（慢边着色）如何避免循环所有tip.labels（包猿）

Question

我在使用“ape”

中的某些函数生成的phylo树中着色边缘

由于我总是用C编程，我仍然觉得很难停止以循环方式思考。

我能想到的唯一方法是通过（1）循环所有tip.labels（ID），（2）找出属于它们的边缘和（3）设置所需的颜色。

这是1比1完成的，因此大树的速度非常慢：

tsampltime.rooted=structure(list(edge = structure(c(24L, 24L, 24L, 24L, 24L, 25L, 
26L, 26L, 27L, 27L, 28L, 28L, 25L, 29L, 29L, 30L, 30L, 30L, 30L, 
24L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 34L, 35L, 35L, 34L, 36L, 
36L, 34L, 37L, 37L, 1L, 2L, 12L, 23L, 25L, 26L, 6L, 27L, 5L, 
28L, 3L, 4L, 29L, 7L, 30L, 8L, 9L, 10L, 11L, 31L, 13L, 32L, 21L, 
22L, 33L, 20L, 34L, 35L, 14L, 15L, 36L, 16L, 17L, 37L, 18L, 19L
), .Dim = c(36L, 2L)), Nnode = 14L, tip.label = c("0", "2325", 
"55304", "124953", "72254", "66507", "85089", "110256", "123265", 
"97350", "123721", "36770", "48692", "110612", "97224", "104337", 
"124625", "128499", "120928", "88404", "73335", "75059", "17928"
), edge.length = c(0, 0.953297, 8.054944, 4.4120893, 9.173083, 
1.409346, 3.752752, 0.483517, 4.620875, 0.582417, 0.510989, 12.4862723, 
6.291209, 1.920329, 3.071429, 4.5027528, 5.497248, 2.777472, 
5.5274749, 8.414843, 2.5467017, 3.79121, 3.824171, 3.961538, 
3.804944, 2.126375, 1.75275, 1.93956, 3.3516546, 1.57418, 2.31319, 
2.22528, 4.0384651, 3.898348, 2.722523, 1.87088)), .Names = c("edge", 
"Nnode", "tip.label", "edge.length"), class = "phylo", order = "cladewise")
   ... 
#distValuesPerId[,] has [LABELID,COLOR]
distValuesPerId=source('http://ubuntuone.com/5y7ZYCWfE73T5lhnUpmeXc')
...
uniqueIDs=unique(tree$tip.label)
distTrdsampledcol <-rep("black", length(tree$edge)) #init in black
for(i in uniqueIDs) { #(1)
    a= c(which(tree$tip.label==i)) 
    b= which(tree$edge[,2]== a) #(2)
    distTrdsampledcol [ b ] <- distValuesPerId[i,2] #(3)
}
...
#plot(tree, edge.color=distTrdsampledcol)

任何人都可以帮我重新考虑一下吗？这样做有效吗？

提前致谢！

Ĵ

Answer 1

你可能会过度思考这个问题。只需从您的巨型颜色data.frame中选择您需要的颜色。

plot(tree,edge.color=distValuesPerId[tree$tip.label,2])

试试?plot.phylo上的示例列表，他们有很多关于你可以用树做的非常酷的事情的例子，包括着色。它可能会给你一些想法。

---

看到你的评论后，我意识到，我误解了这个问题。这应该做你想要的没有循环：

cols=distValuesPerId[match(tree$tip.label[tree$edge[,2]],distValuesPerId[,1]),2]
my.cols=ifelse(is.na(cols),'black',cols)
plot(tree, edge.color=my.cols)

打破它：

# Find the tip labels associated with each edge, NA if it is not an edge to a tip
edge.tip.labels=tree$tip.label[tree$edge[,2]]
# Match each of those tip labels to the label column in your colur data frame
edge.rows=match(edge.tip.labels,distValuesPerId[,1])
# Find the colour for each of those rows
cols=distValuesPerId[edge.rows,2]
# Where it is NA, convert it to 'black' (where it is not a 'tip edge')
my.cols=ifelse(is.na(cols),'black',cols)