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ChangeLog
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ChangeLog
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= New Features =
== 1.21 release (2023-06-20) == #release-1.21
=== Library ===
==== Major changes ====
* New GEV estimation services: MLE, profiled likelihood, r-maxima, time-varying, return level
==== New classes ====
* SmolyakExperiment (openturns.experimental)
* Physical|StandardSpaceCrossEntropyImportanceSampling, CrossEntropyResult (openturns.experimental)
* LeastSquaresExpansion, IntegrationExpansion (openturns.experimental)
* UniformOverMesh (openturns.experimental)
* GeneralizedExtremeValueValidation (openturns.experimental)
* Coles (openturns.usecases.coles)
* Linthurst (openturns.usescases.linthurst)
==== API changes ====
* Deprecated LinearLeastSquaresCalibration::getCandidate, use getStartingPoint
* Deprecated NonLinearLeastSquaresCalibration::getCandidate, use getStartingPoint
* Deprecated GaussianLinearCalibration::getCandidate, use getParameterMean
* Deprecated NonGaussianLinearCalibration::getCandidate, use getParameterMean
* Removed SequentialStrategy
* Removed TensorApproximationAlgorithm, TensorApproximationResult, CanonicalTensorEvaluation, CanonicalTensorGradient
* Removed FunctionalChaosSobolIndices.getSobolGrouped(Total)Index(int)
* Removed FunctionalChaosSobolIndices::summary
* Removed CorrelationAnalysis::PearsonCorrelation|SpearmanCorrelation|PCC|PRCC
* Removed Distribution.getStandardMoment
* Removed deprecated LinearModelAlgorithm | LinearModelStepwiseAlgorithm ctors
* Removed FunctionalChaosAlgorithm(Function) ctors
* Removed MetaModelResult(Function, Function, ...) ctor
* Removed FunctionalChaosResult.getComposedModel, MetaModelResult.getModel and associated attributes for 1.21
* Removed FunctionalChaosResult Function ctor
* Removed (Process)Sample::computeCenteredMoment
* Removed Distribution::getCenteredMoment
* Removed IterativeMoments::getCenteredMoments
* Removed GeneralLinearModelAlgorithm | KrigingAlgorithm ctors
* Removed Drawable.draw|clean & Graph.draw|clean|getRCommand|makeR*|GetExtensionMap methods
* Removed Sample.storeToTemporaryFile|streamToRFormat methods
* Removed GaussianProcess.GIBBS
* Deprecated DomainIntersection|Union|DisjunctiveUnion(Domain, Domain) ctors
* KrigingResult.getTrendCoefficients now returns a single Point
* GeneralLinearModelResult.getTrendCoefficients now returns a single Point
* KrigingResult.getBasisCollection was removed in favor of KrigingResult.getBasis which returns a single Basis
* GeneralLinearModelResult.getBasisCollection was removed in favor of GeneralLinearModelResult.getBasis which returns a single Basis
* Deprecated EllipticalDistribution::getInverseCorrelation
* HSICStat arguments updated (covariance matrices instead of data + covariance models)
* Deprecated HSICStat relying on weight matrix
* Deprecated Basis::getDimension, use getInputDimension instead
* Removed thinning from Gibbs and all MetropolisHastings classes
* Removed burn-in from Gibbs and all MetropolisHastings classes except RandomWalkMetropolisHastings
* RandomWalkMetropolisHastings::getRealization|Sample no longer remove states reached during burn-in
* RandomWalkMetropolisHastings default adaptation parameters were changed to enable adaptation
* Split BoxCoxFactory::build into buildWithGraph, buildWithLM, buildWithGLM
=== Documentation ===
* Add API documentation to common use cases pages
* Added new use case: Linthurst
=== Python module ===
=== Miscellaneous ===
* Add HypothesisTest::LikelihoodRatioTest for nested model selection
* Add VisualTest::DrawPPplot
* Add VisualTest.Draw(Upper|Lower)(Tail|Extremal)DependenceFunction methods to plot dependence functions
* Add Distribution.compute(Upper|Lower)(Tail|Extremal)DependenceMatrix methods to compute dependence coefficients
* Enable Pagmo.moead_gen with pagmo>=2.19
* Enable Bonmin.Ecp/iFP algorithms with bonmin>=1.8.9
* BoxCoxFactory handles linear model
=== Bug fixes ===
* #2045 ([Debian] NLopt issues during tests on arm64, ppc64el, s390x)
* #2046 ([Debian] DistFunc_binomial issues in tests on arm64 and ppc64el)
* #2047 ([Debian] pythoninstallcheck_DistributionFactory_std issues on arm64, armel, armhf, mips64el)
* #2153 (HSIC computation cost)
* #2185 (Error: no member named '__1' in namespace 'std' ARM64 Android Termux)
* #2193 (Tiny spelling issues)
* #2194 (SubsetSampling: bug in 1.15)
* #2200 (out of bound probas)
* #2204 (Build fails with primesieve-11.0)
* #2205 (Edges of a PolygonArray)
* #2206 (Only Contour legends are shown in a graph mixing Contour and other Drawable (Curve, Cloud,...))
* #2209 (The Felhberg algorithm can fail, sometimes)
* #2210 (Python Domain.getImplementation does not work)
* #2213 (Some script fails)
* #2229 (Unary minus for distribution)
* #2240 (The Viewer sometimes fail)
* #2250 (HSIC Target sensitivity bad filtering)
* #2252 (The examples of calibration are difficult to understand)
* #2255 (The description of a Distribution is wrong)
* #2268 (MeixnerDistribution: slow pdfgradient)
* #2274 (Basis accepts functions with different input (output) dimensions)
* #2281 (The marginal of FireSatelliteModel can fail)
* #2285 (The input and output descriptions does not go down to the metamodel)
* #2287 (DesignProxy.computeDesign() can produce a segmentation fault)
* #2296 (DiracCovarianceModel.discretize() is buggy)
* #2297 (Legend location with grid layout)
* #2299 (Allow openturns as subproject)
* #2306 (Dirichlet::computeConditionalPDF can produce NaNs and Infs)
* #2323 (Minor wording issues in the cross entropy importance sampling example)
* #2327 (A sign mistake in FGM document)
* #2328 (Sample.add weird behaviour)
* #2338 (HSIC with large amount of data makes crash)
== 1.20 release (2022-11-08) == #release-1.20
=== Library ===
==== New classes ====
* IndependentCopulaFactory
* FieldToPointFunctionalChaosAlgorithm (openturns.experimental)
* FieldFunctionalChaosResult (openturns.experimental)
* FieldFunctionalChaosSobolIndices (openturns.experimental)
* CorrelationAnalysis
* UserDefinedMetropolisHastings (openturns.experimental)
* QuantileMatchingFactory
* UniformMuSigma
==== API changes ====
* Removed coupling_tools.execute get_stderr,get_stdout arguments
* Removed deprecated Nlopt|Ceres|Bonmin|CMinpack|Ipopt|TBB|HMatrixFactory::IsAvailable methods
* Deprecated SequentialStrategy
* Deprecated TensorApproximationAlgorithm, TensorApproximationResult, CanonicalTensorEvaluation, CanonicalTensorGradient
* Deprecated FunctionalChaosSobolIndices.getSobolGrouped(Total)Index(int)
* Deprecated static CorrelationAnalysis::PearsonCorrelation|SpearmanCorrelation|PCC|PRCC, use the methods of the new CorrelationAnalysis class instead.
* Removed static CorrelationAnalysis::SRC|SRRC due to a bug: #1753.
* Deprecated Distribution::getStandardMoment
* Inverted ctors arguments order in LinearModelAlgorithm & LinearModelStepwiseAlgorithm : first sample, then basis
* Deprecated oldest LinearModelAlgorithm(X, basis, Y) and LinearModelStepwiseAlgorithm(X, basis, Y,...) ctors
* Deprecated FunctionalChaos(Function, ...) ctors
* Deprecated MetaModelResult(Function, Function, ...) ctor
* Deprecated FunctionalChaosResult.getComposedModel, MetaModelResult.getModel
* Deprecated FunctionalChaosResult(Function, ...) ctor
* Deprecated (Process)Sample::computeCenteredMoment in favor of computeCentralMoment
* Deprecated Distribution::getCenteredMoment in favor of getCentralMoment
* Deprecated IterativeMoments::getCenteredMoments in favor of getCentralMoments
* Deprecated GeneralLinearModelAlgorithm | KrigingAlgorithm ctors using collection of basis
* Deprecated Drawable.draw|clean & Graph.draw|clean|getRCommand methods for legacy R graphs
* Deprecated SampleImplementation.storeToTemporaryFile|streamToRFormat
* Deprecated GaussianProcess.GIBBS in favor of GaussianProcess.GALLIGAOGIBBS
* Deprecated FunctionalChaosSobolIndices::summary in favor of __str__
* Deprecated BoxCoxFactory::build method using collection of basis
=== Documentation ===
* Added example galleries at the end of API doc pages
* Added new use case: WingWeightModel and example of use
* Added new use case: FireSatelliteModel and example of use
=== Python module ===
* New openturns.experimental submodule introducing newest classes until stabilization
=== Miscellaneous ===
* Chaos for mixed variables
=== Bug fixes ===
* #1214 (There is no example with IntegrationStrategy on a database)
* #1333 (Polynomial chaos with mixed variables (improvement))
* #1473 (FunctionalChaosResult should provide the used input/output samples )
* #1568 (There is no example to bootstrap the polynomial chaos)
* #2030 (There is no example which shows how to calibrate a model without observed inputs)
* #2043 (Some attributes of PythonDistribution are changed during the lifecycle of the object)
* #2058 (TruncatedNormal failure)
* #2059 (Pb with computeConditionalPDF in KernelMixture)
* #2064 (drop getGroupedSobolIndex(int) ?)
* #2073 (getCenteredMoment(0))
* #2076 (Problem in TruncatedDistribution of discrete distributions)
* #2083 (Problem in the QQplot of a discrete distribution)
* #2088 (Why is this library overriding the SIGINT handler?)
* #2089 (Cannot load Python objects with large attributes in a Study)
* #2097 (LinearModelStepwiseAlgorithm ctor order)
* #2091 (Compressed H5 files?)
* #2094 (getSampleAtVertex() is not robust)
* #2095 (Triangular::computeCharacteristicfunction() produces NaNs)
* #2098 (LinearModelStepwiseAlgorithm null basis)
* #2101 (drop FunctionalChaosSobolIndices::summary)
* #2103 (FunctionalChaosRandomVector notes)
* #2110 (HSIC draw indices method does not handle input sample description names)
* #2115 (Add mini-galleries of examples on the API pages)
* #2121 (GaussianProcess Gibbs sampling method issues)
* #2123 (MixtureClassifier 'grade' method does not work with a Sample input)
* #2125 (SciPyDistribution __init__ failure with scipy 1.9.0)
* #2129 (get samples from Wishart distribution)
* #2139 (KarhunenLoeveSVDAlgorithm seems to truncate the expansion from v1.19)
* #2140 (GeneralizedParetoFactory.buildMethodOfMoments estimating wrong parameter)
* #2145 (Calibration wo obs input API)
* #2152 (P1LagrangeInterpolation can make Python fail)
* #2154 (SpaceFillingMinDist: LaTeX typo)
* #2157 (Slow creation of mixtures when the atom distributions are costly to copy)
* #2161 (Drop Normal SPD check)
* #2176 (Missing documentation on Kriging Result methods)
== 1.19 release (2022-05-10) == #release-1.19
=== Library ===
==== Major changes ====
* HSIC sensitivity indices
* RandomWalkMetropolisHastings now updates all components at a time, previously updated componentwise
* Iterative statistics
==== New classes ====
* RandomVectorMetropolisHastings
* IndependentMetropolisHastings
* Gibbs
* HSICEstimatorConditionalSensitivity
* HSICEstimatorGlobalSensitivity
* HSICEstimatorTargetSensitivity
* HSICUStat
* HSICVStat
* IterativeExtrema
* IterativeMoments
* IterativeThresholdExceedance
* TensorProductExperiment
* NAIS
* Pagmo
* GalambosCopula
==== API changes ====
* Removed deprecated Hanning alias
* Removed deprecated AdaptiveDirectionalSampling alias
* Removed deprecated VisualTest::DrawCobWeb method
* Removed deprecated shims module
* Removed deprecated TBB.SetNumberOfThreads/GetNumberOfThreads
* Removed deprecated MultiFORM.setMaximumNumberOfDesignPoints/getMaximumNumberOfDesignPoints
* Removed deprecated SubsetSampling.getNumberOfSteps
* coupling_tools.execute: deprecated get_stderr,get_stdout for capture_output, returns CompletedProcess
* Deprecated Nlopt|Ceres|Bonmin|CMinpack|Ipopt|TBB|HMatrixFactory::IsAvailable in favor of PlatformInfo::HasFeature, see also GetFeatures
* RandomWalkMetropolisHastings API breaks to split the likelihood definition
* Deprecated CalibrationStrategy class
=== Documentation ===
=== Python module ===
* Hide C++ getImplementation methods and add Python-specific getImplementation methods with automatic dynamic typecasting
* Add Sample.asDataFrame/BuildFromDataFrame pandas conversion methods
=== Miscellaneous ===
* Add Collection::select(Indices) method
* Parallelized SymbolicFunction evaluation (enabled from a sample size>100 with exprtk)
* Sample csv export: allow one to set precision and format
* Sample csv import: handle nan/inf values
* Add EnumerateFunction::getBasisSizeFromTotalDegree(maximumDegree)
=== Bug fixes ===
* #1260 (RandomWalkMetropolisHastings does not handle non-symmetric proposals properly)
* #1263 (Static functions are implemented in C++ classes instead of namespaces)
* #1334 (Multi-objective optimization)
* #1444 (The calibration examples are unclear)
* #1830 (Incompatible documentation for CauchyModel)
* #1914 (Cobyla & NLopt should accept LeastSquaresProblem)
* #1921 (Adaptive Directional Stratification: the coefficient of variation of the probability is inconsistent with repeated probability results)
* #1922 (Adaptive Directional Stratification: the coefficient of variation cannot be used as a stopping criterion)
* #1926 (Examples have broken graphics)
* #1931 (Interface class getImplementation methods are useless in Python)
* #1939 (Contour curves outside graph window)
* #1940 (getMaximumDegreeStrataIndex has a bug with hyperbolic rule)
* #1943 (TriangularMatrix * Point --> ScalarCollection)
* #1946 (Doc search issues)
* #1947 (The constructor of FunctionalChaosResult is undocumented)
* #1949 (The comparison operator of ComposedDistribution is wrong)
* #1958 (Performance of OrthogonalUniVariatePolynomial (precision, speed))
* #1959 (Cobyla run causes segfault when empty ctor is used)
* #1993 (IsotropicCovarianceModel has no default ctor)
* #1994 (default GaussProductExperiment is invalid)
* #1997 (KLSVD spectrum cutoff error)
* #2012 (Cannot sample a ConditionedGaussianProcess on a mesh containing conditioning points)
* #2014 (Precision issue with the Python KrigingAlgorithm test)
* #2019 (Parametric stationary covariance models doc section needs refresh)
* #2020 (Problem with the UserDefined distribution)
* #2025 (The lack of Bonmin generates an error during example compilation)
* #2031 (Multi-objective optimization example question)
* #2032 (Documentation of NAIS)
== 1.18 release (2021-11-10) == #release-1.18
=== Library ===
==== Major changes ====
==== New classes ====
* DistanceToDomainFunction
==== API changes ====
* Removed deprecated MultiStart::setStartingPoints/getStartingPoints
* Removed deprecated KarhunenLoeveResult::getEigenValues
* Removed deprecated coupling_tools.execute is_shell/workdir/shell_exe/check_exit_code arguments
* RandomVector::get/setParameter and getParameterDescription available to PythonRandomVector
* Implemented CovarianceModel::computeCrossCovariance
* Deprecated Hanning in favor of Hann
* Deprecated AdaptiveDirectionalSampling in favor of AdaptiveDirectionalStratification
* Deprecated VisualTest::DrawCobWeb in favor of DrawParallelCoordinates
* IndicatorFunction constructor takes a Domain as input
* Intervals and DomainUnions get new method computeDistanceToDomain(Point or Sample)
* Renamed some ResourceMap keys: cache-max-size>Cache-MaxSize, parallel-threads>TBB-ThreadsNumber
* Deprecated TBB.SetNumberOfThreads/GetNumberOfThreads
* Deprecated MultiFORM.setMaximumNumberOfDesignPoints/getMaximumNumberOfDesignPoints
* Deprecated SubsetSampling.getNumberOfSteps
* Normal and Student distributions: no need to specify the R parameter if it is the identity matrix
* KrigingResult::getConditionalMean and getConditionalMarginalVariance yield Samples instead of Points when applied to Samples
* Deprecated shims module
=== Documentation ===
=== Python module ===
=== Miscellaneous ===
=== Bug fixes ===
* #1840 (HMatrixFactory leaks)
* #1842 (libOT.so.0.0.0 doesn't have a SONAME)
* #1843 (Ali-Mikhail-Haq copula parameter value)
* #1844 (MaximumDistribution::computePDF is wrong when all the marginals are equal and independent)
* #1845 (MemoizeFunction does not propagate to finite difference gradient&hessian)
* #1847 (ParametricFunction require unnecessary function evaluations)
* #1854 (Sample indexing does not work on np.int64 type)
* #1856 (Speed up Normal computeSurvivalFunction)
* #1857 (ProductCovarianceModel fails when constructed with DiracCovarianceModel)
* #1858 (Normal::computeCDF(sample) crash for large dimensions)
* #1861 (Still some instabilities in Kriging with ot.StationaryFunctionalCovarianceModel)
* #1864 (FORM - IMPORTANCE FACTOR)
* #1868 (Not compatible with hmat-oss-1.7.1: no member named 'compressionMethod' in 'hmat_settings_t')
* #1870 (TruncatedDistribution fails to compute quantiles)
* #1874 (ProcessSample.getSampleAtVertex() may be useful as a public method)
* #1877 (How to model singular multivariate distributions?)
* #1878 (Rename Hanning filtering window)
* #1879 (Adaptive Directional Sampling Algorithm: the drawProbabilityConvergence graph may be wrong)
* #1880 (Adaptive Directional Sampling: some enhancements proposed)
* #1882 (Is Distribution::getLinearCorrelation useful ?)
* #1883 (Strange behavior of FORM ?)
* #1884 (setDesign can lead to wrong Sobol' indices)
* #1891 (Correlation of Halton sequence at high dimensions)
* #1911 (DirectionalSampling freezes python if not correctly initialized)
* #1912 (splitter: missing doc)
* #1915 (computePDFGradient(const Sample &) should rely on computePDFGradient(const Point &) in DistributionImplementation)
* #1918 (PythonDistribution does not allow one to overload the isDiscrete() method)
== 1.17 release (2021-05-12) == #release-1.17
=== Library ===
==== Major changes ====
==== New classes ====
* VertexValuePointToFieldFunction
* KarhunenLoeveReduction
* KarhunenLoeveValidation
* IsotropicCovarianceModel
* KroneckerCovarianceModel
* VonMisesFactory
* KFoldSplitter, LeaveOneOutSplitter
==== API changes ====
* Removed deprecated Pairs alias
* Removed deprecated SORMResult::getEventProbabilityHohenBichler/getGeneralisedReliabilityIndexHohenBichler
* Removed deprecated OptimizationResult::getLagrangeMultipliers, OptimizationAlgorithm::computeLagrangeMultipliers
* Removed deprecated FittingTest::Kolmogorov, FittingTest::BestModelKolmogorov (DistributionFactory argument only)
* Deprecated Sample::computeStandardDeviationPerComponent, use computeStandardDeviation
* Deprecated KarhunenLoeveResult::getEigenValues, use getEigenvalues
* Removed StationaryCovarianceModel
* CovarianceModel.computeAsScalar allows scalars
* Swapped SimulatedAnnealingLHS constructor SpaceFilling/TemperatureProfile arguments
* Added EfficientGlobalOptimization::getKrigingResult, gets the updated version of the KrigingResult passed to the constructor
* Deprecated MultiStart::setStartingPoints/getStartingPoints, use MultiStart::setStartingSample/getStartingSample instead
* MultiStart::setStartingPoint/getStartingPoint throws (previously did nothing)
=== Documentation ===
* Fixed example and plot of Kolmogorov statistics.
* Added a new example showing how to combine RandomWalkMetropolisHastings and PythonDistribution
=== Python module ===
* Serialize Python wrapper objects using dill (PythonDistribution, PythonFunction ...)
=== Miscellaneous ===
=== Bug fixes ===
* #1010 (The doc for ExpectationSimulationAlgorithm is confusing)
* #1052 (The Dirichlet and Normal distributions only have 1D graphics in the doc)
* #1224 (The examples in the doc of the DomainEvent class are unclear)
* #1229 (Better encapsulation of optional 3rd-party headers)
* #1240 (There is no theory documentation for ExpectationSimulationAlgorithm)
* #1257 (Cannot create a SimulatedAnnealingLHS without specifying the temperature profile)
* #1287 (The constructors of KernelSmoothing have no doc)
* #1418 (The Contour example does not present the second constructor)
* #1425 (There is no method to create a train / test pair)
* #1431 (The figure for LHSExperiment is not accurate)
* #1459 (There is no example which shows how to set a column of a Sample)
* #1497 (There is no example to create a multivariate Normal distribution)
* #1506 (The Brent class has no example)
* #1570 (Wrong formula for MauntzKucherenkoSensitivityAlgorithm)
* #1650 (There is no example of a parametric StationaryFunctionalCovarianceModel)
* #1656 (The help page of ExpectationSimulationAlgorithm is unclear)
* #1661 (XMLH5StorageManager does not store IndicesCollection into HDF5 files)
* #1662 (Operator() of a CovarianceModel with multidimensional output should yield object of type SquareMatrix)
* #1680 (QuadraticBasisFactory multiplies cross products by 2)
* #1710 (Misleading y labels in VisualTest.DrawPairsMarginals())
* #1713 (The doc of the ResourceMap does not match the content of the ResourceMap)
* #1714 (The log-PDF of the Pareto is wrong)
* #1721 (The `draw` method of `SobolSimulationAlgorithm` does not reuse the descriptions)
* #1723 (There is no interesting example of the ExprTk feature of SymbolicFunction)
* #1725 (The BetaFactory help page has wrong equations)
* #1729 (LinearModelAnalysis sometimes fail)
* #1731 (The Extreme value example may be improved)
* #1737 (Low rank tensor doc issues)
* #1742 (The example which shows how to set the figure size is wrong.)
* #1751 (DrawCorrelationCoefficients has a wrong Text height)
* #1752 (Error while estimating the reduced log-likelihood when using a StationaryFunctionalCovarianceModel)
* #1758 (The LinearModelStepwiseAlgorithm has no example)
* #1759 (Kriging model with StationaryFunctionalCovarianceModel might provide bad results)
* #1768 (Bug in ExponentiallyDampedCosineModel & SphericalModel)
* #1771 (GridLayout hides the titles in the graph)
* #1772 (MinimumVolumeClassifier cannot draw 1D samples)
* #1774 (ExponentialModel::partialGradient is wrong)
* #1775 (ExponentialModel does not account correlation with Covariance ctor)
* #1776 (Typo in the Branin use case implementation)
* #1781 (The link_to_an_external_code example has small bugs)
* #1784 (The drawPDF method of Histogram sometimes fail)
* #1787 (CovarianceMatrix from SymmetricMatrix raises InvalidArgumentException)
* #1790 (LinearModelResult.getFormula() method is not updated by Stepwise regression)
* #1794 (Some doc examples seem to behave with new infrastructure)
* #1796 (VonMisesFactory is missing)
* #1803 (The API example of Experiment has a format issue)
* #1805 (Brent's implementation has a stability issue)
* #1807 (Beta::computeCharacteristicFunction is wrong if the lower bound is not zero)
* #1815 (1.16 fails with dlib-cpp-19.22)
* #1818 (Problem with wilksNumber)
* #1820 (Incoherent results in LinearModelAnalysis)
* #1835 (RegularizedIncompleteBeta returns nan)
* #1836 (Hypergeometric results differ without boost)
* #1837 (Poor performance when using pickle on OT objects)
== 1.16 release (2020-11-16) == #release-1.16
=== Library ===
==== Major changes ====
* Drop normalization in KrigingAlgorithm
* Drop normalization & transformation handling in GeneralLinearModelAlgorithm
* XML/H5 storage (hdf5 library)
* C++11 requirement
==== New classes ====
* BlockIndependentDistribution
* FejerAlgorithm
* GridLayout
* MinimumVolumeClassifier
* StationaryFunctionalCovarianceModel
* XMLH5StorageManager
==== API changes ====
* Removed deprecated Weibull, WeibullFactory, WeibullMuSigma classes
* Removed deprecated GumbelAB class
* Removed deprecated Event class
* Removed deprecated EnumerateFunction constructors
* Removed various deprecated distribution accessors
* Deprecated Pairs class, see VisualTest.DrawPairs
* Deprecated SORMResult::getEventProbabilityHohenBichler, use SORMResult::getEventProbabilityHohenbichler instead
* Deprecated SORMResult::getGeneralisedReliabilityIndexHohenBichler, use SORMResult::getGeneralisedReliabilityIndexHohenbichler instead
* Renamed SobolSequence::MaximumNumberOfDimension as SobolSequence::MaximumDimension
* Added VisualTest::DrawLinearModel(linearModelResult), useful if the test is performed on the training samples
* Added VisualTest::DrawLinearModelResidual(linearModelResult), useful if the test is performed on the training samples
* Deprecated OptimizationResult::getLagrangeMultipliers
* Moved OptimizationAlgorithm::computeLagrangeMultipliers to OptimizationResult
* Added AIC & BestModelAIC static methods in FittingTest
* Added AICC & BestModelAICC static methods in FittingTest
* Moved BuildDistribution from FunctionalChaosAlgorithm to MetaModelAlgorithm
* Added Drawable::BuildRainbowPalette(size)
* Added Drawable::BuildTableauPalette(size), which is now the default palette.
* Added Drawable::ConvertFromRGBIntoHSV
* Added FittingTest::Lilliefors, BestModelLilliefors
* Deprecated FittingTest::BestModelKolmogorov(Sample, DistributionFactoryCollection, TestResult), use BestModelLilliefors
* Deprecated FittingTest::Kolmogorov(Sample, DistributionFactory, TestResult, level), use Lilliefors
* MetamodelValidation: now computePredictivityFactor returns Point, drawValidation return GridLayout
* Deprecated coupling_tools.execute is_shell/workdir/shell_exe/check_exit_code arguments
=== Documentation ===
* Sphinx-gallery used to render examples
==== API documentation ====
* Clarified SobolIndicesExperiment page, notations now consistent with SobolIndicesAlgorithm page
* Clarified SobolIndicesAlgorithm and (Saltellli|Martinez|MauntzKucherenko|Jansen)SensitivityAlgorithm pages, corrected formulas
* Documented how to turn warnings off or write them on a file
=== Python module ===
* Renamed Viewer *_kwargs arguments to *_kw (matplotlib convention)
* Add ProcessSample Field accessors
=== Miscellaneous ===
* Do not compute Lagrange multipliers by default during an optimization
* Add ResourceMap::FindKeys
* Allow computeLogPDF methods to output values lower than SpecFunc::LogMinScalar
=== Bug fixes ===
* #1001 (Add method SobolSimulationResult::draw)
* #1259 (The diagonal of a scatter plot matrix should have the histograms)
* #1267 (Some CSV files cannot be imported)
* #1377 (The `setKnownParameter` method is not compatible with `buildEstimator`)
* #1407 (GeneralLinearModelAlgorithm mishandles user-specified scale parameter when normalize is True)
* #1415 (The BuildDistribution static method should not use the KS-test)
* #1421 (UserDefinedStationaryCovarianceModel doc suggests input dimension can be >1)
* #1436 (The style of the curves is unpleasing to my eyes)
* #1447 (Highly inaccurate result in reliability model when using subset of RandomVector)
* #1465 (The Sample constructor based on a list and an integer should not exist)
* #1470 (setNbModes is sometimes ignored)
* #1474 (optimization defaults)
* #1507 (Leak in Collection typemaps)
* #1510 (ot.Ceres('LEVENBERG_MARQUARDT') and ot.Ceres('DOGLEG') do not handle bound constraints)
* #1515 (KernelSmoothing build failure)
* #1520 (The NLopt test is dubious)
* #1521 (Basis of MonomialFunction)
* #1529 (The error of the NonLinearLeastSquaresCalibration and GaussianNonLinearCalibration are different)
* #1540 (SubsetSampling: incorrect event sample)
* #1547 (Mesh does not check the simplices indices)
* #1549 (Doc of evaluation operator of KrigingResult)
* #1553 (Optimization algorithms ignore MaxEvaluationNumber parameter in SORM)
* #1556 (WeibullMin::computePDFGradient yields the partial derivatives in the wrong order)
* #1558 (Example estimate_multivariate_normal: FittingTest::BestModelBIC fails to compute the BIC)
* #1564 (Set a Point makes OT crash)
* #1567 (The API doc of SobolIndicesExperiment has a format issue)
* #1573 (LinearModelAnalysis::drawQQPlot line is not the first bisector)
* #1578 (Option to suppressing and/or save warnings?)
* #1581 (LinearModelAlgorithm run() fails to parse Sample description)
* #1586 (Documentation: description error in the API for the FittingTest_BestModelKolmogorov and FittingTest_BestModelChiSquaredclasses)
* #1590 (The equation of the Fejer quadrature rule is triplicated)
* #1592 (SubsetSampling returns an error if Pf=1)
* #1594 (LinearLeastSquaresCalibration and CalibrationResult)
* #1599 (FieldToPointConnection-BlockSize is missing)
* #1603 (FieldToPointConnection generates an invalid exception)
* #1605 (MaximumLikelihoodFactory cannot be used with FittingTest.Kolmogorov)
* #1624 (The graphs_loglikelihood_contour example has a bug)
* #1642 (Big white space at the beginning of examples)
* #1643 (Problem in MaximumDistribution PDF)
* #1647 (MCMC::computeLogLikelihood does not compute the log-likelihood)
* #1651 (Cobyla freezes in 0T1.16rc1)
* #1658 (TimeSeries accessor)
* #1660 (Cannot extract continuous modes from KLResult when dimension>1)
* #1668 (LevelSetMesher does not take into account the comparison operator)
== 1.15 release (2020-05-25) == #release-1.15
=== Library ===
==== Major changes ====
* New EV solver for KarhunenLoeveP1Algorithm (Spectra), with sparse matrix and HMatrix support
* Enable HMat AcaRandom compression method
==== New classes ====
* Ipopt optimization solver
==== Documentation ====
==== API changes ====
* Removed deprecated OptimizationAlgorithm::GetLeastSquaresAlgorithmNames
* Removed deprecated GaussianNonLinearCalibration,NonLinearLeastSquaresCalibration::set,getAlgorithm
* Removed deprecated MethodOfMomentsFactory::set,getOptimizationProblem
* ResourceMap::Set* methods no longer add new keys, the new Add* methods must be used instead
* Removed OPTpp
* Renamed HistogramFactory::computeSilvermanBandwidth into HistogramFactory::computeBandwidth.
=== Python module ===
* ProcessSample __getitem__ returns Sample instead of Field
* Implement list indexing
=== Miscellaneous ===
* Add Sample::getMarginal(Description)
* Fixed TBB performance when used together with OpenBLAS
=== Bug fixes ===
* #1124 (DistributionFactory::buildAsXXX methods not documented)
* #1213 (The legend of the graphics in MetaModelValidation is wrong)
* #1222 (There is no kriging example based on HMAT)
* #1331 (FittingTest_BestModelBIC sometimes fail)
* #1335 (The return of the unsafe ResourceMap)
* #1337 (The rDiscrete function has no help page)
* #1349 (Problem in the graph of Histogram)
* #1351 (Text has a zero size)
* #1354 (The doc of GeneralizedParetoFactory does not reflect the implementation)
* #1371 (Memory leak in ot.TruncatedDistribution)
* #1372 (wrap MultiStart::OptimizationResultCollection)
* #1374 (The setKnownParameter of the factories are not documented enough)
* #1376 (The View class has no example)
* #1378 (Kriging-related covariance model weirdness)
* #1383 (The ExprTk engine for SymbolicFunction does not document the "var" keyword)
* #1384 (The ExprTk engine is not case-sensitive)
* #1388 (Kolmogorov fails on a PythonDistribution)
* #1390 (The doc for the `computeQuantile` method does not describe the optional `tail` argument)
* #1393 (SobolSimulationAlgorithm should be simpler)
* #1395 (Indexing Sample improvement)
* #1403 (Python import otagrum throws an error)
* #1404 (Bug in KrigingAlgorithm+hmat-oss)
* #1405 (Most of the simulation algorithms for rare event fail on a coronavirus example)
* #1416 (MethodOfMomentsFactory has no setOptimizationBounds method)
* #1419 (BoundingVolumeHierarchy segaults/hangs)
* #1423 (The computeSilvermanBandwidth of the HistogramFactory has no help)
* #1432 (Expected improvement-based EfficientGlobalOptimization stopping criterion could be improved)
* #1437 (OrderStatisticsMarginalChecker bound message)
* #1438 (Normal distribution: computeComplementaryCDF)
* #1443 (Not all distributions have a getRoughness() method)
* #1448 (Memory consumption leads to crash)
* #1449 (P1LagrangeInterpolation sometimes fails)
* #1455 (GLM::setCovarianceModel could lead to unexpected behavior of parameter optimization in KrigingAlgorithm)
* #1456 (truncation of distribution)
* #1461 (ComparisonOperator().getImplementation().getClassName() segfault)
* #1471 (The graphics of KarhunenLoeveQuadratureAlgorithm has no axes)
* #1485 (The Normal().getRoughness() method is wrong)
* #1495 (Wrong formula for Expected Improvement evaluation)
== 1.14 release (2019-11-13) == #release-1.14
=== Library ===
==== IMPORTANT: Distributions parametrization changes ====
* New argument ordering in Frechet ctor: scale(beta), shape(alpha), location(gamma) (swapped alpha and beta)
* New parametrization in Gumbel: scale(beta), position(gamma) (beta=1/alpha for first argument)
* New parametrization in Beta: shape(alpha), shape(beta), location(a), location(b) (beta=t-r for second argument)
* New parametrization in InverseGamma: rate(lambda), shape(k) (swapped arguments)
* New parametrization in InverseNormal: location(mu), rate(lambda) (swapped arguments)
* New parametrization in Laplace: mean(mu), rate(lambda) (swapped arguments)
=> One can use "import openturns.shims as ot" to maintain compatibility with older scripts
==== Major changes ====
* New optimization solvers (Dlib, Bonmin for mixed integer optimization problems)
* New distributions (SquaredNormal, WeibullMax, Pareto, DiscreteCompoundDistribution, MixedHistogramUserDefined)
* New estimators (ParetoFactory, GeneralizedExtremeValueFactory, LeastSquaresDistributionFactory, PlackettCopulaFactory)
* New copulas (JoeCopula, MarshallOlkinCopula, PlackettCopula)
* Linear model learner (LinearModelStepwiseAlgorithm)
* System events (IntersectionEvent, UnionEvent, SystemFORM, MultiFORM)
==== New classes ====
* Dlib
* SquaredNormal
* NullHessian
* GumbelLambdaGamma
* LogNormalMuErrorFactor
* WeibullMax
* WeibullMaxFactory
* WeibullMaxMuSigma
* GeneralizedExtremeValueFactory
* Pareto
* LeastSquaresDistributionFactory
* ParetoFactory
* DiscreteCompoundDistribution
* Bonmin
* IntersectionEvent
* UnionEvent
* SystemFORM
* MultiFORM
* JoeCopula
* MarginalEvaluation/Gradient/Hessian
* MarshallOlkinCopula
* LinearModelStepwiseAlgorithm
* MixedHistogramUserDefined
* PlackettCopula
* PlackettCopulaFactory
==== API changes ====
* FittingTest methods to return fitted distributions with factory as argument
* Removed deprecated specific RandomVector constructors
* Removed deprecated HypothesisTest::Smirnov
* Removed deprecated FittingTest::TwoSamplesKolmogorov
* Removed deprecated LinearModel, LinearModelFactory
* Removed deprecated HypothesisTest::(Partial|Full)Regression
* Removed deprecated OptimizationProblem(levelFunction, levelValue) ctor
* Removed deprecated (Linear|Quadratic)(LeastSquares|Taylor)::getResponseSurface
* Removed deprecated VisualTest::DrawEmpiricalCDF,DrawHistogram,DrawClouds
* Moved dot to Point::dot
* Deprecated Weibull in favor of WeibullMin
* Deprecated WeibullMuSigma in favor of WeibullMinMuSigma
* Deprecated WeibullFactory in favor of WeibullMinFactory, buildAsWeibull
* Deprecated GumbelAB
* Deprecated GaussianNonLinearCalibration,NonLinearLeastSquaresCalibration::set,getAlgorithm
* Added getConditionalMarginalCovariance method to KrigingResult
* Added getConditionalMarginalVariance method to KrigingResult
* Deprecated OptimizationAlgorithm::GetLeastSquaresAlgorithmNames
* Added linearity features to Function
* Added 'removeKey' method to ResourceMap
* Removed Copula class
* Deprecated Event class, use ThresholdEvent/ProcessEvent/DomainEvent classes
* Deprecated EnumerateFunction constructors
* Added a minimum probability accessor to SubsetSampling
* Added a UniVariateFunction interface to solvers and integration algorithms
=== Python module ===
* Add Domain.__contains__ operator
=== Miscellaneous ===
* Add GeneralizedPareto location parameter
* Add getSobolGroupedTotalIndex method for FunctionalChaosSobolIndices for the indice of a group of variables
=== Bug fixes ===
* #997 (Adding minimum volume set examples)
* #1004 (The doc for SobolSimulationAlgorithm has issues)
* #1006 (Text drawable does not handle size)
* #1130 (Inconsistency in FittingTest)
* #1160 (2-d GaussianProcess realization graph regression)
* #1169 (Missing key in ResourceMap)
* #1173 (There is no dot product example)
* #1185 (Bug with Normal.computeMinimumLevelSet method)
* #1190 (computeProbability clamped by Domain-SmallVolume)
* #1197 (Doc error: TrendTransform)
* #1198 (Doc error: ValueFunction)
* #1202 (Sample::sort & Sample::sortAccordingToAComponent only return new Samples)
* #1204 (sortAccordingToAComponent does not check its inputs arguments)
* #1209 (LinearModelStepwiseAlgorithm from otlm does not exist in OT)
* #1216 (The CalibrationResult doc does not match the code)
* #1247 (KrigingAlgorithm could not compute amplitude analytically with ProductCovarianceModel )
* #1264 (ProductCovarianceModel ignore active parameters of its 1d marginals)
* #1282 (The dlib example fails)
* #1283 (LogNormalFactory::buildMethodOfLeastSquares has no doc)
* #1289 (The help page of PythonFunction has formatting issues)
* #1303 (Rosenblatt transformation segfault)
== 1.13 release (2019-06-06) == #release-1.13
=== Library ===
==== Major changes ====
* Added OPT++ solvers
* Improved a lot the performance of all the Rosenblatt related computations
* Added elementary calibration capabilities
* Added CMinpack, Ceres Solver least-squares solvers
==== New classes ====
* ParametricPointToFieldFunction
* LinearModelResult, LinearModelAlgorithm, LinearModelAnalysis
* OPTpp
* NearestPointProblem, LeastSquaresProblem
* CMinpack
* Ceres
* DiscreteMarkovChain
* CalibrationAlgorithm, CalibrationResult, GaussianLinearCalibration, LinearLeastSquaresCalibration
* NonLinearLeastSquaresCalibration, GaussianNonLinearCalibration
* Hypergeometric
==== API changes ====
* Removed deprecated FunctionalChaosRandomVector::getSobol* methods
* Removed deprecated UserDefinedCovarianceModel constructor based on a Collection<CovarianceMatrix>
* Removed deprecated FieldFunction,FieldToPointFunction::getSpatialDimension
* Removed deprecated LinearModelRSquared, LinearModelAdjustedRSquared
* Deprecated LinearModel, LinearModelFactory
* Moved HypothesisTest::(Partial|Full)Regression to LinearModelTest
* Deprecated OptimizationProblem(levelFunction, levelValue)
* Deprecated (Linear|Quadratic)(LeastSquares|Taylor)::getResponseSurface
* FittingTest::BestModelBIC returns the Distribution and the BIC value
* Deprecated VisualTest::DrawEmpiricalCDF,DrawHistogram,DrawClouds
* Add statistic attribute and accessor to the TestResult class
* Deprecated Point::getDescription,setDescription
=== Python module ===
=== Miscellaneous ===
* Changed bugtracker to GitHub issues (https://github.com/openturns/openturns/issues)
* Dropped rot dependency
=== Bug fixes ===
* #289 (Move the LinearModelFactory class from the Base namespace to the Uncertainty namespace)
* #579 (There is no example of a typical "Central Tendency" study)
* #839 (more optim solvers details)
* #931 (The PostAnalyticalImportanceSampling and PostAnalyticalControlledImportanceSampling are too briefly documented)
* #979 (Viewer does not handle BarPlot's fillStyle)
* #977 (HypothesisTest::ChiSquared is bogus)
* #980 (CorrelationAnalysis_SRC scales the coefficients so that they sum to 1)
* #981 (HypothesisTest_{Full, Partial} regression should be moved to LinearModelTest)
* #982 (LinearModelTest::LinearModelDurbinWatson with several factors)
* #983 (Bogus Normal parameter distribution)
* #989 (Fixed the documentation of BIC according to the code)
* #995 (Pip does not recognize conda install of openturns)
* #1000 (SaltelliSensitivityAlgorithm with LowDiscrepancyExperiment produces wrong results)
* #1005 (The stopping criteria of SobolSimulationAlgorithm is weird)
* #1024 (The unary operator is undefined for Normal distribution)
* #1025 (Empty throw in PythonWrappingFunctions)
* #1028 (Build fails with clang-60: token is not a valid binary operator in a preprocessor subexpression)
* #1031 (The doc for LogNormal and LogNormalMuSigma is confusing )
* #1035 (ProbabilitySimulationResult does not provide the distribution of the probability)
* #1036 (Doc error for KrigingAlgorithm method getReducedLogLikelihoodFunction())
* #1043 (The DrawSobolIndices doc is wrong)
* #1045 (LowDiscrepancyExperiment/ComposedCopula correlation across blocks ?)
* #1051 (The default value of computeSecondOrder in SobolIndicesExperiment should be False)
* #1054 (Optimization algorithms ignore MaxEvaluationNumber parameter)
* #1057 (FittingTest.BestModelBIC to return bic value)
* #1058 (GEV problem)
* #1064 (The summary of a FunctionalChaosSobolIndices fails with more than 14 dimensions)
* #1071 (Event cannot be created from a RandomVector)
* #1078 (KrigingAlgorithm documentation still references "inputTransformation")
* #1080 (Brent, Secant, Bissection documentation)
* #1085 (GPD documentation)
* #1090 (PythonFunction can make OT crash)
* #1092 (The parameterGradient of a ParametricFunction can loss accuracy)
* #1099 (PythonDistribution does not work with ConditionalDistribution)
* #1111 (Function::draw() does not take the scale parameter properly into account)
* #1112 (Several bugs in Multinomial)
* #1119 (The parameter description is not taken into account in CalibrationResult)
* #1129 (Segmentation fault with RandomMixture)
* #1139 (CopulaImplementation should derive from DistributionImplementation)
* #1143 (The ResourceMap is not correctly formatted in help pages)
* #1148 (Fails to find cminpack)
* #1155 (The description of Points can be set, but get is empty)
== 1.12 release (2018-11-08) == #release-1.12
=== Library ===
==== Major changes ====
* FieldFunction and co knows its input/output meshes before evaluation
* SobolSequence has been extended from maximum dimension 40 to 1111
* Parametrized statistical tests by first kind risk instead of 1-risk
* FittingTest now compute a correct p-value in Kolmogorov tests even if the parameters are estimated from the tested sample
* Completed documentation migration with process content
==== New classes ====
* ProbabilitySimulationResult
* ExpectationSimulationAlgorithm, ExpectationSimulationResult
* ExtremeValueCopula
* ChaospyDistribution
* SobolSimulationAlgorithm, SobolSimulationResult
* FractionalBrownianMotionModel
==== API changes ====
* Removed deprecated MonteCarlo, ImportanceSampling, QuasiMonteCarlo, RandomizedQuasiMonteCarlo, RandomizedLHS classes
* Removed deprecated Field::getDimension, getSpatialDimension, getSpatialMean, getTemporalMean methods
* Remove deprecated Process::getDimension, getSpatialDimension methods
* Removed deprecated CovarianceModel::getDimension, getSpatialDimension, getSpatialCorrelation, setSpatialCorrelation methods
* Removed deprecated SpectralModel::getDimension, getSpatialDimension, getSpatialCorrelation methods
* Removed deprecated TruncatedDistribution single bound accessors
* Removed deprecated Function constructors
* Removed deprecated Sample,SampleImplementation::operator*(SquareMatrix) and operator/(SquareMatrix) (and in-place operators)
* Removed deprecated SampleImplementation::scale(SquareMatrix)
* Removed deprecated Domain(a, b) constructor
* Removed deprecated Domain,DomainImplementation::numericallyContains, isEmpty, isNumericallyEmpty, getVolume, getNumericalVolume, computeVolume
* Removed deprecated Domain,DomainImplementation::getLowerBound, getUpperBound methods
* Removed deprecated Interval,Mesh::computeVolume
* Removed deprecated SobolIndicesAlgorithm::[sg]etBootstrapConfidenceLevel
* Removed deprecated Mesh::getVerticesToSimplicesMap,computeSimplexVolume
* Removed deprecated Evaluation,EvaluationImplementation,EvaluationProxy,Function,FunctionImplementation,ParametricEvaluation::operator(inP,parameter)
* Removed deprecated Gradient,GradientImplementation,ParametricGradient::gradient(inP,parameter)
* Removed deprecated Hessian,HessianImplementation,ParametricHessian::operator(inP,parameter)
* Removed ExponentialCauchy, SecondOrderModel, SecondOrderImplementation
* LowDiscrepancyExperiment to work with dependent distributions
* Deprecated UserDefinedCovarianceModel constructor based on a Collection<CovarianceMatrix>
* Deprecated FieldFunction,FieldToPointFunction::getSpatialDimension
* Removed VertexFunction class
* Deprecated LinearModelRSquared, LinearModelAdjustedRSquared
* Added ResourceMap::GetType to access the type of a given key.
* Extended OrthogonalBasis::build() to multi-indices (see ticket #967)
* Deprecated specific RandomVector constructors
=== Python module ===
=== Miscellaneous ===
* CMake >=2.8.8 is required to build OpenTURNS
* The format of openturns.conf has changed to make a distinction between types of keys
=== Bug fixes ===
* #660 (Strange behavior of KernelSmoothing)
* #684 (Strange behavior of Student distribution in multidimensional case)
* #778 (DirectionalSampling is unstable)
* #915 (Distribution.computeQuantile properties)
* #949 (LowDiscrepancyExperiment for distributions having dependent copula)
* #952 (Limitation on distribution type for polynomial chaos?)
* #953 (RandomMixture can fail with truncated distribution)
* #954 (CompositeProcess::getFuture() broken)
* #955 (StudentFactory does not estimate the standard deviation)
* #957 (RandomMixture::getDispersionIndicator() takes a long time)
* #958 (The Sobol' indices plot is wrong for chaos)
* #959 (The PolygonArray and Polygon classes poorly manage the colors)
* #960 (Polygon sometimes make OT crash)
* #961 (The PolygonArray class seem to ignore the legends)
* #962 (The doc of MetaModelValidation.computePredictivityFactor is wrong)
* #963 (VisualTest_DrawHistogram sometimes has overlapping X labels)
* #964 (Study does not load LogNormalMuSigma variables from XML)
* #965 (A RandomVector from a RandomVector can make OT crash)
* #968 (Empty legend make OT crash)
* #970 (Composing gaussian copulas can crash the chaos)
* #972 (FittingTest::ChiSquared slow and buggy)
* #974 (Default constructor of the TruncatedDistribution)
* #975 (EmpiricalBernsteinCopula is a copula as sample is truncated)
== 1.11 release (2018-05-11) == #release-1.11
=== Library ===
==== Major changes ====
==== New classes ====
* FrechetFactory
* Fehlberg
* TranslationFunction
* DomainComplement, DomainIntersection, DomainUnion, DomainDisjunctiveUnion, DomainDifference
* SmoothedUniform
* NearestNeighbourAlgorithm, RegularGridNearestNeighbour, NaiveNearestNeighbour, NearestNeighbour1D
* EnclosingSimplex, EnclosingSimplexImplementation, NaiveEnclosingSimplex, RegularGridEnclosingSimplex, EnclosingSimplexMonotonic1D, BoundingVolumeHierarchy
* IndicesCollection
* SymbolicParserExprTk
* EvaluationProxy
* MemoizeFunction, MemoizeEvaluation
* Evaluation, Gradient, Hessian
* MeshDomain
* NormInfEnumerateFunction
* FunctionalChaosSobolIndices
* P1LagrangeInterpolation
* FilonQuadrature
==== API changes ====
* Removed deprecated NumericalMathFunction class
* Removed deprecated QuadraticNumericalMathFunction class
* Removed deprecated LinearNumericalMathFunction class
* Removed deprecated NumericalSample class
* Removed deprecated NumericalPoint[WithDescription] class
* Removed deprecated NumericalScalarCollection class
* Removed deprecated NumericalComplexCollection class
* Removed deprecated PosteriorRandomVector class
* Removed deprecated ConditionedNormalProcess class
* Removed deprecated ResourceMap::[SG]AsNumericalScalar methods
* Removed deprecated SpecFunc::*NumericalScalar* constants
* Removed deprecated PlatformInfo::GetConfigureCommandLine method
* Removed deprecated Field::getSample method
* Removed deprecated SobolIndicesAlgorithm::Generate method
* Removed deprecated NumericalScalar, NumericalComplex types
* Removed deprecated Function constructors
* CorrelationAnalysis::(Pearson|Spearman)Correlation accepts a multivariate sample and returns a Point
* Deprecated Field::getDimension, getSpatialDimension, getSpatialMean, getTemporalMean
* Deprecated Process::getDimension, getSpatialDimension
* Deprecated CovarianceModel::getDimension, getSpatialDimension, getSpatialCorrelation, setSpatialCorrelation
* Deprecated SecondOrderModel::getDimension, getSpatialDimension
* Deprecated SpectralModel::getDimension, getSpatialDimension, getSpatialCorrelation
* Deprecated TruncatedDistribution single bound accessors in favor of setBounds/getBounds
* Deprecated remaining analytical & database Function ctors
* Mesh constructor no longer builds a KDTree, new method Mesh::setNearestNeighbourAlgorithm must be called explicitly
* Deprecated Domain::numericallyContains, isEmpty, isNumericallyEmpty, getVolume, getNumericalVolume, computeVolume, getLowerBound, getUpperBound
* Add an argument to KarhunenLoeveQuadratureAlgorithm to pass domain bounds
* Add an argument to Mesh::streamToVTKFile() and Mesh::exportToVTKFile() to pass custom simplices
* All KDTree methods are modified
* IndicesCollection is no more an alias to Collection<Indices>, it has its own class and has a fixed size
* Removed BipartiteGraph::add method
* Deprecated usage of _e and _pi constants when defining analytical functions, e_ and pi_ must be used instead.
* Removed Function::enableHistory,disableHistory,isHistoryEnabled,clearHistory,getHistoryInput,getHistoryOutput,getInputPointHistory,getInputParameterHistory
* Removed Function::enableCache,disableCache,isCacheEnabled,getCacheHits,addCacheContent,getCacheInput,getCacheOutput,clearCache
* Added Drawable::getPaletteAsNormalizedRGBA() to get the palette into a native matplotlib format.
* Changed DistributionImplementation::getCopula,getMarginal,getStandardRepresentative,getStandardDistribution to return a Distribution instead of Pointer<DistributionImplementation>
* Changed DistributionFactoryImplementation::build to return a Distribution instead of Pointer<DistributionImplementation>
* Changed ProcessImplementation::getMarginal to return a Process instead of Pointer<ProcessImplementation>
* Changed RandomVector::getAntecedent,getMarginal to return a RandomVector instead of Pointer<RandomVectorImplementation>
* Changed all {get,set}{Evaluation,Gradient,Hessian} methods to work on Evaluation/Gradient/Hessian instead of Pointer
* Deprecated SobolIndicesAlgorithm::setBootstrapConfidenceLevel, getBootstrapConfidenceLevel
* TNC, Cobyla, EGO are parametrized by setMaximumEvaluationNumber instead of setMaximumIterationNumber
* Removed all KDTree services from Mesh,RegularGrid,Field::getNearestVertex, getNearestVertexIndex, etc, client code must use NearestNeighbourAlgorithm if needed
* Changed Mesh to not derive from DomainImplementation
* Deprecated Mesh::computeSimplexVolume, use Mesh::computeSimplicesVolume instead
* Deprecated Mesh,Interval::computeVolume
* Deprecated FunctionalChaosRandomVector::getSobol* methods in favor of FunctionalChaosSensitivity ones
* DeprecatedEvaluation,EvaluationImplementation,EvaluationProxy,Function,FunctionImplementation,ParametricEvaluation::operator()(inP,parameter)
* Deprecated Gradient,GradientImplementation,ParametricGradient::gradient(inP,parameter)
* Deprecated Hessian,HessianImplementation,ParametricHessian::hessian(inP,parameter)
=== Python module ===
* Depend on swig>=2.0.9
=== Miscellaneous ===
* Multivariate TruncatedDistribution
* Asymptotic Sobol' variance estimators
=== Bug fixes ===
* #870 (Problem with TensorizedCovarianceModel with spatial dim > 1)
* #926 (Covariance model active parameter set behavior)
* #928 (Covariance model/ Field/Process properties naming)
* #932 (Optim algo iteration/evaluation number)
* #937 (Small bugs in FunctionalChaosResult::get{Residuals, RelativeErrors})
* #938 (DistributionFactory::buildEstimator to handle Exception)
* #939 (The help of the getMaximumDegreeStrataIndex method is wrong.)
* #941 (Duplicate with SobolIndicesExperiment)
* #944 (Inline plots crash in notebooks if too many points)
* #945 (build fails with cmake 3.11)
* #946 (OT via anaconda, usage of ot.HypothesisTest error: R_EXECUTABLE-NOTFOUND)
* #947 (EmpiricalBernsteinCopula::setCopulaSample() too restrictive)
* #948 (Bug with BayesDistribution)
* #950 (Circular call to getShape() in Copula)
== 1.10 release (2017-11-13) == #release-1.10
=== Library ===
==== Major changes ====
* It is now possible to define numerical model acting on either Point or Field
to produce either Point or Field.
The Python binding has been extended to allow the user to define such
functions based on either a Python function or a Python class.
All the possible compositions have been implemented.
==== New classes ====
* ProbabilitySimulation
* SobolIndicesExperiment
* VertexFunction
* FieldToPointFunction
* FieldToPointFunctionImplementation