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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______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Don McKenzie Research Ecologist Pacific Wildland Fire Sciences Lab US Forest Service Affiliate Professor School of Environmental and Forest Sciences University of Washington dmck at uw.edu -- Edward H Patzelt | Clinical Science PhD Student Psychology | Harvard University
Don McKenzie Research Ecologist Pacific Wildland Fire Sciences Lab US Forest Service Affiliate Professor School of Environmental and Forest Sciences University of Washington dmck at uw.edu