On Wed, 24 Aug 2011, Tsjerk Wassenaar wrote:
Yes, sorry, so the distance is
colSums((t(x)-y)**2)
(I knew that) :S
Did you know that ** is deprecated (and almost undocumented), so your
readers can hardly be expected to understand that? Please use the
documented operator ^ .
Tsjerk
On Wed, Aug 24, 2011 at 9:19 AM, Enrico Schumann
<enricoschum...@yahoo.de> wrote:
R will subtract the vector columnwise from the matrix (so the vectors need
be the columns).
x <- matrix(0, nrow = 10L, ncol = 5L)
y <- 1:5
x - y
[,1] [,2] [,3] [,4] [,5]
[1,] -1 -1 -1 -1 -1
[2,] -2 -2 -2 -2 -2
[3,] -3 -3 -3 -3 -3
[4,] -4 -4 -4 -4 -4
[5,] -5 -5 -5 -5 -5
[6,] -1 -1 -1 -1 -1
[7,] -2 -2 -2 -2 -2
[8,] -3 -3 -3 -3 -3
[9,] -4 -4 -4 -4 -4
[10,] -5 -5 -5 -5 -5
-----Ursprüngliche Nachricht-----
Von: Tsjerk Wassenaar [mailto:tsje...@gmail.com]
Gesendet: Mittwoch, 24. August 2011 09:02
An: Enrico Schumann
Cc: Wei Wu; r-help@r-project.org
Betreff: Re: [R] Efficient way to Calculate the squared
distances for a set ofvectors to a fixed vector
Hi Wei Wu,
What about:
x <- matrix(rnorm(20000*5),ncol=5)
y <- rnorm(5)
distances <- rowSums((x-y)**2)
Cheers,
Tsjerk
On Wed, Aug 24, 2011 at 8:43 AM, Enrico Schumann
<enricoschum...@yahoo.de> wrote:
You could do something like this:
# data
nrows <- 20000L
ncols <- 5L
myVec <- array(rnorm(nrows * ncols), dim = c(nrows, ncols)) y <-
rnorm(ncols)
temp <- t(myVec) - y
result <- colSums(temp * temp)
# check
all.equal(as.numeric(crossprod(myVec[1L, ] - y)), result[1L]) #...
(And don't use a data.frame, but a matrix.)
regards,
Enrico
-----Ursprüngliche Nachricht-----
Von: r-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org] Im Auftrag von Wei Wu
Gesendet: Mittwoch, 24. August 2011 07:18
An: r-help@r-project.org
Betreff: [R] Efficient way to Calculate the squared
distances for a
set ofvectors to a fixed vector
I am pretty new to R. So this may be an easy question for
most of you.
I would like to calculate the squared distances of a large
set (let's
say 20000) of vectors (let's say dimension of 5) to a fixed vector.
Say I have a data frame MY_VECTORS with 20000 rows and 5
columns, and
one 5x1 vector y. I would like to efficiently calculate
the squared
distances between each of the 20000 vectors in MY_VECTORS and y.
The squared distance between two vectors x and y can be calculated:
distance <- crossprod(x-y)
Without looping, what is the efficient code to achieve this?
Thanks.
______________________________________________
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PLEASE do read the posting guide
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and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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.
--
Tsjerk A. Wassenaar, Ph.D.
post-doctoral researcher
Molecular Dynamics Group
* Groningen Institute for Biomolecular Research and Biotechnology
* Zernike Institute for Advanced Materials University of
Groningen The Netherlands
--
Tsjerk A. Wassenaar, Ph.D.
post-doctoral researcher
Molecular Dynamics Group
* Groningen Institute for Biomolecular Research and Biotechnology
* Zernike Institute for Advanced Materials
University of Groningen
The Netherlands
______________________________________________
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.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
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.
