Hello
I have two for loops that I am trying to optimize... I looked for
vectorization or for using some funcions of the apply family but really
cannot do it. I am writting my code with some small data set. With this
size there is no problem but sometimes I will have hundreds of rows so it
is really important to optimize the code. Any suggestion will be very
welcomed.
library("TSMining")
dataS = data.frame(V1 = sample(c(1,2,3,4),30,replace = T),
V2 = sample(c(1,2,3,4),30,replace =
T),
V3 = sample(c(1,2,3,4),30,replace =
T),
V4 = sample(c(1,2,3,4),30,replace =
T))
saxM = Func.matrix(5)
colnames(saxM) = 1:5
rownames(saxM) = 1:5
matrixPrepared = matrix(NA, nrow = nrow(dataS), ncol = nrow(dataS))
FOR(I IN 1:(NROW(DATAS)-1)){
FOR(J IN (1+I):NROW(DATAS)){
MATRIXPREPARED[I,J] = FUNC.DIST(AS.CHARACTER(DATAS[I,]),
AS.CHARACTER(DATAS[J,]), SAXM, N=60)
}
}
matrixPrepared
Thank you!
------
Aurora González Vidal
Phd student in Data Analytics for Energy Efficiency
Faculty of Computer Sciences
University of Murcia
@. aurora.gonzal...@um.es
T. 868 88 7866
www.um.es/ae
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