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#! /usr/bin/env python
import openturns as ot
# Tests
ot.ResourceMap.SetAsUnsignedInteger("SimulationAlgorithm-DefaultBlockSize", 100)
ot.ResourceMap.SetAsUnsignedInteger(
"SimulationAlgorithm-DefaultMaximumOuterSampling", 100
)
ot.ResourceMap.SetAsScalar(
"SimulationAlgorithm-DefaultMaximumCoefficientOfVariation", 0.0
)
ot.ResourceMap.SetAsScalar("SimulationAlgorithm-DefaultMaximumStandardDeviation", 0.0)
ot.ResourceMap.SetAsScalar("RootStrategy-DefaultStepSize", 0.1)
algorithms = ["MonteCarlo", "LHS", "QuasiMonteCarlo", "DirectionalSampling"]
inDim = 4
X = ot.RandomVector(ot.Normal(inDim))
inVars = ot.Description.BuildDefault(inDim, "x")
low = 1.0
up = 2.0
intervals = [
ot.Interval([low], [up], [True], [False]),
ot.Interval([low], [up], [False], [True]),
ot.Interval([low], [up], [True], [True]),
ot.Interval([low], [up], [False], [False]),
ot.Interval([low] * 2, [up] * 2, [True, True], [True, True]),
ot.Interval([low] * 2, [up] * 2, [True, True], [True, False]),
ot.Interval([low] * 2, [up] * 2, [True, True], [False, True]),
ot.Interval([low] * 2, [up] * 2, [True, True], [False, False]),
ot.Interval([low] * 2, [up] * 2, [True, False], [True, True]),
ot.Interval([low] * 2, [up] * 2, [True, False], [True, False]),
ot.Interval([low] * 2, [up] * 2, [True, False], [False, True]),
ot.Interval([low] * 2, [up] * 2, [True, False], [False, False]),
ot.Interval([low] * 2, [up] * 2, [False, True], [True, True]),
ot.Interval([low] * 2, [up] * 2, [False, True], [True, False]),
ot.Interval([low] * 2, [up] * 2, [False, True], [False, True]),
ot.Interval([low] * 2, [up] * 2, [False, True], [False, False]),
ot.Interval([low] * 2, [up] * 2, [False, False], [True, True]),
ot.Interval([low] * 2, [up] * 2, [False, False], [True, False]),
ot.Interval([low] * 2, [up] * 2, [False, False], [False, True]),
ot.Interval([low] * 2, [up] * 2, [False, False], [False, False]),
]
for domain in intervals:
print("#" * 50)
print("domain=\n", domain)
outDim = domain.getDimension()
f = ot.SymbolicFunction(inVars, inVars[0:outDim])
Y = ot.CompositeRandomVector(f, X)
event = ot.ThresholdEvent(Y, domain)
ot.RandomGenerator.SetSeed(0)
# algo = getattr(openturns, algoName)(event)
algo = ot.ProbabilitySimulationAlgorithm(event, ot.MonteCarloExperiment())
algo.run()
res = algo.getResult().getProbabilityEstimate()
print("MC p=%.6g" % res)
ot.RandomGenerator.SetSeed(0)
# algo = getattr(openturns, algoName)(event)
algoOptim = ot.Cobyla()
algoOptim.setMaximumConstraintError(1)
algo = ot.FORM(algoOptim, event, X.getMean())
algo.run()
res = algo.getResult().getEventProbability()
print("FORM p=%.2f" % res)
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