Euclidean Distance in 3 Dimensions

?dist

from the help

dist {stats}    R Documentation
Distance Matrix Computation

Description

This function computes and returns the distance matrix computed by using
the specified distance measure to compute the distances between the rows of
a data matrix.

Is this what you want?  Computing on a matrix whose rows are your x, y,
and z values?


On Aug 20, 2014, at 1:12 PM, Patzelt, Edward <patzelt at g.harvard.edu>
wrote:

R Community -

I am attempting to write a function that will calculate the distance
between points in 3 dimensional space for unique regions (e.g. localized
brain regions such as the frontal lobe).

For example I'm looking to compare each point in region 45 to every other
region in 45 to establish if they are a distance of 8 or more apart. I

can

do this linearly comparing each distance to the previous but this is not
comparing all points.

structure(list(Cluster.Index = c(46L, 46L, 46L, 46L, 46L, 45L,
45L, 45L, 45L, 45L, 44L, 44L, 44L, 44L, 44L, 43L, 43L, 43L, 43L,
43L), Value = c(8.21, 7.96, 7.85, 7.83, 7.8, 5.38, 4.56, 4.5,
4, 3.99, 5.42, 4.82, 4.21, 4.18, 3.91, 4.79, 4.27, 3.24, 3.06,
3.04), x = c(33L, 38L, 37L, 36L, 38L, 47L, 42L, 43L, 44L, 42L,
50L, 41L, 39L, 41L, 44L, 46L, 45L, 45L, 41L, 46L), y = c(15L,
12L, 12L, 13L, 13L, 91L, 84L, 84L, 95L, 96L, 69L, 70L, 65L, 65L,
59L, 41L, 40L, 46L, 44L, 47L), z = c(41L, 38L, 41L, 39L, 33L,
39L, 40L, 42L, 44L, 45L, 34L, 36L, 30L, 35L, 39L, 53L, 47L, 61L,
52L, 57L), X = c(NA, 6.557438524302, 3.16227766016838, 2.44948974278318,
6.32455532033676, 78.7464284904401, 8.66025403784439, 2.23606797749979,
11.2249721603218, 2.44948974278318, 30.2324329156619, 9.2736184954957,
8.06225774829855, 5.3851648071345, 7.81024967590665, 22.8910462845192,
6.16441400296898, 15.2315462117278, 10.0498756211209, 7.68114574786861
)), .Names = c("Cluster.Index", "Value", "x", "y", "z", "X"), row.names =
c(NA,
20L), class = "data.frame")

mainDat <- data.frame()
for(i in 2:nrow(dat)){
tempDist <- (sqrt((dat$x[i] - dat$x[i-1])^2 + (dat$y[i] - dat$y[i-1])^2 +
(dat$z[i] - dat$z[i-1])^2))
dat$X[i] <- c(tempDist)
if(dat$Cluster.Index[i] != dat$Cluster.Index[i-1]){
mainDat <- rbind(mainDat, dat[i,])
}
if((dat$Cluster.Index[i] == dat$Cluster.Index[i-1])) {
if(tempDist > 8){
mainDat <- rbind(mainDat, dat[i,])
}
}
}




--

*Edward H Patzelt | Clinical Science PhD StudentPsychology | Harvard
University *

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