我想知道如何計算兩個橢圓之間的交點,例如如圖所示該圖中雲芝和virginca之間的交點的體積: ,其使用基於此tutorial以下兆瓦繪製:如何計算r中橢圓交點的體積
data(iris)
log.ir <- log(iris[, 1:4])
ir.species <- iris[, 5]
ir.pca <- prcomp(log.ir, center = TRUE, scale. = TRUE)
library(ggbiplot)
g <- ggbiplot(ir.pca, obs.scale = 1, var.scale = 1,
groups = ir.species, ellipse = TRUE,
circle = TRUE)
g <- g + scale_color_discrete(name = '')
g <- g + theme(legend.direction = 'horizontal',
legend.position = 'top')
print(g)
我得到爲橢圓的協方差和中心如下:
setosa.cov <- cov(ir.pca$x[ir.species=="setosa",])
versicolor.cov <- cov(ir.pca$x[ir.species=="versicolor",])
virginica.cov <- cov(ir.pca$x[ir.species=="virginica",])
setosa.centre <- colMeans(ir.pca$x[ir.species=="setosa",])
versicolor.centre <- colMeans(ir.pca$x[ir.species=="versicolor",])
virginica.centre <- colMeans(ir.pca$x[ir.species=="virginica",])
但是,然後我在我的智慧結束: - |
編輯: 繼@下面卡爾witthoft,這裏的例子使用SIAR ::重疊的適應症:
library(siar)
setosa <- ir.pca$x[ir.species=="setosa",]
versicolor <- ir.pca$x[ir.species=="versicolor",]
virginica <- ir.pca$x[ir.species=="virginica",]
overlap.fun <- function(data.1, data.2){
dimensions <- ncol(data.1)
for(i in 1:(dimensions-1)){
overlap.out <- overlap(data.1[,i], data.1[,i+1], data.2[,i], data.2[,i+1], steps = 5)
out$overlap[i] <- overlap.out$overlap
out$area1[i] <- overlap.out$area1
out$area2[i] <- overlap.out$area2
}
return(out)
}
overlap.fun(versicolor, virginica)
回報:
$overlap
[1] 0.01587977 0.48477088 0.08375927
$area1
[1]1.020596 1.04614461 0.08758691
$area2
[1] 1.028594 1.1535106 0.1208483
奇怪的是當我做了百分比計算的值並不真正對應於ggbiplot PCA中的橢球:
tmp <- overlap(versicolor[,1], versicolor[,2], virginica[,1], virginica[,2], steps = 5)
virginica.percentage <- round(x=(tmp$overlap/tmp$area2*100), digits = 2)
versicolor.percentage <- round(x=(tmp$overlap/tmp$area1*100), digits = 2)
> virginica.percentage [1] 1.54
> versicolor.percentage[1] 1.56
這比上面的圖1中所示的要小得多。 但是可能更好的在這個here上打開另一個線程。
基本的方法是找到相交點,計算「上」和「下」曲線的積分,並取距離,您需要將其分開以確保每個積分超過單值d功能範圍。也就是說,我似乎記得在CRAN上有一兩個包含這種相交面積計算的軟件包。當然我不記得哪些:-( –