Hi Roy,
We will probably enhance the experiment class. It may reduce 2N evaluations,
which is substantial (only in 2d case)
What do you mean by "not computed correctly" in your mail? Are you talking
about generated experiment or post processing (SaltelliSensitivityAlgorithm?)
Sofiane
Le jeudi 7 décembre 2017 à 10:42:29 UTC+1, roy <[email protected]> a écrit :
Hi Sofiane,
Thanks for the update.
Do you plan to have it implemented on OT? Or should I handle this in my package?
Also, I have a last interrogation. When I create the sample with
SobolIndicesExperiment,I found that Sobol' indices are not always computed
correctly. I am not able to provide a MCVE here asfrom the sample generation to
the computation of the indices, a lot happens. Sorry.But from my trying, if I
set OT’s seed, I get correct results.
So is there a way to ensure that the sample generated by SobolIndicesExperiment
will correspond towhat is expected by the indices classes? Seems that there is
a randomization effect here.
Thanks again for the support.
Sincerely,
Pamphile ROY
Le 7 déc. 2017 à 00:39, HADDAD Sofiane <[email protected]> a écrit :
Hi
You are right only the case dim=2 has duplicates if compute second order is
set tot True.
I miss it, sorry!
An enhancement is to generate samples of size N * (dim + 1) in case dim=2
whatever second order is True or False
Thanks for the report.
Regards,Sofiane
Le samedi 2 décembre 2017 à 13:25:25 UTC+1, Pamphile ROY <[email protected]>
a écrit :
Hi Sofiane,
I got it now.
But if in 2dim this behavior is to be expected, why not doing this
internally?The root of this was that I have an expensive numerical model. So
having to compute twice a sample is not tractable.
Thanks for your support.
Sincerely,
Pamphile ROYDe: "HADDAD Sofiane" <[email protected]>
À: "users" <[email protected]>, "roy" <[email protected]>
Envoyé: Vendredi 1 Décembre 2017 13:31:14
Objet: Re: [ot-users] duplicate with SobolIndicesExperiment
Hi
There is no problem here
You can find here how the experiment is defined. As you set second order to
True and your sub samples are of size 5, you have (2 * 2 + 2) blocks of size 5
Have a look at SobolIndicesAlgorithm — OpenTURNS documentation
|
|
| |
SobolIndicesAlgorithm — OpenTURNS documentation
|
|
|
Using this :import openturns as otot.RandomGenerator.SetSeed(0)distribution =
ot.ComposedDistribution([ot.Uniform(15, 60), ot.Normal(3000, 400)])sample =
np.array(ot.SobolIndicesAlgorithmImplementation.Generate(distribution, 5,
True))print(sample.reshape(-1,5,2))
you will see all matrices defines in link.Hope this helps
Bien cordialement,
Sofiane HADDAD
Le mercredi 29 novembre 2017 à 19:30:39 UTC+1, roy <[email protected]> a
écrit :
Hi,
I am using ot.SobolIndicesExperiment and if I set my input dimension to 2,I get
some repeated points. From my understanding of the method, this should not be
the case.Also going with a higher dimension does not do that.
Am I wrong?
Here is an example (same behaviour with the old method available in OT 1.9)
where I highlighted some duplicate:
import openturns as otdistribution = ot.ComposedDistribution([ot.Uniform(15,
60), ot.Normal(3000, 400)])sample =
np.array(ot.SobolIndicesAlgorithmImplementation.Generate(distribution, 5, True))
array([[ 29.65970938, 2535.47991432], [ 33.01991727,
2559.28624639], [ 33.25474751, 2682.95080229], [ 32.95380182,
2419.44678937], [ 55.23575378, 3039.33121131], [ 26.05095231,
3271.18330661], [ 41.00594229, 3683.75154513], [ 54.81729255,
3428.24812578], [ 28.2423326 , 2797.23010815], [ 52.36310769,
2335.65441869], [ 26.05095231, 2535.47991432], [ 41.00594229,
2559.28624639], [ 54.81729255, 2682.95080229], [ 28.2423326 ,
2419.44678937], [ 52.36310769, 3039.33121131], [ 29.65970938,
3271.18330661], [ 33.01991727, 3683.75154513], [ 33.25474751,
3428.24812578], [ 32.95380182, 2797.23010815], [ 55.23575378,
2335.65441869], [ 29.65970938, 3271.18330661], [ 33.01991727,
3683.75154513], [ 33.25474751, 3428.24812578], [ 32.95380182,
2797.23010815], [ 55.23575378, 2335.65441869], [ 26.05095231,
2535.47991432], [ 41.00594229, 2559.28624639], [ 54.81729255,
2682.95080229], [ 28.2423326 , 2419.44678937], [ 52.36310769,
3039.33121131]])
Thanks for your support.
Sincerely,
Pamphile ROY
PhD candidate in Uncertainty Quantification
CERFACS - Toulouse (31) - France
+33 (0) 5 61 19 31 57
+33 (0) 7 86 43 24 22
_______________________________________________
OpenTURNS users mailing list
[email protected]
http://openturns.org/mailman/listinfo/users
_______________________________________________
OpenTURNS users mailing list
[email protected]
http://openturns.org/mailman/listinfo/users
