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norm <- function(x) { | |
norm <- sqrt(sum(x^2)) | |
return(norm) | |
} | |
x.1 <- c(-2,1,0) | |
x.2 <- c(1,-1,1) | |
y.1 <- c(0,1,0) | |
y.2 <- c(1,1,2) | |
#making lines into planes, finding normal vector between them | |
x.1 <- c(-2,1,0) | |
x.2 <- c(1,-1,1) | |
y.1 <- c(0,1,0) | |
y.2 <- c(1,1,2) | |
#find normal vector | |
mm<-cbind(x.2,y.2) | |
N <- sapply(1:3,function(x)det(mm[-x,])*(2*(x%%2)-1)) | |
xy <- x.1 - y.1 | |
dist <- norm(t(xy)%*%N)/norm(N) | |
#minimizing the distance function | |
linesDist <- function(x1, x2, y1, y2) { | |
dist <- function(s1, s2) { | |
d <- sqrt(t(x1 + s1*x2 - (y1 + s2*y2)) %*% (x1 + s1*x2 - (y1 + s2*y2))) | |
return(d)} | |
start <- cbind(seq(-100,100,.01),seq(-100,100,.01)) | |
m<-min(mapply(function(s1,s2) nlm(dist,s1,s2)$minimum,start[,1],start[,2])) | |
return(m)} | |
linesDist(x.1,x.2,y.1,y.2) | |
#[1] 1.603579 | |
dist | |
# 1.603567 |
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