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Hi Chris,
The problem is the step where you interpolate your GP. From this
point on you do not have a discrete but a continuous GP as
modelGP. It has the nice property of being continuous but it is
slow.
I think you can go two ways:
- Either discretize the model you get with modelGP.discretize(refMesh)
- Or you calculate the posterior directly using the function
posterior from the StatisticalMeshModel class
instead of first interpolating it (see the tutorials).
So you would call model.posterior instead of modelGP.posterior
but with different arguments.
Best, Andreas
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val transformationSpace = GaussianProcessTransformationSpace(lowRankGP)
if I pass the discretePosteriorGP here, I get a type mismatch error.
I'm wondering is there something I need to consider?
regards,
Chris