Hi all,
The getWeights() method will be deprecated. You should use the
generateWithWeights() method to get the points and the weights. Nevertheless,
the attached script works well using both generate() then getWeights() or
generateWithWeights() with OT 1.7
Regards,
Régis
----- Mail original -----
> De : BLATMAN Geraud <[email protected]>
> À : "[email protected]" <[email protected]>
> Cc : "[email protected]" <[email protected]>
> Envoyé le : Mercredi 15 juin 2016 17h30
> Objet : Re: [ot-users] OpenTURNS - How to get the weights of a quadrature
> rule?
>
> Hi Denis,
>
> Unfortunately this does not change the results... I have also tried : myExp.
> generateWithWeights(), but the returned weights are still constant and equal
> to
> 1/N.
>
>
>
>
> Geraud BLATMAN
> Ingénieur-chercheur
> EDF - R&D
> Matériaux et Mécanique des Composants
> Groupe T24 - Équipe Études Probabilistes
> EDF Lab Les Renardières - Écuelles
> 77818 Moret-Sur-Loing Cedex
>
> [email protected]
> Tél. : 01 60 73 70 39
>
>
> -----Message d'origine-----
> De : [email protected] [mailto:[email protected]]
> Envoyé : mercredi 15 juin 2016 17:14
> À : BLATMAN Geraud
> Cc : [email protected]
> Objet : Re: [ot-users] OpenTURNS - How to get the weights of a quadrature
> rule?
>
> On 2016-06-15 11:38 GMT+02:00 BLATMAN Geraud wrote:
>>
>> Dear users,
>>
>> I am wondering how to obtain the weights related to a Gauss quadrature rule
> in OpenTURNS. These weights should be computed somewhere since Gauss
> quadrature
> can be used to estimate the coefficients of a polynomial chaos expansion, as
> shown by the following commands taken from the Use Cases Guide (Section
> 4.3.4) :
>>
>> >>> marginalDegrees = [2] * dim
>> >>> evaluationCoeffStrategy_3 = IntegrationStrategy(
> GaussProductExperiment(distributionMu, marginalDegrees))
>>
>> So I have tried to retrieve the weights from the ‘GaussProductExperiment’
> object as follows :
>>
>> >>> myExp = GaussProductExperiment(distributionMu,
> marginalDegrees)
>> >>> weights = myExp.getWeight()
>>
>> However I always get weights all equal to 1/N (N being the sample size),
> whatever the distribution (parameter ‘distributionMu’). For instance, if this
> distribution is a collection of independent uniform variables over [-1,1], I
> would rather expect the well-known Gauss-Legendre quadrature weights.
>>
>> Any ideas ?
>
> Hello, it seems that weights are computed only after myExp.generate() is
> being
> called. This is annoying, but not trivial to fix.
>
> Denis
>
>
>
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import openturns as ot
distribution = ot.ComposedDistribution([ot.Exponential(), ot.Triangular(-1.0, -0.5, 1.0)])
marginalDegrees = [3, 2]
myPlane = ot.GaussProductExperiment(distribution, marginalDegrees)
print "sample=", myPlane.generate()
print "weights=", myPlane.getWeight()
sample, weights = myPlane.generateWithWeights()
print "sample=", sample
print "weights=", weights
sample= [ marginal_1_marginal 1 marginal_2_marginal 1 ]
0 : [ 0.415775 -0.511215 ]
1 : [ 2.29428 -0.511215 ]
2 : [ 6.28995 -0.511215 ]
3 : [ 0.415775 0.357369 ]
4 : [ 2.29428 0.357369 ]
5 : [ 6.28995 0.357369 ]
weights= [0.429018,0.168036,0.00626806,0.282075,0.110482,0.00412119]
sample= [ marginal_1_marginal 1 marginal_2_marginal 1 ]
0 : [ 0.415775 -0.511215 ]
1 : [ 2.29428 -0.511215 ]
2 : [ 6.28995 -0.511215 ]
3 : [ 0.415775 0.357369 ]
4 : [ 2.29428 0.357369 ]
5 : [ 6.28995 0.357369 ]
weights= [0.429018,0.168036,0.00626806,0.282075,0.110482,0.00412119]
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