#! /usr/bin/env python
import openturns as ot
import openturns.testing
import persalys
import os
myStudy = persalys.Study('myStudy')
# Model 1
filename = 'data.csv'
ot.RandomGenerator.SetSeed(0)
ot.Normal(3).getSample(10).exportToCSVFile(filename)
inColumns = [0, 2]
model = persalys.DataModel('myDataModel', filename, inColumns)
myStudy.add(model)
print(model)
print("inputNames=", model.getInputNames())
print("outputNames=", model.getOutputNames())
# Data analysis ##
analysis = persalys.DataAnalysis("aDataAnalysis", model)
myStudy.add(analysis)
analysis.run()
result = analysis.getResult()
print("result=", result)
print("PDF=", result.getPDF())
from __future__ import print_function
import openturns as ot
import openturns.testing
import persalys
import os
myStudy = persalys.Study('myStudy')
# data
filename = 'données.csv'
ot.RandomGenerator_SetSeed(0)
ot.Normal(3).getSample(10).exportToCSVFile(filename)
inColumns = [0, 2]
# Model 1
model = persalys.DataModel('myDataModel', filename, inColumns)
myStudy.add(model)
print(model)
# Model 2
model2 = persalys.SymbolicPhysicalModel(
'SM', [persalys.Input('A'), persalys.Input('B')], [persalys.Output('S')],
['A+B+2'])
myStudy.add(model2)
importedDOE = persalys.ImportedDesignOfExperiment('doeI', model2, filename,
inColumns)
myStudy.add(importedDOE)
# script
script = myStudy.getPythonScript()
print(script)
# importDesign ##
importDesign = persalys.ImportedDesignOfExperiment('importDesign', symbolicModel, 'data.csv', [0, 2, 3])
importDesign.run()
myStudy.add(importDesign)
# onePointDesign ##
onePointDesign = persalys.GridDesignOfExperiment('onePointDesign', pythonModel)
myStudy.add(onePointDesign)
# twoPointsDesign ##
twoPointsDesign = persalys.GridDesignOfExperiment('twoPointsDesign', pythonModel, [[0.2], [1.2], [-0.2, 1.]])
myStudy.add(twoPointsDesign)
# fixed DataModel ##
fixedDataModel = persalys.DataModel('fixedDataModel', fixedDesign.getOriginalInputSample(), fixedDesign.getResult().getDesignOfExperiment().getOutputSample())
myStudy.add(fixedDataModel)
# imported DataModel ##
importDataModel = persalys.DataModel('importDataModel', 'data.csv', [0, 2, 3], [1], ['x_0', 'x_2', 'x_3'], ['x_1'])
myStudy.add(importDataModel)
# model evaluation
evaluation1 = persalys.ModelEvaluation('evaluation1', symbolicModel)
myStudy.add(evaluation1)
# morris ##
try:
morris = persalys.MorrisAnalysis('aMorris', symbolicModel)
morris.setInterestVariables(['y0'])
morris.setLevel(4)
import openturns.testing
import persalys
import os
myStudy = persalys.Study('myStudy')
# Model
filename = 'data1.csv'
ot.RandomGenerator.SetSeed(0)
sample = ot.Normal(3).getSample(300)
sample.stack(ot.Gumbel().getSample(300))
sample.setDescription(['X0', 'X1', 'X2', 'X3'])
sample.exportToCSVFile(filename, ',')
columns = [0, 2, 3]
model = persalys.DataModel('myDataModel', "data1.csv", columns)
myStudy.add(model)
print(model)
# Inference analysis ##
analysis = persalys.InferenceAnalysis('analysis', model)
variables = ["X0", "X3"]
analysis.setInterestVariables(variables)
factories = [ot.NormalFactory(), ot.GumbelFactory()]
analysis.setDistributionsFactories("X3", factories)
analysis.setLevel(0.1)
myStudy.add(analysis)
print(analysis)
analysis.run()
model1 = persalys.SymbolicPhysicalModel(
'model1', [x1, x2, x3], [fake_var, y0, fake_y0, y1],
[formula_fake_var, formula_y0, formula_y0, formula_y1])
myStudy.add(model1)
# model 3 ##
filename = 'data.csv'
cDist = ot.ComposedDistribution(
[ot.Normal(), ot.Gumbel(),
ot.Normal(), ot.Uniform()],
ot.ComposedCopula([ot.IndependentCopula(2),
ot.GumbelCopula()]))
sample = cDist.getSample(20)
sample.exportToCSVFile(filename, ' ')
model3 = persalys.DataModel('model3', 'data.csv', [0, 2, 3], [1],
['x_0', 'x_2', 'x_3'], ['x_1'])
myStudy.add(model3)
# Design of Experiment ##
probaDesign = persalys.ProbabilisticDesignOfExperiment('probaDesign', model1,
20, "MONTE_CARLO")
probaDesign.run()
myStudy.add(probaDesign)
# 1- meta model1 ##
# 1-a Kriging ##
kriging = persalys.KrigingAnalysis('kriging', probaDesign)
kriging.setBasis(ot.LinearBasisFactory(2).build())
kriging.setCovarianceModel(ot.MaternModel(2))
