[R] r function for calculating extreme spread in group
I'm trying to figure out how to write a r function that will calculate
the extreme spread of a group of points given their (x,y)
coordinates. Extreme Spread is the maximal Euclidean distance between
two points in a group
ex.spread = max{ sqrt [ (xi-xj)^2 - (yi-yj)^2 ] } for i not equal to j
I have 60 levels to apply this to.
There is the combination function in the dprep package but I wasn't
sure how to use this or apply an index the points in each group.
Any ideas?
Steve
Steven Matthew Anderson
[EMAIL PROTECTED]
Ad Astra per Aspera
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Re: [R] r function for calculating extreme spread in group
Steven Matthew Anderson adastra69 at mac.com writes:
I'm trying to figure out how to write a r function that will calculate
the extreme spread of a group of points given their (x,y)
coordinates. Extreme Spread is the maximal Euclidean distance between
two points in a group
ex.spread = max{ sqrt [ (xi-xj)^2 - (yi-yj)^2 ] } for i not equal to j
I have 60 levels to apply this to.
how about something like
max(dist(cbind(x,y)) ... ???
(or to do this in a data frame d with columns x, y, and g (group),
sapply(split(d,d$g),function(Z)max(dist(Z[,c(x,y)])))
Ben Bolker
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Re: [R] r function for calculating extreme spread in group
Thank you Jorge,
My talent in building functions is weak. I think I'm close but I'm
not doing something right.
res=dist(yourdata)
res[which.max(res)]
does provide me with the correct distance but how do I apply it across
data with level such as ...
yourdata
=as.data.frame(cbind(lvl=LETTERS[1:2],x=rpois(10,10),y=rnorm(10) ))
yourdata
lvl x y
1A 10 0.14377148075807
2B 5 -0.117753598165951
3A 14 -0.912068366948338
4B 10 -1.43758624082998
5A 16 -0.797089525071965
6B 11 1.25408310644997
7A 7 0.77214218580453
8B 9 -0.219515626753440
9A 12 -0.424810283377287
10 B 13 -0.418980099421959
My attempt to use tapply blew up on me.
Extreme.Spread-matrix(nrow=60,ncol=2)
ES-function(Level) {
+temp-
subset(x=ES.Data,Level==level,select=c(Horizontal,Vertical))
+e-dist(rbind(temp$Horizontal,temp
$Vertical),method=euclidean)
+m-e[which.max(e)]
+es-cbind(level,m)
+Extreme.Spread-rbind(Extreme.Spread,es)
+}
tapply(X=ES.Data,INDEX=Level,FUN=ES)
Error in tapply(X = ES.Data, INDEX = Level, FUN = ES) :
arguments must have same length
On Aug 27, 2008, at 2:30 PM, Jorge Ivan Velez wrote:
R-help@r-project.org
Steven Matthew Anderson
[EMAIL PROTECTED]
Ad Astra per Aspera
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] r function for calculating extreme spread in group
On Wednesday 27 August 2008, Steven Matthew Anderson wrote:
Thank you Jorge,
My talent in building functions is weak. I think I'm close but I'm
not doing something right.
res=dist(yourdata)
res[which.max(res)]
does provide me with the correct distance but how do I apply it across
data with level such as ...
yourdata
=as.data.frame(cbind(lvl=LETTERS[1:2],x=rpois(10,10),y=rnorm(10) ))
yourdata
lvl x y
1A 10 0.14377148075807
2B 5 -0.117753598165951
3A 14 -0.912068366948338
4B 10 -1.43758624082998
5A 16 -0.797089525071965
6B 11 1.25408310644997
7A 7 0.77214218580453
8B 9 -0.219515626753440
9A 12 -0.424810283377287
10 B 13 -0.418980099421959
My attempt to use tapply blew up on me.
How about something like:
# generate some fake data
set.seed(1)
x - as.data.frame(cbind(lvl=LETTERS[1:2],x=rpois(10,10),y=rnorm(10) ))
# function for computing the max, euclidean distance
function(x.i) { d - dist(x.i) ; d[which.max(d)]}
# run function with data, subset by level
x.list - by(x, x$lvl, f)
# combine elements of resulting list into vector, with names from original
# levels
sapply(x.list, '[')
AB
8.686382 4.578703
Dylan
--
Dylan Beaudette
Soil Resource Laboratory
http://casoilresource.lawr.ucdavis.edu/
University of California at Davis
530.754.7341
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Re: [R] r function for calculating extreme spread in group
Dear Steven,
Try this:
# Data set
yourdata=as.data.frame(cbind(lvl=LETTERS[1:2],x=rpois(10,10),y=rnorm(10) ))
# Splitting your data set
sdata=split(yourdata,yourdata$lvl)
res=lapply(sdata,function(X) max(dist(X[,-1])))
do.call(c,res)
HTH,
Jorge
On Wed, Aug 27, 2008 at 7:28 PM, Steven Matthew Anderson
[EMAIL PROTECTED]wrote:
Thank you Jorge,
My talent in building functions is weak. I think I'm close but I'm not
doing something right.
res=dist(yourdata)
res[which.max(res)]
does provide me with the correct distance but how do I apply it across data
with level such as ...
yourdata=as.data.frame(cbind(lvl=LETTERS[1:2],x=rpois(10,10),y=rnorm(10)
))
yourdata
lvl x y
1A 10 0.14377148075807
2B 5 -0.117753598165951
3A 14 -0.912068366948338
4B 10 -1.43758624082998
5A 16 -0.797089525071965
6B 11 1.25408310644997
7A 7 0.77214218580453
8B 9 -0.219515626753440
9A 12 -0.424810283377287
10 B 13 -0.418980099421959
My attempt to use tapply blew up on me.
Extreme.Spread-matrix(nrow=60,ncol=2)
ES-function(Level) {
+
temp-subset(x=ES.Data,Level==level,select=c(Horizontal,Vertical))
+
e-dist(rbind(temp$Horizontal,temp$Vertical),method=euclidean)
+ m-e[which.max(e)]
+ es-cbind(level,m)
+ Extreme.Spread-rbind(Extreme.Spread,es)
+ }
tapply(X=ES.Data,INDEX=Level,FUN=ES)
Error in tapply(X = ES.Data, INDEX = Level, FUN = ES) :
arguments must have same length
On Aug 27, 2008, at 2:30 PM, Jorge Ivan Velez wrote:
R-help@r-project.org
Steven Matthew Anderson
[EMAIL PROTECTED]
Ad Astra per Aspera
[[alternative HTML version deleted]]
__
R-help@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.
