[0, 2])
anOTStudy.add(aDesign2)
aDesign2.run()
print('outs=', aDesign2.getResult().getDesignOfExperiment().getOutputSample())
# Design of Experiment ##
aDesign3 = persalys.ProbabilisticDesignOfExperiment('aDesign_3', model, 10,
'QUASI_MONTE_CARLO')
anOTStudy.add(aDesign3)
aDesign3.run()
print('outs=', aDesign3.getResult().getDesignOfExperiment().getOutputSample())
# Design of Experiment ##
aDesign4 = persalys.FixedDesignOfExperiment('aDesign_4', model)
inputSample = ot.LHSExperiment(model.getDistribution(), 10).generate()
#inputSample.stack(ot.Sample(10, [0.5, 1.3]))
aDesign4.setOriginalInputSample(inputSample)
anOTStudy.add(aDesign4)
aDesign4.run()
print('outs=', aDesign4.getResult().getDesignOfExperiment().getOutputSample())
# 3D Model to test Space filling algos
X0 = persalys.Input('X0', 1, ot.Normal())
X1 = persalys.Input('X1', 2, ot.Normal())
X2 = persalys.Input('X2', 3, ot.Normal())
Y0 = persalys.Output('Y0')
xi2 = persalys.Input('xi2', ot.Uniform(0., 10.))
xi3 = persalys.Input('xi3', 0.5)
y00 = persalys.Output('fake_y0')
y00.setIsSelected(False)
y0 = persalys.Output('y0')
y1 = persalys.Output('y1')
formula_y00 = "xi1"
formula_y0 = "cos(0.5*xi1) + sin(xi2)"
formula_y1 = "cos(0.5*xi1) + sin(xi2) + xi3"
model = persalys.SymbolicPhysicalModel('model', [xi1, xi2, xi3], [y00, y0, y1], [
formula_y00, formula_y0, formula_y1])
myStudy.add(model)
# Design of Experiment ##
aDesign = persalys.FixedDesignOfExperiment('design', model)
inputSample = ot.LHSExperiment(model.getDistribution(), 50).generate()
inputSample.stack(ot.Sample(50, [0.5]))
aDesign.setOriginalInputSample(inputSample)
myStudy.add(aDesign)
aDesign.run()
# Chaos 1 ##
analysis = persalys.FunctionalChaosAnalysis('chaos_0', aDesign)
analysis.setChaosDegree(4)
analysis.setSparseChaos(True)
myStudy.add(analysis)
print(analysis)
analysis.run()
# python model ##
code = 'from math import cos, sin, sqrt\n\ndef _exec(x1, x2, x3):\n y0 = cos(0.5*x1) + sin(x2) + sqrt(x3)\n return y0\n'
pythonModel = persalys.PythonPhysicalModel('pythonModel', [x1, x2, x3], [y0], code)
myStudy.add(pythonModel)
filename = 'data.csv'
cDist = ot.ComposedDistribution([ot.Normal(), ot.Gumbel(), ot.Normal(), ot.Uniform()],
ot.ComposedCopula([ot.IndependentCopula(2), ot.GumbelCopula()]))
sample = cDist.getSample(200)
sample.exportToCSVFile(filename, ' ')
# Designs of Experiment ##
# fixed design ##
ot.RandomGenerator.SetSeed(0)
fixedDesign = persalys.FixedDesignOfExperiment('fixedDesign', symbolicModel)
inputSample = ot.LHSExperiment(ot.ComposedDistribution([ot.Uniform(0., 10.), ot.Uniform(0., 10.)]), 10).generate()
inputSample.stack(ot.Sample(10, [0.5]))
fixedDesign.setOriginalInputSample(inputSample)
fixedDesign.run()
myStudy.add(fixedDesign)
# grid ##
values = [[0.5+i*1.5 for i in range(7)], [0.5+i*1.5 for i in range(7)], [1]]
grid = persalys.GridDesignOfExperiment('grid', symbolicModel, values)
myStudy.add(grid)
# importDesign ##
importDesign = persalys.ImportedDesignOfExperiment('importDesign', symbolicModel, 'data.csv', [0, 2, 3])
importDesign.run()
myStudy.add(importDesign)
'from math import pi\n\ndef _exec(R, F):\n G = 6*F\n H = 42.0\n return G, H\n')
f = model.getFunction()
print(f([300., 75000.]))
# test operator() (sample)
model.setCode(
'from math import pi\n\ndef _exec(R, F):\n G = 2*R-F/(pi*100.0)\n return G\n')
f = model.getFunction()
print(f([[300., 75000.]]))
print(f([[300., 75000.], [400., 74000.]]))
# test operator() (sample)
model.setCode(
'from math import pi\nimport time\ndef _exec(R, F):\n if R == 300.:\n time.sleep(0.5)\n G = 2*R-F/(pi*100.0)\n return G\n')
plan_0 = persalys.FixedDesignOfExperiment('plan_0', model, [[300., 75000.], [400., 74000.]])
plan_0.setBlockSize(2)
myStudy.add(plan_0)
plan_0.run()
print("Sample :\n %s" % plan_0.getResult().getDesignOfExperiment().getSample())
# model with an error
model.setCode(
'from math import pi\n\ndef _exec(R, F):\n G = 2*R-F/(pi*100.0)/0.\n return G\n')
f = model.getFunction()
try:
print(f([[300., 75000.]]))
except Exception as e:
print("ZeroDivisionError occured: %s" % ("ZeroDivisionError: float division by zero" in str(e)))
print("Error on the line 4 : %s" % ("line 4" in str(e)))
#! /usr/bin/env python
import openturns as ot
import persalys
import os
# Model with error
X0 = persalys.Input('X0', 1, ot.Normal())
X1 = persalys.Input('X1', 2)
Y0 = persalys.Output('Y0')
Y1 = persalys.Output('Y1')
model2 = persalys.PythonPhysicalModel('model2', [X0, X1], [Y0], 'from math import pi\n\ndef _exec(X0, X1):\n Y0 = 2*X1 - 1/X0\n return Y0\n')
model2.setParallel(True)
design5 = persalys.FixedDesignOfExperiment('design5', model2)
design5.setOriginalInputSample([[0.9, 1.1], [1.8, 2.2], [0, 2.2]])
design5.setBlockSize(3)
design5.run()
assert design5.getResult().getDesignOfExperiment().getOutputSample().getSize() == 2, "whole block must no fail"
model3 = persalys.PythonPhysicalModel('model3', [X0, X1], [Y0, Y1], 'from math import pi\n\ndef _exec(X0, X1):\n Y0 = 2*X1 - 1/X0\n Y1=5\n return Y0, Y1\n')
model3.setParallel(True)
# same with multiple outputs
design6 = persalys.FixedDesignOfExperiment('design6', model3)
design6.setInterestVariables(['Y0'])
design6.setOriginalInputSample([[0.9, 1.1], [1.8, 2.2], [0, 2.2]])
design6.setBlockSize(3)
design6.run()
assert design6.getResult().getDesignOfExperiment().getOutputSample().getSize() == 2, "whole block must no fail"
