from openturns.viewer import View
thetaDist = ot.Normal(2.0, 0.1)
if 'VarianceMeasure' == 'WorstCaseMeasure':
thetaDist = ot.Uniform(-1.0, 4.0)
elif 'ChanceMeasure' in 'VarianceMeasure':
thetaDist = ot.Normal(1.0, 1.0)
f_base = ot.Function(['x', 'theta'], ['y'], ['x*theta'])
f = ot.Function(f_base, [1], thetaDist.getMean())
if 'VarianceMeasure' == 'JointChanceMeasure':
measure = otrobopt.JointChanceMeasure(f, thetaDist, ot.GreaterOrEqual(),
0.95)
elif 'VarianceMeasure' == 'IndividualChanceMeasure':
measure = otrobopt.IndividualChanceMeasure(f, thetaDist,
ot.GreaterOrEqual(), [0.95])
elif 'VarianceMeasure' == 'MeanStandardDeviationTradeoffMeasure':
measure = otrobopt.MeanStandardDeviationTradeoffMeasure(
f, thetaDist, [0.8])
elif 'VarianceMeasure' == 'QuantileMeasure':
measure = otrobopt.QuantileMeasure(f, thetaDist, 0.99)
else:
measure = otrobopt.VarianceMeasure(f, thetaDist)
N = 10
experiment = ot.LHSExperiment(N)
factory = otrobopt.MeasureFactory(experiment)
discretizedMeasure = factory.build(measure)
continuous_measure = otrobopt.MeasureFunction(measure)
discretized_measure = otrobopt.MeasureFunction(discretizedMeasure)
import otrobopt
# First test: theta of dimension 1
thetaDist = ot.Normal(2.0, 0.1)
f_base = ot.SymbolicFunction(['x', 'theta'], ['x*theta'])
f = ot.ParametricFunction(f_base, [1], [1.0])
x = [1.0]
measures = [otrobopt.MeanMeasure(f, thetaDist),
otrobopt.VarianceMeasure(f, thetaDist),
otrobopt.WorstCaseMeasure(f, ot.Uniform(-1.0, 4.0)),
otrobopt.WorstCaseMeasure(f, ot.Uniform(-1.0, 4.0), False),
otrobopt.JointChanceMeasure(
f, ot.Normal(1.0, 1.0), ot.GreaterOrEqual(), 0.95),
otrobopt.IndividualChanceMeasure(
f, ot.Normal(1.0, 1.0), ot.GreaterOrEqual(), [0.95]),
otrobopt.MeanStandardDeviationTradeoffMeasure(f, thetaDist, [0.8]),
otrobopt.QuantileMeasure(f, thetaDist, 0.99)
]
aggregated = otrobopt.AggregatedMeasure(measures)
measures.append(aggregated)
for measure in measures:
print(measure, '(continuous)', measure(x))
N = 10000
experiment = ot.LHSExperiment(N)
factory = otrobopt.MeasureFactory(experiment)
discretizedMeasure = factory.build(measure)
print(discretizedMeasure, '(discretized LHS)', discretizedMeasure(x))
N = 4
experiment = ot.GaussProductExperiment([N])