Hi Anita,
It totally looks like some works has been initiated for the mean point in DS, this goes back to release 0.14.0.
I'll see what I can do.
j
De : Anita Laera <[email protected]>
Envoyé : vendredi 4 août 2017 12:24:55
À : Julien Schueller | Phimeca
Cc : users
Objet : Re: [ot-users] directional sampling - mean point in event domain + importance factors
Envoyé : vendredi 4 août 2017 12:24:55
À : Julien Schueller | Phimeca
Cc : users
Objet : Re: [ot-users] directional sampling - mean point in event domain + importance factors
Thank you Julien, but for both computeMeanPointInEventDomain and
computeImportanceFactors it is written:
"Be careful: this notion is only valid for ![\vect{X}_i]()
."
MonteCarlo or LHS sampling
as the mean is evaluated from the equation (2)(only
uniform weights over the realizations while I am using Directional Sampling.
2017-08-04 12:19 GMT+02:00 Julien Schueller | Phimeca
<[email protected]>:
Hi Anita,
You may want to use SimulationSensitivityAnalysis:
j
De : [email protected] <[email protected]> de la part de Anita Laera <[email protected]>
Envoyé : jeudi 3 août 2017 11:39:36
À : users
Objet : [ot-users] directional sampling - mean point in event domain + importance factorsHi all,I am using Directional Sampling in OpenTURNS.In the documentation, it is specified that it is not possible to get the mean point in event domain and the importance factors through the class SimulationResults (as for Monte Carlo). Why?
By looking at the DirectionalSampling.cxx file, I can see that the computation of the mean point in event domain is commented out:
// meanPointInEventDomain = meanPointInEventDomain + computeMeanContribution(roots) * direction;++contributionNumber;} // if contribution}// meanPointInEventDomain = meanPointInEventDomain * (1.0 / contributionNumber);
Why? Is there a way to calculate them?
Thank you,Anita
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