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ChangeLog
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= New Features =
== 1.11 release (in progress) == #release-1.11
=== Library ===
==== Major changes ====
==== New classes ====
* FrechetFactory
* Fehlberg
==== 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
=== Python module ===
=== Miscellaneous ===
* Multivariate TruncatedDistribution
=== Bug fixes ===
* #870 (Problem with TensorizedCovarianceModel with spatial dim > 1)
* #926 (Covariance model active parameter set behavior)
* #928 (Covariance model/ Field/Process properties naming)
* #933 (Compilation failed when Muparser is missing)
== 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
* PythonFieldToPointFunction
* OpenTURNSPythonFieldToPointFunction
* PointToFieldFunction
* PointToFieldFunctionImplementation
* PythonPointToFieldFunction
* OpenTURNSPythonPointToFieldFunction
* KarhunenLoeveLifting
* KarhunenLoeveProjection
* PointToPointEvaluation
* PointToPointConnection
* PointToFieldConnection
* FieldToFieldConnection
* FieldToPointConnection
==== API changes ====
* Removed deprecated LAR class
* Remove deprecated Function::GetValidConstants|GetValidFunctions|GetValidOperators
* Removed deprecated TemporalNormalProcess, SpectralNormalProcess classes
* Removed deprecated GeneralizedLinearModelAlgorithm, GeneralizedLinearModelResult classes
* Removed deprecated DynamicalFunction, SpatialFunction, TemporalFunction classes
* Removed deprecated KarhunenLoeveP1Factory, KarhunenLoeveQuadratureFactory classes
* Removed deprecated GramSchmidtAlgorithm, ChebychevAlgorithm classes
* Removed [gs]etOptimizationSolver methods
* Removed CovarianceModel::compute{AsScalar,StandardRepresentative} overloads
* Deprecated PosteriorRandomVector
* Deprecated MonteCarlo, ImportanceSampling, QuasiMonteCarlo, RandomizedQuasiMonteCarlo, RandomizedLHS classes
* Made MatrixImplementation::isPositiveDefinite const and removed its argument
* Renamed EfficientGlobalOptimization::setAIETradeoff to setAEITradeoff
* Deprecated PlatformInfo::GetConfigureCommandLine.
* Renamed ConditionedNormalProcess to ConditionedGaussianProcess
* Deprecated Field::getSample in favor of getValues
* Deprecated SobolIndicesAlgorithm::Generate in favor of SobolIndicesExperiment.
=== Python module ===
=== Miscellaneous ===
* Changed bounds evaluation in UniformFactory, BetaFactory
* Worked around bug #864 (parallel segfault in BernsteinCopulaFactory)
=== Bug fixes ===
* #890 (Cannot build triangular distribution)
* #891 (Viewer issue with Pairs drawables)
* #895 (Trouble reading CSV files with separators in description)
* #896 (Python iteration in ProcessSample leads to capacity overflow)
* #897 (Bug in Graph::draw with small data)
* #898 (Could not save/load some persistent classes)
* #899 (PythonDistribution copula crash when parallelism is active)
* #902 (NormalGamma constructor builds wrong link function)
* #905 (Bogus MaternModel::setParameter)
* #906 (t_LevelSetMesher_std fails on most non-Intel based chips)
* #907 (Notation)
* #908 (Documentation: change titles)
* #909 (Wrong argument type in the API doc)
* #910 (Graph of a d-dimensionnal distribution)
* #911 (In the Field class, the getSample and getValues methods are duplicate)
* #912 (Wrong description of Histogram constructor parameters)
* #914 (KarhunenLoeveQuadratureAlgorithm crashes for covariance models of dimension>1)
* #917 (Bug in RandomMixture::computeCDF())
* #918 (The class SobolIndicesAlgorithm has a draw method which has no example)
* #919 (Wrong simplification mechanism in MarginalTransformationEvaluation for Exponential distribution)
* #921 (Cannot print a FixedExperiment when built from sample and weight)
* #923 (Fix ExponentialModel::getParameter for diagonal correlation)
* #924 (Probleme with the factory of a Generalized Pareto distribution)
* #927 (Functional chaos is memory hungry)
* #929 (The labels of the sensitivity analysis graphics are poor)
* #930 (The getMean method has a weird behavior on parametrized distribution)
== 1.9 release (2017-04-18) == #release-1.9
=== Library ===
==== Major changes ====
* Integrate otlhs module
* New function API
* Canonical format low-rank tensor approximation
* EGO global optimization algorithm
==== New classes ====
* SpaceFillingPhiP, SpaceFillingMinDist, SpaceFillingC2
* LinearProfile, GeometricProfile
* MonteCarloLHS, SimulatedAnnealingLHS
* LHSResult
* MultiStart
* MethodOfMomentsFactory
* SymbolicFunction, AggregatedFunction, ComposedFunction, DatabaseFunction, DualLinearCombinationFunction
* LinearCombinationFunction, LinearFunction, QuadraticFunction, ParametricFunction, IndicatorFunction
* DistributionTransformation
* GeneralizedExtremeValue
* UniVariateFunctionFamily, UniVariateFunctionFactory, TensorizedUniVariateFunctionFactory
* MonomialFunction, MonomialFunctionFactory
* KarhunenLoeveSVDAlgorithm
* RankMCovarianceModel
* SparseMethod
* CanonicalTensorEvaluation|Gradient, TensorApproximationAlgorithm|Result
* GaussLegendre
* EfficientGlobalOptimization
==== API changes ====
* Removed deprecated SLSQP, LBFGS and NelderMead classes
* Removed deprecated QuadraticCumul class
* Removed classes UserDefinedPair, HistogramPair
* Removed deprecated method WeightedExperiment::getWeight
* Removed deprecated method DistributionFactory::build(NumericalSample, CovarianceMatrix&)
* Removed deprecated distributions alternative parameters constructors, accessors
* Added a generic implementation of the computeLogPDFGradient() method in the DistributionImplementation class.
* Allow Box to support bounds
* Deprecated LinearNumericalMathFunction in favor of LinearFunction
* Deprecated QuadraticNumericalMathFunction in favor of QuadraticFunction
* Deprecated NumericalMathFunction::GetValidConstants|GetValidFunctions|GetValidOperators
* Renamed ComposedNumericalMathFunction to ComposedFunction
* Renamed LinearNumericalMathFunction to LinearFunction
* Swap covModel and basis arguments in KrigingAlgorithm constructors
* Removed useless keepCholesky argument in KrigingAlgorithm constructors
* Renamed OptimizationSolver to OptimizationAlgorithm
* Renamed TemporalNormalProcess to GaussianProcess
* Renamed SpectralNormalProcess to SpectralGaussianProcess
* Renamed GeneralizedLinearModelAlgorithm to GeneralLinearModelAlgorithm
* Renamed GeneralizedLinearModelResult to GeneralLinearModelResult
* Renamed DynamicalFunction to FieldFunction
* Renamed SpatialFunction to ValueFunction
* Renamed TemporalFunction to VertexValueFunction
* Deprecated [gs]etOptimizationSolver methods
* Renamed ProductNumericalMathFunction to ProductFunction
* Deprecated KarhunenLoeveP1Factory, KarhunenLoeveQuadratureFactory
* Deprecated GramSchmidtAlgorithm, ChebychevAlgorithm
* Added getSobolAggregatedIndices() to FunctionalChaosRandomVector
* Added computeWeight() to Mesh
* Deprecated NumericalMathFunction ctors
* Deprecated NumericalMathFunction for Function
* Deprecated NumericalSample for Sample
* Deprecated NumericalPoint[WithDescription] for Point[WithDescription]
* Deprecated ResourceMap::[SG]AsNumericalScalar for [SG]AsScalar
* Deprecated SpecFunc::*NumericalScalar*
* Deprecated NumericalScalar for Scalar
* Deprecated NumericalComplex for Complex
* Deprecated DistributionImplementation::getGaussNodesAndWeights
=== Python module ===
=== Miscellaneous ===
=== Bug fixes ===
* #351 (FORM is it possible to hav a ".setMaximumNumberOfEvaluations")
* #729 (KDTree & save)
* #774 (Exact limits of a normal distribution with unknown mean and variance)
* #866 (Check the parameter estimate for the kriging model)
* #869 (The ProductNumericalMathFunction class has no example)
* #871 (GeneralizedExponential P parameter : int or float ?)
* #872 (Cannot draw a Text drawable using R)
* #874 (Compatibility between a distribution factory and an alternate parametrization not checked)
* #875 (TruncatedNormalFactory randomly crashes)
* #876 (Bad time grid in StationaryCovarianceModelFactory::build)
* #877 (centered whitenoise limitation)
* #878 (Viewer does not take into account labels in Contour)
* #879 (Incomplete arguments in FunctionalChaosRandomVector docstrings)
* #882 (RandomMixture segfaults with Dirac)
* #883 (VisualTest.DrawHistogram should rely on Histogram.drawPDF)
* #886 (Bogus RandomMixture::getSupport)
* #887 (Bogus PDF evaluation in RandomMixture with mix of continuous/discrete variables)
* #888 (Bogus RandomMixture::getSample)
== 1.8 release (2016-11-18) == #release-1.8
=== Library ===
==== Major changes ====
* Changed the default orthonormalization algorithm of StandardDistributionPolynomialFactory from GramSchmidtAlgorithm to AdaptiveStieltjesAlgorithm
* New api for sensitivity analysis
* New methods to compute confidence regions in Distribution
==== New classes ====
* SubsetSampling
* AdaptiveDirectionalSampling
* KarhunenLoeveQuadratureFactory
* SobolIndicesAlgorithm
* SaltelliSensitivityAlgorithm
* MartinezSensitivityAlgorithm
* JansenSensitivityAlgorithm
* MauntzKucherenkoSensitivityAlgorithm
* SoizeGhanemFactory
* LevelSetMesher
* HistogramPolynomialFactory
* ChebychevFactory
* FourierSeriesFactory, HaarWaveletFactory
* OrthogonalProductFunctionFactory
==== API changes ====
* Removed deprecated (AbdoRackwitz|Cobyla|SQP|TNC)SpecificParameters classes
* Removed AbdoRackwitz|Cobyla|SQP::[gs]etLevelFunction|[gs]etLevelValue
* Removed deprecated OptimizationSolver::setMaximumIterationsNumber
* Removed deprecated method Distribution::setParametersCollection(NP)
* Removed deprecated PersistentFactory string constructor
* Deprecated QuadraticCumul class in favor of TaylorExpansionMoments
* Renamed __contains__ to contains
* Modified NumericalMathFunction::[sg]etParameter to operate on NumericalPoint instead NumericalPointWithDescription
* Add NumericalMathFunction::[sg]etParameterDescription to access the parameter description
* Deprecated classes UserDefinedPair, HistogramPair
* Removed SensitivityAnalysis class
* Deprecated SLSQP, LBFGS and NelderMead classes in favor of NLopt class
* Deprecated LAR in favor of LARS
* Deprecated DistributionFactory::build(NumericalSample, CovarianceMatrix&)
* Deprecated distributions alternative parameters constructors, accessors
* Swap SpectralModel scale & amplitude parameters: CauchyModel, ExponentialCauchy
=== Python module ===
* Added the possibility to distribute PythonFunction calls with multiprocessing
=== Miscellaneous ===
* Improved the computeCDF() method of Normal
* Added the computeMinimumVolumeInterval(), computeBilateralConfidenceInterval(), computeUnilateralConfidenceInterval() and computeMinimumVolumeLevelSet() methods to compute several kind of confidence regions in Distribution
* Added HarrisonMcCabe, BreuschPagan and DurbinWatson tests to test homoskedasticity, autocorrelation of linear regression residuals
* Added two samples Kolmogorov test
* Improved the speed of many algorithms based on method binding
* Added more options to control LHSExperiment and LowDiscrepancyExperiment
* Improved the IntervalMesher class: now it takes into account the diamond flag
* Shortened ResourceMap keys to not contain 'Implementation'
* Improved the performance of Classifier/MixtureClassifier/ExpertMixture
=== Bug fixes ===
* #535 (parallel-threads option cannot be changed at runtime with TBB)
* #565 (The SensitivityAnalysis class manages only one single output.)
* #604 (Bug concerning the NonCentralStudent distribution)
* #698 (KernelSmoothing() as a factory)
* #786 (Bug in sensitivity analysis)
* #802 (Python issue with ComplexMatrix::solveLinearSystem)
* #803 (prefix openturns includes)
* #813 (Error when multiplying a Matrix by a SymmetricMatrix)
* #815 (ConditionedNormalProcess test fails randomly)
* #820 (Python distribution fails randomly when computing the PDF over a sample)
* #822 (Incorect Matrix / point operations with cast)
* #824 (Confusing behavior of NumericalSample::sort)
* #828 (ImportFromCSVFile fails on a file created by exportToCSVFile)
* #830 (more optim algos examples)
* #831 (Missing get/setParameter in OpenTURNSPythonFunction)
* #833 (Homogeneity in Covariance Models)
* #837 (TruncatedDistribution::setParameter segfaults)
* #838 (Symmetry of SymmetricMatrix not always enforced)
* #840 (Remove WeightedExperiment::getWeight)
* #841 (Better CovarianceModelCollection in Python)
* #842 (Better ProcessCollection in Python)
* #843 (Remove all the specific isCopula() methods)
* #848 (Inverse Wishart sampling)
* #849 (Ambiguous NumericalSample::computeQuantile)
* #853 (Switch the default for normalize boolean from TRUE to FALSE in ot.GeneralizedLinearModelAlgorithm)
* #854 (InverseWishart.computeLogPDF)
* #861 (document HMatrix classes)
== 1.7 release (2016-01-27) == #release-1.7
=== Library ===
==== Major changes ====
* Optimization API rework
* New parametrization of covariance models
* Changed behaviour of ExponentialCauchy
* KrigingAlgorithm rework
==== New classes ====
* OptimizationSolver, OptimizationProblem
* SLSQP, LBFGS, NelderMead optimization algorithms from NLopt
* DiracCovarianceModel, TensorizedCovarianceModel
* HMatrixParameters: support class for HMat
* KarhunenLoeveP1Factory: Karhunen-Loeve decomposition of a covariance model using a P1 Lagrange interpolation
* GeneralizedLinearModelAlgorithm, GeneralizedLinearModelResult: estimate parameters of a generalized linear model
* BipartiteGraph: red/black graph
* CumulativeDistributionNetwork: high dimensional distribution using a collection of (usually) small dimension
distributions and a bipartite graph describing the interactions between these distributions
* AdaptiveStieltjesAlgorithm: orthonormal polynomials wrt arbitrary measures using adaptive integration
* MaximumLikelihoodFactory: generic maximum likelihood distribution estimation service
==== API changes ====
* Removed BoundConstrainedAlgorithm class
* Removed NearestPointAlgorithm class
* Deprecated AbdoRackwitz|Cobyla|SQP::[gs]etLevelFunction|[gs]etLevelValue
* Deprecated (AbdoRackwitz|Cobyla|SQP|TNC)SpecificParameters classes
* Replaced KrigingAlgorithm::[gs]etOptimizer methods by KrigingAlgorithm::[gs]etOptimizationSolver
* Removed ConfidenceInterval class
* Removed draw method to CovarianceModel
* Added Distribution::[sg]etParameter parameter value accessors
* Added Distribution::getParameterDescription parameter description accessor
* Deprecated method Distribution::setParametersCollection(NP)
* Removed CovarianceModel::getParameters
* Added CovarianceModel::getParameter
* Added CovarianceModel::getParameterDescription
* Moved CovarianceModel::setParameters to CovarianceModel::setParameter
* Added discretizeAndFactorize method to covariance model classes
* Added discretizeHMatrix method to covariance model classes
* Added discretizeAndFactorizeHMatrix method to covariance model classes
* Deprecated OptimizationSolver::setMaximumIterationsNumber in favor of OptimizationSolver::[sg]etMaximumIterationNumber
* Moved NumericalMathFunction::[sg]etParameters to NumericalMathFunction::[sg]etParameter
* Moved NumericalMathFunction::parametersGradient to NumericalMathFunction::parameterGradient
* Removed NumericalMathFunction::[sg]etInitial(Evaluation|Gradient|Hessian)Implementation
* Renamed DistributionImplementationFactory to DistributionFactoryImplementation
* Extended BoxCoxFactory::build to generalized linear models
=== Python module ===
* Support infix operator for matrix multiplication (PEP465)
=== Miscellaneous ===
* Enhanced print of samples
* Dropped old library wrappers
=== Bug fixes ===
* #784 (Troubles with UserDefinedFactory/UserDefined)
* #790 (AbdoRackwitz parameters)
* #796 (Beta distribution: if sample contains Inf, freeze on getSample)
* #797 (computeProbability might be wrong when distribution arithmetic is done)
* #798 (Error message misstyping (Gamma distribution))
* #799 (Error message misstyping (Gumbel distribution factory))
* #800 (Exponential distribution built on constant sample)
* #804 (no IntervalMesher documentation content)
* #805 (Python segfault in computeSilvermanBandwidth)
* #806 (DistributionImplementation::computeCDFParallel crash)
* #808 (Index check of SymmetricTensor fails when embedded within a PythonFunction)
* #812 (Sphinx documentation build error)
== 1.6 release (2015-08-14) == #release-1.6
=== Library ===
==== Major changes ====
* Improved encapsulation of hmat-oss to use H-Matrices in more classes
* Kriging metamodelling becomes vectorial
* Conditional normal realizations
* Polynomial chaos performance improvements (#413)
==== New classes ====
* VonMises, distribution
* Frechet, distribution
* ParametrizedDistribution, to reparametrize a distribution
* DistributionParameters, ArcsineMuSigma, BetaMuSigma, GumbelAB, GumbelMuSigma, GammaMuSigma, LogNormalMuSigma, LogNormalMuSigmaOverMu, WeibullMuSigma parameters
* PolygonArray, allows to draw a collection of polygons
* MarginalDistribution, MaximumDistribution, RatioDistribution, arithmetic distributions
* KrigingRandomVector
* ConditionalNormalProcess
* MetaModelValidation, for the validation of a metamodel
==== API changes ====
* Added a new draw3D() method based on Euler angles to the Mesh class.
* Changed the parameter value of the default constructor for the AliMikhailHaqCopula and FarlieGumbelMorgensternCopula classes.
* Added a new constructor to the ParametricEvaluationImplementation class.
* Added floor, ceil, round, trunc symbols to analytical function.
* Allow to save/load simulation algorithms
* Added the low order G1K3 rule to the GaussKronrodRule class.
* Added the BitCount() method to the SpecFunc class.
* Added vectorized versions of the non-uniform random generation methods in the DistFunc class.
* Added a generic implementation of the computePDF() method in the DistributionImplementation class.
* Added the computeMinimumVolumeInterval() method to compute the minimum volume interval of a given probability content to the DistributionImplementation class in the univariate case.
* Added the keys "CompositeDistribution-SolverEpsilon" and "FunctionalChaosAlgorithm-PValueThreshold" to the ResourceMap class.
* Added the max() operator as well as new versions of the algebra operators to the DistributionImplementation class.
* Added a new add() method to the ARMACoefficients class.
* Allowed to parameterize the CompositeDistribution class through ResourceMap.
* Allow the use of hmat in KrigingAlgorithm
* Added getConditionalMean method to KrigingResult
* Added getConditionalCovariance method to KrigingResult
* Added operator() to KrigingResult to get the conditional normal distribution
* Improved TemporalNormalProcess : added specific setMethod to fix numerical method for simulation
=== Python module ===
* Fixed IPython 3 inline svg conversion
* Improved sequence[-n] accessors (#760)
=== Miscellaneous ===
* Improved performance of MetropolisHastings, set default burnin=0, thin=1, non-rejected components
* Improved the coupling tools module using format mini-language spec
* Improved the pretty-printing of the LinearCombinationEvaluationImplementation class.
* Improved the draw() method of the NumericalMathEvaluationImplementation and NumericalMathFunction classes to better handle log scale.
* Improved the GaussKronrod class to avoid inf in the case of pikes in the integrand.
* Improved the numerical stability of the ATanh() method in the SpecFunc class.
* Improved many of the nonlinear transformation methods of the distribution class.
* Improved the automatic parameterization of the FunctionalChaosAlgorithm. It closes ticket #781.
* Improved the robustness of the GeneralizedParetoFactory, TruncatedNormal and MeixnerDistributionFactory classes.
* Made some minor optimizations in the TemporalNormalProcess class.
=== Bug fixes ===
* #751 (IndicesCollection as argument of Mesh)
* #772 (FORM does not work if Event was constructed from Interval)
* #773 (Problems with Event constructed from Interval)
* #779 (PolygonArray not available from python)
* #781 (failure to transform data in chaos)
* #789 (Time consuming extraction of chaos-based Sobol indices in the presence of many outputs)
* #791 (Bug in ProductCovarianceModel::partialGradient)
* #792 (PythonFunction does not check the number of input args)
== 1.5 release (2015-02-11) == #release-1.5
=== Library ===
==== Major changes ====
* PCE: polynomial cached evaluations
* Kriging: new kernels including anisotropic ones
* Distribution: more efficient algebra, more copulas and multivariate distributions
* Bayesian modeling: improved MCMC, BayesDistribution, enhanced ConditionalDistribution, conjugate priors for Normal distribution
==== New classes ====
* AggregatedProcess, allowing to stack processes with common spatial dimension
* ProductDistribution class, dedicated to the modeling of the distribution of the product of two independent absolutely continuous random variables.
* MaximumEntropyStatisticsDistribution
* MaximumEntropyStatisticsCopula
* CovarianceHMatrix, which can be used by TemporalNormalProcess to approximate covariance matrix via an H-Matrix library.
* InverseChiSquare
* InverseGamma
* NormalGamma
* OrdinalSumCopula
* MaternModel
* ProductCovarianceModel
* BoxCoxGradientImplementation
* BoxCoxHessianImplementation
* InverseBoxCoxGradientImplementation
* InverseBoxCoxHessianImplementation
* KrigingResult
* BayesDistribution
* PythonNumericalMathGradientImplementation
* PythonNumericalMathHessianImplementation
* PythonDynamicalFunctionImplementation
==== API changes ====
* Deprecated method NumericalMathFunction|NumericalMathFunctionEvaluation::getOutputHistory|getInputHistory in favor of NumericalMathFunction::getHistoryOutput|getHistoryInput
* Removed method Graph::initializeValidLegendPositions
* Renamed the getMarginalProcess() method into getMarginal() in the Process class and all the related classes.
* Deprecated methods Graph::getBitmap|getPostscript|getVectorial|getPath|getFileName
* Deprecated methods Graph::draw(path, file, width, height, format), use draw(path+file, width, height, format) instead
* Removed deprecated methods ResourceMap::SetAsUnsignedLong|GetAsUnsignedLong in favor of ResourceMap::SetAsUnsignedInteger|GetAsUnsignedInteger
* Removed deprecated methods NumericalSample::scale|translate
* Renamed the acosh(), asinh(), atanh() and cbrt() methods of the SpecFunc class into Acosh(), Asinh(), Atanh() and Cbrt() and provided custom implementations.
* Added the rUniformTriangle() method to the DistFunc class to generate uniform random deviates in a given nD triangle.
* Extended the GaussKronrod, IntegrationAlgorithm and IntegrationAlgorithmImplementation classes to multi-valued functions.
* Extended the FFT and RandomMixture classes to 2D and 3D.
* Added the setValues() method to the Field class.
* Added Simulation::setProgressCallback|setStopCallback to set up hooks
* Added the getParameterDimension() method to the NumericalMathFunction class.
* Added new parallel implementations of the discretize() and discretizeRow() methods in the CovarianceModelImplementation class.
* Added the key "Os-RemoveFiles" to the ResourceMap class.
* Added the BesselK(), LogBesselK() and BesselKDerivative() methods to the SpecFunc class.
* Added the spatial dimension information to the CovarianceModel class.
* Added a discretize() method based on sample to the CovarianceModel class.
* Added a nugget factor to all the covariance models.
* Added an history mechanism to the MCMC class.
* Added accessors to the amplitude, scale, nugget factor, spatial correlation to the CovarianceModel class.
* Added the getLogLikelihoodFunction() method to the KrigingAlgorithm class.
* Added a link function to the ConditionalDistribution class.
* Added the getMarginal(), hasIndependentCopula(), hasEllipticalCopula(), isElliptical(), isContinuous(), isDiscrete(), isIntegral() methods to the RandomMixture class.
* Added the getSupport() and the computeProbability() methods to the Mixture class.
* Added a simplified constructor to the BayesDistribution class.
* Added the computeRange() and getMarginal() methods to the BayesDistribution class.
* Added the isIncreasing() method to the Indices class.
* Added a dedicated computeLogPDF() method to the Rice class.
* Added the LargeCaseDeltaLogBesselI10() and DeltaLogBesselI10() methods to the SpecFunc class.
* Removed the useless getPartialDiscretization() method to the CovarianceModel class.
* Removed the getConditionalCovarianceModel() in the KrigingAlgorithm class.
* Renamed the getMeshDimension() method into getSpatialDimension() in the DynamicalFunction class.
* Renamed the isNormal(), isInf() and isNaN() methods into IsNormal(), IsInf() and IsNan() in the SpecFunc class.
* Removed FittingTest::GetLastResult, FittingTest::BestModel*(sample, *) in favor of FittingTest::BestModel*(sample, *, &bestResult)
* Deprecated NumericalMathFunction(Implementation)::set{Evaluation|Gradient|Hessian}Implementation in favor of NumericalMathFunction(Implementation)::set{Evaluation|Gradient|Hessian}
* Deprecated NumericalSample::compute{Range,Median,Variance,Skewness,Kurtosis,CenteredMoment,RawMoment}PerComponent
* Deprecated ProcessSample::setField(index, field) in favor of ProcessSample::setField(field, index)
=== Python module ===
* Include sphinx documentation
* Improved collection accessors
* Allow to overload gradient and hessian
* Improved viewer's integration with matplotlib api
* Added PythonDynamicalFunction to override DynamicalFunction
=== Miscellaneous ===
* In Graph::draw, the file extension overrides the format argument
* Improved the compactSupport() method of the UserDefined class. Now, it works with multidimensional distributions.
* Improved the computePDF() and computeCDF() methods of the UserDefined class.
* Improved the RandomMixture class to allow for constant distribution and Dirac contributors.
* Added /FORCE option to windows installer to allow out-of-python-tree install
* Added a generic implementation of the getMarginal() method to the Process class for 1D processes.
* Added a description to all the fields generated by a getRealization() method of a process.
* Changed the values of the keys ConditionalDistribution-MarginalIntegrationNodesNumber, KernelSmoothing-BinNumber, SquaredExponential-DefaultTheta, AbsoluteExponential-DefaultTheta, GeneralizedExponential-DefaultTheta in the ResourceMap class and the openturns.conf file.
* Changed the parameterization of the AbsoluteExponential, GeneralizedExponential and SquaredExponential classes.
* Changed the default parameterization of the ComposedCopula, ConditionalDistribution, AliMikhailHaqCopula, FarlieGumbelMorgensternCopula, KernelMixture, Mixture and NormalCopula classes.
* Changed the default presentation of analytical functions.
* Changed the parameters of the default distribution of the FisherSnedecor class.
* Changed the algorithm used in the FisherSnedecorFactory class. Now the estimation is based on MLE.
* Extended the Debye() method of the SpecFunc class to negative arguments.
* Extended the computeCDF(), computeDDF(), computeProbability() methods of the RandomMixture class.
* Extended the ConditionalDistribution class to accept a link function.
* Extended the build() method of the IntervalMesher class to dimension 3.
* Improved the capabilities of the KrigingAlgorithm class. Now it can use anisotropic covariance models.
* Improved the __str__() method of the CompositeDistribution class.
* Improved the numerical stability of the computeCharacteristicFunction() in the Beta class.
* Improved the distribution algebra in the DistributionImplementation class.
* Improved the getKendallTau() and computeCovariance() methods of the SklarCopula class.
* Improved the Gibbs sampler in the TemporalNormalProcess class.
* Improved the presentation of the graphs generated by the drawPDF() and drawCDF() methods of the distributions.
* Improved the messages sent by the NotYetImplementedException class.
* Improved the pretty-print of the NumericalMathFunction class.
* Improved the HistogramFactory and KernelSmoothing classes by using inter-quartiles instead of standard deviations to estimate scale parameters.
* Improved the management of small coefficients in the DualLinearCombinationEvaluationImplementation class.
* Improved the algorithms of the getRealization() and computePDF() methods of the Rice class.
* Improved the operator() method of the PiecewiseLinearEvaluationImplementation class.
=== Bug fixes ===
* #614 (FORM Method - Development of sensitivity and importance factors in the physical space)
* #673 (Perform the computeRange method of the PythonDistributionImplementation class)
* #678 (Pretty-printer for gdb)
* #688 (incorrect analytical gradient)
* #704 (Problem with Exception)
* #709 (MatrixImplementation::computeQR issues)
* #713 (Dirichlet hangs on np.nans)
* #720 (Missing LHSExperiment::getShuffle)
* #721 (Python implementation of a NumericalMathGradientImplementation)
* #731 (Problems with Rice and FisherSnedecor distributions)
* #736 (Graph : keep getBitmap, getVectorial, getPDF, getPostScript, initializeValidLegendPositions?)
* #737 (Bug in composeddistribution inverse iso-probabilistic transformation in the ellipical distribution case )
* #738 (Incorrect pickling of ComposedDistribution with ComposedCopula)
* #739 (Bug in the SpecFunc::LnBeta() method)
* #744 (Incorrect iso-probabilistic transformation for elliptical ComposedDistribution)
* #745 (DirectionalSampling: ComposedCopula bug and budget limitation ignored)
* #747 (Packaging for conda)
* #748 (Can't add sklar copula to CopulaCollection)
* #754 (Bad conversion list to python with negative integer)
* #755 (inconsistency in functions API)
* #757 (Spearman correlation in CorrelationAnalysis)
* #759 (Problem with RandomMixture::project)
* #762 (NumericalSample's export produce empty lines within the Windows environment)
* #763 (Missing description of samples with RandomVector realizations)
* #764 (RandomVector's description)
* #769 (Dirichlet behaves strangely on constant)
* #770 (Problem with FittingTest based on BIC)
== 1.4 release (2014-07-25) == #release-1.4
=== Library ===
==== Major changes ====
* Native windows support, OT.dll can be generated by MSVC compilers; Python bindings not yet available
* 64bits windows support
* Python docstrings work started
* Major speed improvement for random fields
==== New distributions ====
* Wishart
* InverseWishart
* CompositeDistribution
==== New classes ====
* KrigingResult
* LevelSet
* KDTree
* ExponentiallyDampedCosineModel
* SphericalModel
* MeshFactory
* IntervalMesher
* ParametricEvaluationImplementation
* ParametricGradientImplementation
* ParametricHessianImplementation
==== API changes ====
* Removed deprecated types UnsignedLong, IndexType in favor of UnsignedInteger, SignedInteger
* Deprecated method ResourceMap::SetAsUnsignedLong|GetAsUnsignedLong in favor of ResourceMap::SetAsUnsignedInteger|GetAsUnsignedInteger
* Removed method ResourceMap::GetAsNewCharArray
* Renamed Matrix::computeSingularValues(u, vT) to computeSVD(u, vT)
* Renamed MatrixImplementation::computeEigenValues(v) to computeEV(v)
* Added Matrix::computeTrace
* Renamed WeightedExperiment::generate(weights) to WeightedExperiment::generateWithWeights(weights)
* Removed DistributionImplementation::getGaussNodesAndWeights(void)
* Removed DescriptionImplementation class
* Removed deprecated method NumericalPoint::norm2 in favor of normSquare, normalize2 in favor of normalizeSquare
* Removed deprecated method SpectralModel::computeSpectralDensity
* Deprecated method NumericalSample::scale|translate
=== Python module ===
* Docstring documentation, can be used in combination with sphinx (in-progress)
* Added Drawable|Graph::_repr_svg_ for automatic graphing within IPython notebook
* Added Object::_repr_html_ to get html string representation of OpenTURNS objects
* Some methods no longer return argument by reference, return tuple items instead (see #712)
=== Miscellaneous ===
* DrawHenryLine now works for any Normal sample/distribution.
* Added a DrawHenryLine prototype with given Normal distribution.
* Added a add_legend=True kwarg to openturns.viewer.View.
* New arithmetic on Distribution (can add/substract/multiply/divide/transform by an elementary function)
* New arithmetic on NumericalMathFunction (can add/substract/multiply)
* New arithmetic on NumericalSample (can add/substract a scalar, a point or a sample, can multiply/divide by a scalar, a point or a square matrix)
=== Bug fixes ===
* #693 (Distribution.computeCDFGradient(NumericalSample) segfaults)
* #697 (Problem with LogNormal on constant sample)
* #700 (Problem with MeixnerDistribution (continuation))
* #706 (rot tests fail with r 3.1.0)
* #707 (Error when executing ot.Multinomial().drawCDF())
* #708 (Typing across OpenTURNS matrices hangs, fills RAM and is eventually killed)
* #710 (Slicing matrices)
* #718 (DirectionalSampling does not set the dimension of the SamplingStrategy)
* #712 (do not pass python arguments as reference)
* #722 (Problem with drawPDF() for Triangular distribution)
* #725 (Remove NumericalSample::scale/translate ?)
* #726 (Defect in the Multinomial distribution constructor)
== 1.3 release (2014-03-06) == #release-1.3
=== Library ===
==== Major changes ====
* Extended process algorithms to stochastic fields
* Kriging metamodelling
* Optionally use Boost for better distribution estimations
==== New kriging classes ====
* KrigingAlgorithm
* KrigingGradient
* SquaredExponential
* GeneralizedExponential
* AbsoluteExponential
* ConstantBasisFactory
* LinearBasisFactory
* QuadraticBasisFactory
==== New classes ====
* Skellam
* SkellamFactory
* MeixnerDistribution
* MeixnerDistributionFactory
* GaussKronrod
* GaussKronrodRule
* TriangularMatrix
* QuadraticNumericalMathFunction
==== API changes ====
* Removed framework field in generic wrapper
* Added the getVerticesNumber(), getSimplicesNumber() and getClosestVertexIndex() methods to the Mesh class.
* Renamed the getClosestVertexIndex() method into getNearestVertexIndex() in the Mesh class.
* Added the computeSurvivalFunction() method to distributions
* Added the getSpearmanCorrelation() and getKendallTau() to distributions
* Added the DiLog() and Log1MExp() methods to the SpecFunc class.
* Added the LogGamma() and Log1p() functions of complex argument to the SpecFunc class.
* Added the setDefaultColors() method to the Graph class.
* Added the computeLinearCorrelation() method as an alias to the computePearsonCorrelation() method of the NumericalSample class.
* Added two in-place division operators to the NumericalSample class.
* Added the getShapeMatrix() method to the NormalCopula, Copula, Distribution and DistributionImplementation classes.
* Added the getLinearCorrelation() and getPearsonCorrelation() aliases to the getCorrelation() method in the Distribution and DistributionImplementation classes.
* Added a new constructor to the SimulationSensitivityAnalysis class.
* Added the stack() method to the NumericalSample class.
* Added the inplace addition and soustraction of two NumericalSample with same size and dimension.
* Removed the TimeSeriesImplementation class.
* Added the isBlank() method to the Description class.
* Added a new constructor to the Cloud, Curve and Polygon classes.
* Added an optimization for regularly discretized locations to the PiecewiseHermiteEvaluationImplementation and PiecewiseLinearEvaluationImplementation classes.
* Added the streamToVTKFormat() method to the Mesh class.
* Create the RandomGeneratorState class and allow to save and load a RandomGeneratorState.
* Allow the use of a sample as operator() method argument of the AnalyticalNumericalMathEvaluationImplementation class.
* Removed deprecated method Distribution::computeCDF(x, tail)
* Removed deprecated method Curve::set|getShowPoints
* Removed deprecated method Drawable::set|getLegendName
* Removed deprecated method Pie::Pie(NumericalSample), Pie::Pie(NumericalSample, Description, NumericalPoint)
* Deprecated method NumericalPoint::norm2 in favor of normSquare, normalize2 in favor of normalizeSquare
=== Python module ===
* Added NumericalSample::_repr_html_ for html representation in IPython
* Allow to reuse figure/axes instances from matplotlib viewer
* PythonFunction now prints the complete traceback
=== Miscellaneous ===
* Improved numerical stability of InverseNormal
* Preserve history state in the marginal function.
* Port to MinGW-w64 3.0 CRT
* Added a new simplification rule to the MarginalTransformationEvaluation for the case where the input and output distributions are linked by an affine transformation.
* Propagated the use of potential parallel evaluations of the computeDDF(), computePDF() and computeCDF() methods in many places, which greatly improves the performance of many algorithms.
* Allowed for non-continuous prior distributions in the MCMC class.
=== Bug fixes ===
* #442 (OT r1.0 Box Cox is only for Time Series Not for Linear Model)
* #506 (There are unit tests which fail on Windows with OT 1.0)
* #512 (The documentation is not provided with the Windows install)
* #589 (The Histogram class is too complicated)
* #640 (Optional values formatting in coupling_tools.replace)
* #643 (Problem with description in graph)
* #645 (Problem to build a truncated normal distribution from a sample)
* #647 (cannot save a NumericalMathFunction issued from PythonFunction)
* #648 (wrong non-independent normal ccdf)
* #649 (Loss of accuracy in LogNormal vs Normal MarginalTransformation (in the (very) far tails))
* #650 (OpenTURNS has troubles with spaces in path names)
* #651 (The generalized Nataf transformation is unplugged)
* #652 (Problem with setParametersCollection() in KernelSmoothing)
* #657 (RandomWalkMetropolisHastings moves to zero-probability regions)
* #661 (Problem with getParametersCollection() while using KernelSmoothing)
* #664 (AggregatedNumericalMathEvaluationImplementation::getParameters is not implemented)
* #667 (Missing draw quantile function in distribution class)
* #668 (__str__ method of the Study object occasionally throws an exception)
* #669 (Bad export of NumericalSample)
* #670 (TruncatedDistribution)
* #672 (Multivariate python distribution requires getRange.)
* #674 (python nmf dont force cache)
* #675 (Bug with standard deviation evaluation for UserDefined distribution with dimension > 1)
* #676 (DistributionCollection Study::add crash)
* #677 (Error in SobolSequence.cxx on macos 10.9 with gcc4.8)
* #681 (Incomplete new NumericalSample features regarding operators)
* #682 (dcdflib.cxx license does not comply with Debian Free Software Guidelines)
* #683 (Normal)
* #685 (muParser.h not installed when using ExternalProject_Add)
* #686 (Probabilistic model with SklarCopula can't be saved via pickle)
* #687 (Segfault using BIC and SklarCopula)
* #688 (incorrect analytical gradient)
* #691 (Strange behavior of convergence graph)
== 1.2 release (2013-07-26) == #release-1.2
=== Library ===
==== New combinatorial classes ====
* KPermutations
* KPermutationsDistribution
* Tuples
* CombinatorialGenerator
* Combinations
==== New classes ====
* PiecewiseEvaluationImplementation
* GeneralizedPareto
* GeneralizedParetoFactory
* RungeKutta
==== API changes ====
* Switched from getLegendName() and setLegendName() to getLegend() and setLegend() in the drawables.
* Extended the add() method of the Collection class to append a collection to a given collection;
* Extended the add() method of the Graph class in order to add another Graph.
* Added the getCallsNumber() method to the NumericalMathFunction class.
* Removed deprecated methods getNumericalSample in Distribution, RandomVector, TimeSeries, and TimeSeries::asNumericalSample.
* Removed deprecated methods HistoryStrategy::reset, and resetHistory in NumericalMathFunction, NumericalMathFunctionImplementation, NumericalMathEvaluationImplementation
* Removed deprecated method Distribution::computeCharacteristicFunction(NumericalScalar x, Bool logScale)
* Removed deprecated method Distribution::computeGeneratingFunction(NumericalComplex z, Bool logScale)
* Removed deprecated method Distribution::computeCDF(x, tail)
==== Python module ====
* The distributed python wrapper is now shipped separately
* No more need for base class casts
* Enhanced collection classes wrapping: no more need for NumericalMathFunctionCollection, DistributionCollection, ...
* Introduced pickle protocol support
==== Miscellaneous ====
* Modified the matplotlib viewer in order to use color codes instead of color names, to avoid errors when the color name is not known by matplotlib.
* Added a binning capability to the KernelSmoothing class. It greatly improves its performance for large samples (300x faster for 10^6 points and above)
* Changed the definition of the sample skewness and kurtosis. Now, we use the unbiased estimators for normal populations.
* Changed back to the first (thinest) definition of hyperbolic stratas. Added a function to control the number of terms per degree.
==== Bug fixes ====
* #411 (Long time to instanciate a NumericaMathFunction (analytical function))
* #586 (The Pie graphics could be easily improved.)
* #593 (Can't draw a Contour drawable with the new viewer)
* #594 (Useless dependency to R library)
* #595 (Bug in distributed_wrapper if tmpdir point to a network filesystem)
* #596 (Bug in distributed_wrapper if files_to_send are not in current directory.)
* #597 (The SWIG typemap is still failing to assign some prototypes for overloaded basic objects)
* #598 (distributed_wrapper do not kill remote sleep process.)
* #599 (Wrong quantile estimation in Histogram distribution)
* #600 (Please remove timing checks from python/test/t_coupling_tools.py)
* #606 (Too permissive constructors)
* #608 (Distributed_python_wrapper : files permissions of files_to_send parameter are not propagated)
* #609 (How about implementing a BlatmanHyperbolicEnumerateFunction?)
* #612 (Missing description using slices)
* #616 (PythonDistribution)
* #619 (chaos rvector from empty chaos result segfault)
* #620 (LogNormalFactory does not return a LogNormal)
* #622 (undetermined CorrectedLeaveOneOut crash)
* #630 (Fix build failure with Bison 2.7)
* #634 (NMF bug within the python api)
* #637 (The docstring of coupling_tools is not up-to-date.)
* #638 (libopenturns-dev should bring libxml2-dev)
== 1.1 release == #release-1.1
=== Library ===
New stochastic process classes:
* ARMALikelihood
* ARMALikelihoodFactory
* UserDefinedStationaryCovarianceModel
* StationaryCovarianceModelFactory
* UserDefinedCovarianceModel
* CovarianceModelFactory
* NonStationaryCovarianceModel
* NonStationaryCovarianceModelFactory
* DickeyFullerTest
New bayesian updating classes:
* RandomWalkMetropolisHastings
* MCMC
* Sampler
* CalibrationStrategy
* PosteriorRandomVector
New distributions:
* AliMikhailHaqCopula
* AliMikhailHaqCopulaFactory
* Dirac
* DiracFactory
* FarlieGumbelMorgensternCopula
* FarlieGumbelMorgensternCopulaFactory
* FisherSnedecorFactory
* NegativeBinomialFactory
* ConditionalDistribution
* PosteriorDistribution
* RiceFactory
New classes:
* FunctionalBasisProcess
* Classifier
* MixtureClassifier
* ExpertMixture
* Mesh
* RestrictedEvaluationImplementation
* RestrictedGradientImplementation
* RestrictedHessianImplementation
==== API changes ====
* Changed the way the TrendFactory class uses the basis. It is now an argument of the build() method instead of a parameter of the constructor.
* Deprecated Distribution::getNumericalSample, RandomVector::getNumericalSample, TimeSeries::getNumericalSample, and TimeSeries::asNumericalSample (getSample)
* Deprecated Distribution::computeCharacteristicFunction(NumericalScalar x, Bool logScale) (computeCharacteristicFunction/computeLogCharacteristicFunction)
* Deprecated Distribution::computeGeneratingFunction(NumericalComplex z, Bool logScale) (computeGeneratingFunction/computeLogGeneratingFunction)
* Deprecated Distribution::computeCDF(x, Bool tail) (computeCDF/computeComplementaryCDF)
* Removed SVMKernel, SVMRegression classes
* Added samples accessors to MetaModelAlgorithm.
* Added AggregatedNumericalMathEvaluationImplementation::operator()(NumericalSample)
* Deprecated PlatformInfo::GetId.
* Added a draw() method to the NumericalMathFunction class.
* Changed the return type of the build() method for all the DistributionImplementationFactory related classes. Now, it returns a smart pointer on a DistributionImplementation rather than a C++ pointer. It closes the memory leak mentioned in ticket #545.
* Changed the return type of the getMarginal() method of the DistributionImplementation, RandomVectorImplementation and ProcessImplementation related classes. Now, it returns smart pointers instead of C++ pointers to avoid memory leak.
=== Python module ===
* DistributedPythonFunction: new python wrapper module, which allows to launch a function
to several nodes and cores in parallel
* PythonFunction: added simplified constructor for functions
* New matplotlib viewer as replacement for rpy2 & qt4 routines
* Added PythonRandomVector, PythonDistribution to overload Distribution & RandomVector objects
* Added NumericalSample, NumericalPoint, Description, Indice slicing
* Added automatic python conversion to BoolCollection
* Allowed use of wrapper data enums using their corresponding xml tags
=== Miscellaneous ===
* Added NumericalMathFunction::clearCache
* CMake: MinGW build support
* CMake: completed support for UseOpenTURNS.config
* Added quantile function on a user-provided grid.
* Added the SetColor() and GetColor() methods to the Log class.
* Added row and column extraction to the several matrices.
* Added the getInverse() method to the TrendTransform and InverseTrendTransform classes.
* Improved the generic implementation of the computeQuantile() method in the CopulaImplementation class.
* Improved the labeling of the Kendall plot in the VisualTest class.
* Improved the robustness of the BestModelBIC(), BestModelKolmogorov() and BestModelChiSquared() methods in the FittingTest class.
* Ship openturns on windows as a regular python module.
* R & R.rot as only runtime dependencies.
* Improved the pretty-printing of many classes.
* Added a constructor based on the Indices class to the Box class.
==== Bug fixes ====
* #403 (do not display the name if object is unamed)
* #424 (OT rc1.0 Ipython interactive mode: problem with "ctrl-c")
* #429 (OT r1.0 Creation of a NumericalSample with an np.array of dimension 1)
* #471 (The key 'BoxCox-RootEpsilon' is missing in the ResourceMap object)
* #473 (Bug with generic wrapper)
* #479 (Wrong output of getRealization() for the SpectralNormalProcess class when dimension>1)
* #480 (Wrong random generator for the NegativeBinomial class)
* #482 (Build failure with g++ 4.7)
* #487 (Wrong output of getRealization() for the Event class built from a domain and a random vector when dimension>1)
* #488 (The getConfidenceLength() method of the SimulationResult class does not take the given level into account)
* #495 (g++ 4.7 miscompiles OT)
* #496 (Missing name of DistributionFactories)
* #497 (Spurious changes introduced in Python docstrings (r1985))
* #504 (Bad size of testResult in HypothesisTest)
* #509 (I cannot install OT without admin rights)
* #510 (Cast trouble with DistributionCollection)
* #518 (DistributionCollection does not check indices)
* #537 (Downgrade of numpy version at the installation of openturns)
* #538 (Please remove CVS keywords from source files (2nd step))
* #541 (LogUniform, Burr distributions: incorrect std dev)
* #542 (Bad default constructor of TruncatedNormal distribution)
* #549 (OpenTURNSPythonFunction attributes can be inadvertendly redefined)
* #551 (The generic wrapper fails on Windows)
* #556 (OpenTURNSPythonFunction definition)
* #560 (Missing getWeights method in Mixture class)
* #561 (The Windows installer does not configure the env. var. appropriately.)
* #562 (wrong value returned in coupling_tools.get_value with specific parameters.)
* #572 (Various changes in distribution classes)
* #576 (DrawHistogram fails with a constant NumericalSample)
* #580 (ExpertMixture marginal problem)
* #581 (ExpertMixture Debug Message)
* #583 (Missing description when using NumericalMathFunction)
* #584 (ComposedDistribution description)
* #586 (The Pie graphics could be easily improved.)
* #587 (Cannot save a NumericalMathFunction if built from a NumericalMathEvaluationImplementation)
* #592 (View and Show)
== 1.0 release == #release-1.0
==== Library ====
Introducing stochastic processes modelling through these classes:
* TimeSeries
* TimeGrid
* ProcessSample
* SecondOrderModel
* TemporalFunction
* SpatialFunction
* DynamicalFunction
* ARMA
* ARMACoefficients
* ARMAState
* Process
* NormalProcess
* CompositeProcess
* TemporalNormalProcess
* SpectralNormalProcess
* WhiteNoise
* RandomWalk
* WhittleFactory
* Domain
* FilteringWindows
* RegularGrid
* WelchFactory
* WhittleFactory
* SpectralModel
* ExponentialModel
* CauchyModel
* UserDefinedSpectralModel
* SpectralModel
* CovarianceModel
* InverseBoxCoxTransform
* BoxCoxTransform
* BoxCoxFactory
* BoxCoxEvaluationImplementation
* InverseBoxCoxEvaluationImplementation
* ComplexMatrix
* TriangularComplexMatrix
* HermitianMatrix
* FFT
* KissFFT
* TrendTransform
New classes:
* Added the NegativeBinomial class.