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class=KrigingAnalysis name=kriging_0 designOfExperiment=design interestVariables=[y0] analyticalValidation=true testSampleValidation=false kFoldValidation=false leaveOneOutValidation=false test sample parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Percentage,Seed] values=[20,0] k-Fold parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Number of folds,Seed] values=[5,0] basis=class=Basis coll=[class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=class=LinearEvaluation name=Unnamed center=class=Point name=Unnamed dimension=2 values=[0,0] constant=class=Point name=Unnamed dimension=1 values=[1] linear=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] gradientImplementation=class=ConstantGradient name=Unnamed constant=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] hessianImplementation=class=NullHessian name=Unnamed inputDimension=2 outputDimension=1,class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=class=LinearEvaluation name=Unnamed center=class=Point name=Unnamed dimension=2 values=[0,0] constant=class=Point name=Unnamed dimension=1 values=[0] linear=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[1,0] gradientImplementation=class=ConstantGradient name=Unnamed constant=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[1,0] hessianImplementation=class=NullHessian name=Unnamed inputDimension=2 outputDimension=1,class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=class=LinearEvaluation name=Unnamed center=class=Point name=Unnamed dimension=2 values=[0,0] constant=class=Point name=Unnamed dimension=1 values=[0] linear=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,1] gradientImplementation=class=ConstantGradient name=Unnamed constant=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,1] hessianImplementation=class=NullHessian name=Unnamed inputDimension=2 outputDimension=1] covarianceModel=class=MaternModel scale=class=Point name=Unnamed dimension=2 values=[1,1] amplitude=class=Point name=Unnamed dimension=1 values=[1] nu=1.5 optimizeParameters=true
class=KrigingAnalysis name=kriging_1 designOfExperiment=design interestVariables=[y1,y0] analyticalValidation=true testSampleValidation=false kFoldValidation=false leaveOneOutValidation=false test sample parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Percentage,Seed] values=[20,0] k-Fold parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Number of folds,Seed] values=[5,0] basis=class=Basis coll=[class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=class=LinearEvaluation name=Unnamed center=class=Point name=Unnamed dimension=2 values=[0,0] constant=class=Point name=Unnamed dimension=1 values=[1] linear=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] gradientImplementation=class=ConstantGradient name=Unnamed constant=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] hessianImplementation=class=NullHessian name=Unnamed inputDimension=2 outputDimension=1] covarianceModel=class=SquaredExponential scale=class=Point name=Unnamed dimension=2 values=[1,1] amplitude=class=Point name=Unnamed dimension=1 values=[1] optimizeParameters=true
class=KrigingAnalysis name=kriging_2 designOfExperiment=design interestVariables=[y0] analyticalValidation=true testSampleValidation=false kFoldValidation=false leaveOneOutValidation=false test sample parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Percentage,Seed] values=[20,0] k-Fold parameters=class=PointWithDescription name=Unnamed dimension=2 description=[Number of folds,Seed] values=[5,0] basis=class=Basis coll=[class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=class=LinearEvaluation name=Unnamed center=class=Point name=Unnamed dimension=2 values=[0,0] constant=class=Point name=Unnamed dimension=1 values=[1] linear=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] gradientImplementation=class=ConstantGradient name=Unnamed constant=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=1 values=[0,0] hessianImplementation=class=NullHessian name=Unnamed inputDimension=2 outputDimension=1] covarianceModel=class=SquaredExponential scale=class=Point name=Unnamed dimension=2 values=[1,1] amplitude=class=Point name=Unnamed dimension=1 values=[1] optimizeParameters=false
result= class=KrigingAnalysisResult krigingResultCollection=[KrigingResult(covariance models=SquaredExponential(scale=[1,1], amplitude=[1]), covariance coefficients=0 : [ 0.621384 ]
1 : [ 0.472278 ]
2 : [ -1.38309 ]
3 : [ -1.50168 ]
4 : [ -2.12515 ]
5 : [ 1.83574 ]
6 : [ -2.10243 ]
7 : [ 2.58837 ]
8 : [ -1.15284 ]
9 : [ 2.74742 ], basis=[Basis( [class=LinearEvaluation name=Unnamed center=[0,0] constant=[1] linear=[[ 0 ]
[ 0 ]]] )], trend coefficients=[[0.208352]])]
#!/usr/bin/env python
import openturns as ot
import persalys
myStudy = persalys.Study('myStudy')
persalys.Study.Add(myStudy)
dist_xi1 = ot.Uniform(0, 10)
xi1 = persalys.Input('xi1', 0, dist_xi1, '')
dist_xi2 = ot.Uniform(0, 10)
xi2 = persalys.Input('xi2', 0, dist_xi2, '')
xi3 = persalys.Input('xi3', 0.5, '')
fake_y0 = persalys.Output('fake_y0', '')
fake_y0.setIsSelected(False)
y0 = persalys.Output('y0', '')
y1 = persalys.Output('y1', '')
inputs = [xi1, xi2, xi3]
outputs = [fake_y0, y0, y1]
formulas = ['xi1', 'cos(0.5*xi1) + sin(xi2)', 'cos(0.5*xi1) + sin(xi2) + xi3']
model = persalys.SymbolicPhysicalModel('model', inputs, outputs, formulas)
myStudy.add(model)
design = persalys.FixedDesignOfExperiment('design', model)
inputSample = [
[4.68457, 6.82803, 0.5],
[0.359802, 4.95475, 0.5],
[6.58862, 8.18204, 0.5],
[9.08578, 5.66073, 0.5],
[7.21044, 2.38623, 0.5],
[1.02456, 0.418919, 0.5],
[2.98184, 3.91613, 0.5],
[5.9556, 7.47295, 0.5],
[3.25986, 9.66134, 0.5],
[8.48977, 1.46852, 0.5]]
design.setOriginalInputSample(inputSample)
design.setBlockSize(1)
interestVariables = ['y0', 'y1']
design.setInterestVariables(interestVariables)
myStudy.add(design)
kriging_0 = persalys.KrigingAnalysis('kriging_0', design)
interestVariables = ['y0']
kriging_0.setInterestVariables(interestVariables)
kriging_0.setBasis(ot.LinearBasisFactory(2).build())
kriging_0.setCovarianceModel(ot.MaternModel([1, 1], [1], 1.5))
kriging_0.setOptimizeParameters(True)
kriging_0.setAnalyticalValidation(True)
kriging_0.setTestSampleValidation(False)
kriging_0.setKFoldValidation(False)
myStudy.add(kriging_0)
kriging_1 = persalys.KrigingAnalysis('kriging_1', design)
kriging_1.setBasis(ot.ConstantBasisFactory(2).build())
kriging_1.setCovarianceModel(ot.SquaredExponential([1, 1], [1]))
kriging_1.setOptimizeParameters(True)
kriging_1.setAnalyticalValidation(True)
kriging_1.setTestSampleValidation(False)
kriging_1.setKFoldValidation(False)
myStudy.add(kriging_1)
kriging_2 = persalys.KrigingAnalysis('kriging_2', design)
interestVariables = ['y0']
kriging_2.setInterestVariables(interestVariables)
kriging_2.setBasis(ot.ConstantBasisFactory(2).build())
kriging_2.setCovarianceModel(ot.SquaredExponential([1, 1], [1]))
kriging_2.setOptimizeParameters(False)
kriging_2.setAnalyticalValidation(True)
kriging_2.setTestSampleValidation(False)
kriging_2.setKFoldValidation(False)
myStudy.add(kriging_2)
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