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<div class="moz-cite-prefix">You can try something like<br>
// CALCULATE VARIANCE OVER LAST N POINTS <br>
<br>
Ni = 100;<br>
Nj = 10;<br>
Nk = 10;<br>
<br>
A = rand(Ni,Nj,Nk); <br>
tic;<br>
A=matrix(A,Ni,-1);//transform A into a 2D array<br>
D1=zeros(Ni-N+1,Nj*Nk);<br>
for i=N:Ni, <br>
D1(i-(N-1),:)=variance(A(i-(N-1):i,:),1);<br>
end<br>
<br>
D1=matrix(D1,-1,Nj,Nk); //Transform D1 into a 3D array<br>
toc<br>
<br>
Are you sure of your variance definition? For me if v is a vector
the variance of v is computed by sqrt(sum( (v-mean(v))^2))<br>
<br>
Serge Steer<br>
INRIA<br>
Le 12/02/2013 17:10, Stéphane Bécu a écrit :<br>
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cite="mid:E9DEEAB2FB6E5A49B6F9FE70D0B8AF301CC785@SRVMAYA.maya.local"
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<div><font color="#000000" face="Arial" size="2">Hello,</font></div>
<div> </div>
<div><font face="Arial" size="2">I have much difficulty to
optimize my calculation. It consists of calculating the
variance of a vector over last N elements . See the example in
the attached file for a 3D matrix. With a PC under windows 7
and scilab 5.3, it needs 40 sec to calculate the variance for
a 10*10*1000 matrix. This is too much long since I have much
bigger files to work on.</font></div>
<div> </div>
<div><font face="Arial" size="2">There must be a way to vectorize
the problem but I do not see how ?</font></div>
<div> </div>
<div><font face="Arial" size="2">Thanks in advance,</font></div>
<div> </div>
<div><font face="Arial" size="2">Stéphane</font></div>
<br>
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