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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
dimension = 3
# Create the orthogonal basis
enumerateFunction = ot.LinearEnumerateFunction(dimension)
productBasis = ot.OrthogonalProductPolynomialFactory(
[ot.LegendreFactory()] * dimension, enumerateFunction
)
degree = 6
basisSize = enumerateFunction.getBasisSizeFromTotalDegree(degree)
maximumDimension = 100
maximumSize = 20
significanceFactor = 1e-4
adaptiveStrategy = ot.CleaningStrategy(
productBasis, maximumDimension, maximumSize, significanceFactor
)
assert adaptiveStrategy.involvesModelSelection() is True
adaptiveStrategy.computeInitialBasis()
assert adaptiveStrategy.getCurrentVectorIndex() == 20
psi = adaptiveStrategy.getPsi()
assert len(psi) == 20
alpha_k = [3.5, 0.1, 0.0, -0.2, 0.0, 0.3, 0.0, -0.4, 0.0, -0.5]
residual = 0.0
relativeError = 0.0
adaptiveStrategy.updateBasis(alpha_k, residual, relativeError)
psi = adaptiveStrategy.getPsi()
assert len(psi) == 7
assert adaptiveStrategy.getCurrentVectorIndex() == 21
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