在R(convhulln函数)中绘制由quickhull算法给出的凸包 [英] Plot convex hull given by quickhull algorithm in R (convhulln function)

问题描述

我需要绘制R中quickhull算法给出的凸包.这是一个示例.

I need to plot the convex hull given by quickhull algorithm in R. Here is an example.

library(geometry)
x1 <- rnorm(100, 0.8, 0.3)
y1 <- rnorm(100, 0.8, 0.3)
ConVexHull<-convhulln(cbind(x1,y1),"FA")

ConVexHull $ hull给出一个m维度的索引矩阵，其每一行都定义一个 昏暗的三角形".

ConVexHull$hull gives a m-by-dimension index matrix of which each row defines a dim-dimensional "triangle".

我知道如何使用chull函数进行绘图，但是我不确定chull是否提供与convhulln相同的船壳

I know how to plot using chull function but I am not sure if chull gives the same hull as given by convhulln

  Plot_ConvexHull<-function(xcoord, ycoord, lcolor){
  hpts <- chull(x = xcoord, y = ycoord)
  hpts <- c(hpts, hpts[1])
  lines(xcoord[hpts], ycoord[hpts], col = lcolor)
} 
xrange <- range(c(x1))
yrange <- range(c(y1))
par(tck = 0.02, mgp = c(1.7, 0.3, 0))
plot(x1, y1, type = "p", pch = 1, col = "black", xlim = c(xrange), ylim =    c(yrange))
Plot_ConvexHull(xcoord = x1, ycoord = y1, lcolor = "black")

推荐答案

可重现的示例:

library(geometry)

set.seed(0)

x1 <- rnorm(100, 0.8, 0.3)
y1 <- rnorm(100, 0.8, 0.3)

xdf <- data_frame(x1, y1)

(ConVexHull <- convhulln(cbind(x1,y1), "FA"))
## $hull
##      [,1] [,2]
## [1,]   63   59
## [2,]   10   53
## [3,]   10   63
## [4,]   80   59
## [5,]   80   15
## [6,]   37   53
## [7,]   37   15
## 
## $area
## [1] 4.258058
## 
## $vol
## [1] 1.271048

这些是$hull中的从/到"边缘对，因此我们将建立一组顶点对:

Those are the from/to edge pairs in $hull, so we shall build said set of vertex pairs:

data.frame(
  do.call(
    rbind,
    lapply(1:nrow(ConVexHull$hull), function(i) {
      rbind(xdf[ConVexHull$hull[i,1],], xdf[ConVexHull$hull[i,2],])
    })
  )
) -> h_df

，并证明它们确实是正确的:

and, prove they are, indeed, correct:

ggplot() +
  geom_point(data=xdf, aes(x1, y1), color="red") +
  geom_point(data=h_df, aes(x1, y1), shape=21, fill=NA, color="black", size=3)

但是，它们不是订单"中的 :

They are, however, not in "order":

ggplot() +
  geom_point(data=xdf, aes(x1, y1), color="red") +
  geom_point(data=h_df, aes(x1, y1), shape=21, fill=NA, color="black", size=3) +
  geom_path(data=h_df, aes(x1, y1), color="blue")

因此，如果要在点周围有路径或多边形(这是匿名用户的注释/链接的意思)，我们需要按顺序对它们进行排序(对它们进行排序).

So, we need to get them in order (sort them) if you want to have a path or polygon around the points (which was the meaning of the comment / link by the anonymous user).

我们可以按顺时针对其进行排序:

We can sort them clockwise:

h_df <- h_df[order(-1 * atan2(h_df$y1 - mean(range(h_df$y1)), h_df$x1 - mean(range(h_df$x1)))),]
h_df <- rbind(h_df, h_df[1,])

(将-1取反)

而且，我们有一个漂亮的外包装:

and, we have a lovely outer wrapper:

ggplot() +
  geom_point(data=xdf, aes(x1, y1), color="red") +
  geom_point(data=h_df, aes(x1, y1), shape=21, fill=NA, color="black", size=3) +
  geom_path(data=h_df, aes(x1, y1), color="blue")

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