Hi,
I've got a 2D timeseries of handwriting samples,
xy time
1 1073 1058 769.05
2 1072 1085 769.07
3 1066 1117 769.08
4 1052 1152 769.10
5 1030 1196 769.12
6 1009 1242 769.13
7 994 1286 769.14
upto 500
I was just wondering how to plot this as an animation, so that the point
Hi, guys. Thanks for all your help.
I tried Gabors methods and they seem to work fine - robust as well. I wish
I had though of those a few days ago! I'll try and give the other methods a
try later.
In the end though this drove me so nuts that I've managed to query the
database which outputed my
Hi, I'm new to R and I'm stuck trying to import some data from a .dat file
I've been given. The tricky bit for me is that the data has both variable
values and labels?
The data looks like this,
Id=1 time=2011-03-27 19:23:40 start=1.4018 end=1.4017
Id=2 time=2011-03-27 19:23:40 start=1.80
Hi Stefan,
thats really interesting - I never though of trying to benchmark Linux-64
against OSX (a friend who works on large databases, says OSX performs better
than Linux in his work!). Thanks for posting your comparison, and your hints
:)
i) I guess you have a very fast CPU (Core i7 or so, I g
Hi Dennis, sorry for the delayed reply and thanks for the article. I digged
into it and found that if you have a GPU, the CUBLAS library beats the
BLAS/ATLAS implementation in the Matrix package for 'large' problems. Here's
what I mean,
its = 2500
dim = 1750
X = matrix(rnorm(its*dim),its, dim)
Hey thanks alot guys !!! That really speeds things up !!! I didn't know %*%
and crossprod, could operate on matrices. I think you've saved me hours in
calculation time. Thanks again.
> system.time({C=matrix(0,50,50);for(i in 1:n)C = C + (X[i,] %o% X[i,])})
user system elapsed
0.450.00
Hi, I'm new to R and stats, and I'm trying to speed up the following sum,
for (i in 1:n){
C = C + (X[i,] %o% X[i,]) # the sum of outer products - this is very
slow
according to Rprof()
}
where X is a data matrix (nrows=1000 X ncols=50), and n=1000. The sum has to
be calcula
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