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 ot
distribution = 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
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