I guess it doesn't matter, but typical n are 1...1000. However, I need to call the operation hundreds or thousands times (while running NLP solver ralg, so 4..5 * nIter times). Number of zeros can be 0...n-1 Charles R Harris wrote:

How big is n?

On Dec 14, 2007 1:24 AM, dmitrey mailto:dmitrey.kroshko@scipy.org> wrote:

Hi all, I have to get Ax, A is n x n matrix, x is vector of length n. Some coords of x are zeros, so I want to economy time/cputime somehow w/o connecting sparse module from scipy. What's the easiest way to do so?

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Thank you for the tip, however, I expect being vector of length n A and x change every iter. A is not sparse. Alan G Isaac wrote:

On Fri, 14 Dec 2007, dmitrey apparently wrote:

...

I guess it doesn't matter, but typical n are 1...1000. However, I need to call the operation hundreds or thousands times (while running NLP solver ralg, so 4..5 * nIter times). Number of zeros can be 0...n-1

Do both A and x change every iteration?

Anyway, if x is sparse I think you'll get some benefit by doing idx=N.ravel(x)!=0 A[:,idx]*x[idx]

hth, Alan Isaac

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Hi, How sparse are A, x and Ax? You probably will not find any time or operation efficiency unless A and x are relatively sparse. With the small size of n, any efficiency will typically be small in any case. As you indicate that this has to be repeated multiple times, perhaps you should look at your overall algorithm for efficiencies. Bruce On Dec 14, 2007 3:44 AM, dmitrey wrote:

I guess it doesn't matter, but typical n are 1...1000. However, I need to call the operation hundreds or thousands times (while running NLP solver ralg, so 4..5 * nIter times). Number of zeros can be 0...n-1

Charles R Harris wrote:

...

How big is n?

On Dec 14, 2007 1:24 AM, dmitrey mailto:dmitrey.kroshko@scipy.org> wrote:

Hi all, I have to get Ax, A is n x n matrix, x is vector of length n. Some coords of x are zeros, so I want to economy time/cputime somehow w/o connecting sparse module from scipy. What's the easiest way to do so?

Thx, D. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org mailto:Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion

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