <- 100
Thresh <- 50
## Make vector of colors for values below threshold
rc1 <- colorRampPalette(colors = c("purple", "white"), space="Lab")(nHalf)
## Make vector of colors for values above threshold
rc2 <- colorRampPalette(colors = c("white", "orange"), space="Lab")(nHalf)
rampcols <- c(rc1, rc2)
## In your example, this line sets the color for values between 49 and 51.
rampcols[c(nHalf, nHalf+1)] <- rgb(t(col2rgb("green")), maxColorValue=256)
rb1 <- seq(Min, Thresh, length.out=nHalf+1)
rb2 <- seq(Thresh, Max, length.out=nHalf+1)[-1]
rampbreaks <- c(rb1, rb2)
heatmap(data_matrix, Rowv = NA, Colv = NA, scale="none",
col = rampcols, breaks = rampbreaks)
答案 1 :(得分:4)
我发现这个帖子非常有用,并且从here中提取了一些想法,但是出于我的目的,我需要概括一些事情并想要使用RColorBrewer包。当我正在研究它时,布鲁尔博士(Color Brewer成名)在我办公室停下来告诉我,我需要在较小的颜色中断内插入,而不是仅仅选择终点。我认为其他人可能会觉得这很有用,所以我在这里发布我的功能以供后代使用。
该函数接收数据向量,发散的colorBrewer调色板的名称以及颜色方案的中心点(默认值为0)。它输出一个包含2个对象的列表:一个classIntervals对象和一个颜色向量:该函数设置为插入总共100种颜色,但可以小心修改。
diverge.color <- function(data,pal_choice="RdGy",centeredOn=0){
nHalf=50
Min <- min(data,na.rm=TRUE)
Max <- max(data,na.rm=TRUE)
Thresh <- centeredOn
pal<-brewer.pal(n=11,pal_choice)
rc1<-colorRampPalette(colors=c(pal[1],pal[2]),space="Lab")(10)
for(i in 2:10){
tmp<-colorRampPalette(colors=c(pal[i],pal[i+1]),space="Lab")(10)
rc1<-c(rc1,tmp)
}
rb1 <- seq(Min, Thresh, length.out=nHalf+1)
rb2 <- seq(Thresh, Max, length.out=nHalf+1)[-1]
rampbreaks <- c(rb1, rb2)
cuts <- classIntervals(data, style="fixed",fixedBreaks=rampbreaks)
return(list(cuts,rc1))
}
在我的工作中我使用这个方案使用spplot绘制栅格图层(rs),如下所示:
brks<-diverge.color(values(rs))
spplot(rs,col.regions=brks[[2]],at=brks[[1]]$brks,colorkey=TRUE))