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#! /usr/bin/env python
import openturns as ot
import openturns.testing
import persalys
import os
myStudy = persalys.Study("myStudy")
# Model
filename = "data2.csv"
ot.RandomGenerator.SetSeed(0)
R = ot.CorrelationMatrix(4)
R[0, 3] = 0.9
distribution = ot.JointDistribution([ot.Normal(), ot.Normal(), ot.Normal(), ot.Gumbel()], ot.NormalCopula(R))
sample = distribution.getSample(300)
sample.setDescription(["X0", "X1", "X2", "X3"])
sample.exportToCSVFile(filename, ",")
columns = [0, 2, 3]
model = persalys.DataModel("myDataModel", "data2.csv", columns)
myStudy.add(model)
print(model)
# Dependencies inference analysis ##
analysis = persalys.CopulaInferenceAnalysis("analysis", model)
variables = ["X0", "X3"]
factories = [ot.ClaytonCopulaFactory(),
ot.FrankCopulaFactory(),
ot.GumbelCopulaFactory(),
ot.NormalCopulaFactory(),
ot.StudentCopulaFactory()]
analysis.setDistributionsFactories(variables, factories)
myStudy.add(analysis)
print(analysis)
analysis.run()
result = analysis.getResult()
inferenceSet = result.getCopulaInferenceSetResult(variables)
print(inferenceSet.getBICResults())
# script
script = myStudy.getPythonScript()
print(script)
exec(script)
os.remove(filename)
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