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#! /usr/bin/env python
import openturns as ot
import persalys
myStudy = persalys.Study("myStudy")
# Model
X0 = persalys.Input("X0", ot.Normal(1, 1))
X1 = persalys.Input("X1", ot.Normal(1, 1))
Y00 = persalys.Output("fake_Y0")
Y00.setIsSelected(False)
Y0 = persalys.Output("Y0")
formula_Y00 = "X0"
formula_Y0 = "sin(X0) + 8*X1"
model = persalys.SymbolicPhysicalModel(
"aModelPhys", [X0, X1], [Y00, Y0], [formula_Y00, formula_Y0]
)
myStudy.add(model)
# Monte Carlo ##
analysis = persalys.MonteCarloAnalysis("myMonteCarlo", model)
analysis.setLevelConfidenceInterval(0.93)
analysis.setMaximumCalls(1000)
analysis.setMaximumCoefficientOfVariation(-1)
analysis.setMaximumElapsedTime(30)
analysis.setSeed(2)
myStudy.add(analysis)
print(analysis)
analysis.run()
result = analysis.getResult()
print("result=", result)
print("PDF=", result.getPDF())
print("CDF=", result.getCDF())
print("outliers=", result.getOutliers())
# Monte Carlo ##
analysis2 = persalys.MonteCarloAnalysis("myMonteCarlo2", model)
analysis2.setIsConfidenceIntervalRequired(False)
analysis2.setMaximumCoefficientOfVariation(0.02)
analysis2.setMaximumElapsedTime(100000)
analysis2.setBlockSize(100)
myStudy.add(analysis2)
print(analysis2)
analysis2.run()
result2 = analysis2.getResult()
print("result=", result2)
print("PDF=", result2.getPDF())
print("CDF=", result2.getCDF())
print("outliers=", result2.getOutliers())
# Monte Carlo ##
X2 = persalys.Input("X2", 2)
model.addInput(X2)
model.addOutput(persalys.Output("Y1"))
model.setFormula("Y1", "sin(X0) + 8*X1 + X2")
analysis3 = persalys.MonteCarloAnalysis("myMonteCarlo3", model)
analysis3.setMaximumCalls(1000)
analysis3.setInterestVariables(["Y1"])
myStudy.add(analysis3)
print(analysis3)
analysis3.run()
result3 = analysis3.getResult()
print("result=", result3)
# script
script = myStudy.getPythonScript()
print(script)
exec(script)
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