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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
marginals = [ot.Normal(), ot.Uniform()]
R = ot.CorrelationMatrix(2, [1.0, 0.5, 0.5, 1.0])
copula = ot.NormalCopula(R)
factories = [
ot.SoizeGhanemFactory(ot.JointDistribution(marginals)),
ot.SoizeGhanemFactory(ot.JointDistribution(marginals, copula), False),
ot.SoizeGhanemFactory(ot.JointDistribution(marginals, copula), True),
]
x = [0.5] * 2
kMax = 5
ot.ResourceMap.SetAsUnsignedInteger("IteratedQuadrature-MaximumSubIntervals", 2048)
ot.ResourceMap.SetAsScalar("IteratedQuadrature-MaximumError", 1.0e-6)
for soize in factories:
distribution = soize.getMeasure()
print("SoizeGhanem=", soize)
functions = list()
for k in range(kMax):
functions.append(soize.build(k))
print("SoizeGhanem(", k, ")=", functions[k].getEvaluation())
print("SoizeGhanem(", k, ")(", x, "=", functions[k](x))
M = ot.SymmetricMatrix(kMax)
for m in range(kMax):
for n in range(m + 1):
def wrapper(x):
return functions[m](x) * functions[n](x)[0] * distribution.computePDF(x)
kernel = ot.PythonFunction(distribution.getDimension(), 1, wrapper)
value = ot.IteratedQuadrature().integrate(kernel, distribution.getRange())[
0
]
if abs(value) >= 1.0e-6:
M[m, n] = value
print("M=\n", M)
# Test isTensorProduct(), case True
sgTensorProduct = ot.SoizeGhanemFactory(ot.JointDistribution(marginals))
assert sgTensorProduct.isTensorProduct()
# Test isTensorProduct(), case False
sgTensorProduct = ot.SoizeGhanemFactory(ot.JointDistribution(marginals, copula))
assert not sgTensorProduct.isTensorProduct()
# Test getMarginal
basis = ot.SoizeGhanemFactory(ot.JointDistribution(marginals))
basisMarginal = basis.getMarginal([0])
for i in range(20):
function = basisMarginal.build(i)
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