Euclidean Distance in 3 Dimensions

 The dist() function works just fine in 2d or 3d or 100d. Your
description of what you want to accomplish is not clear. Your code compares
rows 1 and 2, then 2 and 3, then 3 and 4, and so on. You are comparing only
adjacent points, but your description makes it sound like you want to
compare point 1 to all the other points and see if they are in the same
group and over 8 or in another group. If you type the following command you
will see that your dat$X is just the diagonal of the distance matrix: 1
with 2, 2 with 3, 3 with 4 etc:



dist(dat[, 3:5])



-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352



*From:* r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
*On Behalf Of *Don McKenzie
*Sent:* Thursday, August 21, 2014 1:44 PM
*To:* Patzelt, Edward
*Cc:* R-help at r-project.org
*Subject:* Re: [R] Euclidean Distance in 3 Dimensions



Ugh sorry.  I misread your message obviously. Cc?ing back to the list (as
is the protocol)

I?m surprised no one else has replied. I?m a lightweight compared to
others on the list.  It looks as if the dist() function has compiled code,
which suggests that there is some gnarly linear algebra underneath to
speed it up even in 2D. Not for the faint-of-heart to hack.

Others?  ?dist3D??

On Aug 21, 2014, at 11:34 AM, Patzelt, Edward <patzelt at g.harvard.edu>
wrote:

This function unfortunately does not work in 3d space.

Thoughts?


On Wed, Aug 20, 2014 at 4:57 PM, Don McKenzie <dmck at u.washington.edu>

wrote:

?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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