/dports/math/openturns/openturns-1.18/python/doc/examples/meta_modeling/polynomial_chaos_metamodel/ |
H A D | plot_chaos_beam_sensitivity_degree.py | 46 myDistribution = ot.ComposedDistribution([dist_E, dist_F, dist_L, dist_I]) variable 59 g.setInputDescription(myDistribution.getDescription()) 67 inputTrain, outputTrain, multivariateBasis, totalDegree, myDistribution argument 104 inputTrain, outputTrain, myDistribution, adaptiveStrategy, projectionStrategy 179 inputTrain = myDistribution.getSample(N) 181 inputTest = myDistribution.getSample(n_valid) 186 inputTrain, outputTrain, multivariateBasis, totalDegree, myDistribution 220 inputTrain = myDistribution.getSample(N) 222 inputTest = myDistribution.getSample(n_valid) 225 inputTrain, outputTrain, multivariateBasis, totalDegree, myDistribution
|
H A D | plot_chaos_cantilever_beam_integration.py | 28 myDistribution = cb.independentDistribution variable 54 inputTrain = myDistribution.getSample(N) 100 g, myDistribution, adaptiveStrategy, projectionStrategy) 125 inputTest = myDistribution.getSample(n_valid)
|
/dports/math/openturns/openturns-1.18/python/doc/examples/probabilistic_modeling/distributions/ |
H A D | plot_create_extreme_value_distribution.py | 27 myDistribution = ot.GeneralizedExtremeValue(0.0, 1.0, 0.0) variable 31 print(myDistribution.getActualDistribution()) 39 graphPDF = myDistribution.drawPDF() 44 graphCDF = myDistribution.drawCDF()
|
/dports/math/openturns/openturns-1.18/python/doc/examples/meta_modeling/low_rank_tensors_metamodel/ |
H A D | plot_tensor_cantilever_beam.py | 88 myDistribution = ot.ComposedDistribution([E, F, L, I]) variable 99 X_train = myDistribution.getSample(sampleSize_train) 146 X_train, Y_train, myDistribution, functionFactory, nk, maxRank) 158 for j in range(myDistribution.getDimension()): 173 X_test = myDistribution.getSample(sampleSize_test)
|
/dports/math/openturns/openturns-1.18/python/doc/examples/data_analysis/distribution_fitting/ |
H A D | plot_fit_extreme_value_distribution.py | 53 myDistribution = ot.GeneralizedExtremeValueFactory().buildAsGeneralizedExtremeValue( variable 59 print(myDistribution) 63 print(myDistribution.getActualDistribution()) 70 graph = myDistribution.drawPDF() 90 graph = myDistribution.drawPDF()
|
/dports/math/openturns/openturns-1.18/python/doc/examples/meta_modeling/kriging_metamodel/ |
H A D | plot_kriging_hyperparameters_optimization.py | 73 myDistribution = ot.ComposedDistribution([E, F, L, I], myCopula) variable 84 X_train = myDistribution.getSample(sampleSize_train) 95 dimension = myDistribution.getDimension() 229 dimension = myDistribution.getDimension() 242 X_new = myDistribution.getSample(20) 290 X_train = myDistribution.getSample(sampleSize_train)
|
H A D | plot_kriging_cantilever_beam.py | 31 myDistribution = cb.distribution variable 42 X_train = myDistribution.getSample(sampleSize_train) 126 X_test = myDistribution.getSample(sampleSize_test)
|
H A D | plot_kriging_cantilever_beam_hmat.py | 31 myDistribution = cb.distribution variable 42 X_train = myDistribution.getSample(sampleSize_train) 135 X_test = myDistribution.getSample(sampleSize_test)
|
H A D | plot_kriging_beam_trend.py | 36 myDistribution = cb.distribution variable 47 X_train = myDistribution.getSample(sampleSize_train) 174 X_test = myDistribution.getSample(sampleSize_test)
|
/dports/math/openturns/openturns-1.18/python/test/ |
H A D | t_Waarts_concave.py | 29 myDistribution = Normal(mean, sigma, R) variable 31 start = myDistribution.getMean() 32 Covariance = myDistribution.getCovariance() 38 vect = RandomVector(myDistribution)
|
H A D | t_FORM_draw.py | 52 myDistribution = Normal(mean, sigma, R) variable 58 myDistribution.setDescription(componentDescription) 61 vect = RandomVector(myDistribution)
|
H A D | t_FORM_sensitivity.py | 64 myDistribution = testDistributions[i] variable 69 myDistribution.setDescription(componentDescription) 72 vect = RandomVector(myDistribution)
|
H A D | t_Waarts_convex.py | 45 myDistribution = Normal(mean, sigma, R) variable 47 start = myDistribution.getMean() 48 Covariance = myDistribution.getCovariance() 54 vect = RandomVector(myDistribution)
|
H A D | t_LHS_std.py | 29 myDistribution = Normal(mean, sigma, R) variable 32 vect = RandomVector(myDistribution)
|
H A D | t_ProbabilitySimulationAlgorithm_draw.py | 29 myDistribution = Normal(mean, sigma, R) variable 32 vect = RandomVector(myDistribution)
|
H A D | t_Waarts_noisy_lsf.py | 114 myDistribution = ComposedDistribution(aCollection, aCopula) variable 115 myDistribution.setName("myDist") 117 start = myDistribution.getMean() 118 Covariance = myDistribution.getCovariance() 124 vect = RandomVector(myDistribution)
|
H A D | t_ProbabilitySimulationAlgorithm_sensitivity.py | 29 myDistribution = Normal(mean, sigma, R) variable 32 vect = RandomVector(myDistribution)
|
H A D | t_PostAnalyticalControlledImportanceSampling_std.py | 29 myDistribution = Normal(mean, sigma, R) variable 32 vect = RandomVector(myDistribution)
|
H A D | t_Analytical_std.py | 23 myDistribution = Normal(mean, sigma, R) variable 26 vect = RandomVector(myDistribution)
|
/dports/math/openturns/openturns-1.18/python/doc/examples/reliability_sensitivity/reliability/ |
H A D | plot_axial_stressed_beam.py | 53 myDistribution = sm.distribution variable 60 inputRandomVector = ot.RandomVector(myDistribution) 127 algoFORM = ot.FORM(myCobyla, myEvent, myDistribution.getMean()) 201 dimension = myDistribution.getDimension()
|
/dports/math/openturns/openturns-1.18/lib/test/ |
H A D | t_FORM_draw.cxx | 67 Normal myDistribution(mean, sigma, R); in main() local 73 myDistribution.setDescription(componentDescription); in main() 76 RandomVector vect(myDistribution); in main()
|
H A D | t_DickeyFullerTest_std.cxx | 39 Normal myDistribution; in main() local 40 WhiteNoise whiteNoise (myDistribution, timeGrid); in main()
|
H A D | t_FORM_sensitivity.cxx | 75 Distribution myDistribution(testDistributions[i]); in main() local 80 myDistribution.setDescription(componentDescription); in main() 83 RandomVector vect(myDistribution); in main()
|
H A D | t_DirectionalSampling_std.cxx | 53 Normal myDistribution(mean, sigma, R); in main() local 56 RandomVector vect(myDistribution); in main()
|
H A D | t_LHS_std.cxx | 53 Normal myDistribution(mean, sigma, R); in main() local 56 RandomVector vect(myDistribution); in main()
|