Openturns

=== 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 one 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 unnamed)
* 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)

==== 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.
* Added the MeixnerFactory class, in charge of building the orthonormal basis associated to the negative binomial distribution.
* Added the HaselgroveSequence class, which implements a new low discrepancy sequence based on irrational translations of the nD canonical torus.
* Added the RandomizedLHS, RandomizedQuasiMonteCarlo classes.

Enhancements:
* Added an history mechanism to all the NumericalMathFunction types. It is deactivated by default, and stores all the input and output values of a function when activated.
* Fixed callsNumbers being incorrecly incremented in ComputedNumericalMathEvaluationImplementation.
* Added getCacheHits, addCacheContent methods to NumericalMathFunction
* Improved the speed and accuracy of moments computation for the ZipfMandelbrot distribution.
* Added the getMarginal() methods to the UserDefined class.
* Added the MinCopula class.
* Improved the buildDefaultLevels() method of the Contour class. Now, the levels are based on quantiles of the value to be sliced.
* Improved the drawPDF() and drawCDF() methods of the CopulaImplementation class.
* Restored the ability to compute importance factors and mean point in event domain to the SimulationResult class, using the SimulationSensitivityAnalysis class.
* Improved the StandardDistributionPolynomialFactory class to take into account the NegativeBinomial special case using Meixner factory.
* Added methods to define color using the Hue, Saturation, Value color space to the Drawable class.
* Added the isDiagonal() method to the SymmetricMatrix class.
* Improved the use of ResourceMap throughout the library.
* The input sample of the projection strategy is stored in the physical space in all circumstances.
* Parallelized NumericalSample::computeKendallTau() method.
* Improved the FunctionalChaosRandomVector: it is now based on the polynomial meta model in the measure space instead of the input distribution based random vector. It provides the same output distribution for much cheaper realizations.
* Improved the performance of the RandomMixture class. Now, all the Normal atoms are merged into a unique atom, which greatly improve the performance in case of random mixture of many such atoms.
* Fixed bug in NumericalSample::exportToCSV method.

==== API changes ====
* deprecated Interval::isNumericallyInside(const NumericalPoint & point) in favor of numericallyContains(const NumericalPoint & point)
* removed deprecated class SobolIndicesResult.
* removed deprecated class SobolIndicesParameters.
* removed deprecated method CorrelationAnalysis::SobolIndices.
* Removed FunctionCache in favor of in/out History.
* Added 2 mandatory macros for wrappers: WRAPPER_BEGIN and WRAPPER_END.

=== Python module ===
* Added Matrix / Tensor / ComplexMatrix conversion from/to python sequence/list/ndarray
* Added typemaps to convert directly Indices and Description object from python sequences
* Added operators NumericalPoint::__div__, __rmul__; NumericalSample::operator==; Matrix::__rmul__.
* Fixed a memory leak in PythonNumericalMathEvaluationImplementation.

=== Miscellaneous ===
* Added patch for OSX build
* Updated the MuParser version. OpenTURNS is now based on MuParser version 2.0.0.
* Moved the Uncertainty/Algorithm/IsoProbabilisticTransformation folder into Uncertainty/Algorithm/Transformation folder, in order to prepare the development of the process transformations.
* Added colorization to make check and make installcheck outputs.
* Windows (un)installer can be run in quiet mode (e.g. openturns-setup-1.0.exe /S /D=C:\Program Files\OpenTURNS).
* Windows installer can avoid admin check (e.g. openturns-setup-1.0.exe /userlevel=[0|1]).
* The windows python example uses NumericalPythonMathFunction and can launch several external application in parallel.

==== Bug fixes ====
* 300 (openturns_preload makes it harder to bypass system libraries)
* 365 (LeastSquaresStrategy sample constructor)
* 366 (ProjectionStrategy's input sample gets erased)
* 369 (ndarray of dimension > 1 casts into NumericalPoint)
* 371 (Invalid DistributionImplementation::computeCDF dimension)
* 376 (Confidence intervals for LHS and QMC / RQMC implementation)
* 377 (Save a study crash after remove object)
* 378 (CMake always calls swig even if source files have not changed)
* 379 (Computation of the Cholesky factor)
* 380 (Ease customizing installation paths with CMake)
* 381 (Indices typemap)
* 382 (CorrelationMatrix::isPositiveDefinite crashes when matrix empty)
* 387 (cmake installs headers twice)
* 388 (Broken illegal argument detection in TimeSeries[i,j])
* 389 (Bug in ARMA prediction)
* 390 (Reorder tests launched by CMake to mimic Autotools)
* 398 (Cannot copy a TimeSeries in TUI)
* 399 (Wrong automatic cast of TimeSeries into NumericalSample in TUI)
* 400 (segmentation fault with TBB and GCC 4.6)
* 405 (missing headers in libopenturns-dev)
* 406 (Calcul quantiles empiriques)
* 407 (print fails with a gradient)
* 410 (Problem with getMarginal on a NumericalMathFunction)
* 414 (Fix compiler warnings)
* 417 (Minor bug in FFT)
* 418 (Problem in SpectralNormalProcess)
* 420 (File WrapperCommon_static.h forgotten during the installation (make install) ?)
* 421 (Problem when testing the wrapper template wrapper_calling_shell_command)
* 423 (OT rc1.0 Bug while creating a NumericalPoint with a numpy array)
* 425 (OT r1.0 Bug while creating a Matrix with a numpy matrix)
* 432 (TemporalNormalProcess bad dimension)
* 434 (Missing copyOnWrite() in TimeSeries.getValueAtIndex())
* 436 (Wrong results when using external code wrapper with openturns not linked to TBB and input provided in the command line)
* 445 (slow NumericalSample deepcopy)
* 464 (dimension not checked in NumericalSample)
* 465 (The ViewImage function makes a cmd.exe console appear (on Windows))

=== Library ===
Sparse polynomial chaos expansion:
* LAR algorithm
* CorrectedLeaveOneOut cross-validation
* KFold cross-validation

New distributions:
* Burr
* InverseNormal

New classe:
* BlendedStep: proportional finite difference step
* DualLinearCombination NumericalMathFunctions classes
* CharlierFactory class, which provides orthonormal polynomials for the Poisson distribution.
* KrawtchoukFactory class, which provides orthonormal polynomials for the Binomial distribution.

Enhancements:
* Added the DrawKendallPlot() method to the VisualTest class.
* SensitivityAnalysis uses efficient Saltelli's algorithm implementation without relying on R-sensitivity

==== Bug fixes ====
* 344
* 322
* 324
* 319
* 307
* 302
* 227
* 337
* 350
* 338
* 308

=== Python module ===

* Numpy arra type conversion
* Ability to pickle an OpenTURNSPythonFunction

==== Bug fixes ====

* 343
* 284
* Better handling of python exception in python NumericalMathFunction

{{{
!html
<h1 style="color: red">
WARNING: There is a bug regarding the iso-probabilistic transformation<br> affecting all the algorithms working in the standard space (FORM/SORM, chaos PCE, directional sampling),<br>
as a result the values provided can be biased in certain cases.
</h1>
}}}




=== Library ===

==== Enhancements ====
New distributions:
* Arcsine
* ArcsineFactory
* Bernoulli
* BernoulliFactory
* Burr
* BurrFactory
* Chi
* ChiFactory
* Dirichlet
* DirichletFactory
* FisherSnedecor
* InverseNormal
* InverseNormalFactory
* Multinomial
* MultinomialFactory
* NonCentralChiSquare
* Rice
* Trapezoidal
* TrapezoidalFactory
* ZipfMandelBrot
New differentation classes:
* FiniteDifferenceGradient
* FiniteDifferenceHessian
* FiniteDifferenceStep
* ProportionalStep
* ConstantStep
New low discrepancy sequences:
* InverseHaltonSequence
* FaureSequence
New classes:
* TBB
* TTY
* HyperbolicAnisotropicEnumerateFunction

Enhancement of existing classes:
* Wrappers library:
* IO performance
* Better error handling
* Massive parallelization support: tested up to 1k threads and 10e7 points
* Generic wrapper (no compilation required anymore)
* NumericalSample
* Use of TBB library for multithreading
* New imlementation allowing storage up to 8Gb
* Added clear() method to erase all content
* Added merge() method to merge two instances
* New accessors
* Pretty print for the following classes:
* Accessors to a composition of NumericalMathFunctions
* Aggregated functions
* FunctionalChaosAlgorithm allows for a multivariate model
* Automatic differentiation of analytical formulas
* Enhancement of distributions:
* Enhanced PDF/CDF drawing for discrete distributions
* Generic realization implementation for n-d distributions
* LogNormalFactory uses maximum likeliHood
* NormalCopulaFactory uses Kendall tau
* HistogramFactory based on Scott estimator
* Implementation of the RosenBlatt transformation
* Enhancement of graphs:
* Line width setting for StairCase and BarPlot
* CobWeb plot
* Copula fitting test (Kendall plot)
* Cloud from complex numbers


Methods:
* Added a constructor based on two input/output NumericalSamples to the NumericalMathFunction allowing to use the FunctionalChaos provided a sample.
* Added the getProjectionStrategy() method to FunctionalChaosAlgorithm allowing to retrieve the design experiment generated.


==== Miscellaneous ====
General:
* Compatibility with r-sensitivity > 1.3.1
* CMake compatibility

Moved classes:
* LeastSquares, QuadraticLeastSquares, LinearTaylor, QuadraticTaylor got moved to Base/MetaModel

==== Bug fixes ====
Fixes:
* Fixed Mixture distribution

=== Python module ===
==== Enhancements ====
* No more upcasting necessary for the following classes:
* Distribution
* HistoryStrategy

==== Bug fixes ====
* Less RAM required to build openturns thanks to new module dist
* Compatibility with swig 2
* Correct install on OSes that use a lib64 dir on x86_64 arch (rpm distros)

==== Miscellaneous ====
* Added some docstring to the main module

----

=== Library ===

==== Enhancements ====
New classes:
* BootstrapExperiment
* ChebychevAlgorithm
* ConditionalRandomVector
* GaussProductExperiment
* GramSchmidtAlgorithm
* HaltonSequence
* OrthogonalUnivariatePolynomial
* OrthonormalizationAlgorithm
* Os
* StandardDistributionPolynomialFactory

Enhancement of existing classes:
* Pretty print for the following classes:
* NumericalSample
* Matrix
* UniVariatePolynomial
* New generic algorithm for the computeCovariance() and computeShiftedMoment() methods for the continuous distributions.
* Improved the CSV parser of the NumericalSample class. It can now cope with the various end of line conventions and any kind of blank characters in lines.
* Improved the CSV export by adding the description of the NumericalSample into the resulting file.
* The default constructor of a CovarianceMatrix now initializes it to the identity matrix.
* It is now possible to compute the tail quantile and tail CDF of any distribution.

Methods:
* Added the getStandardMoment() method that computes the raw moments of the standard version of the distribution for the following ones:
* Beta
* ChiSquare
* Exponential
* Laplace
* Logistic
* LogNormal
* Normal
* Rayleigh
* Student
* Triangular
* Uniform
* Weibull
* setAlphaBeta() method to set simultaneously the two parameters of a Weibull distribution.
* setParametersCollection() and getParametersCollection() for the Student distribution.
* Added a constructor based on a NumericalSample and the optional corresponding weights to the UserDefined distribution.
* Added two new methods for the computation of the bandwidth in the 1D case to the KernelSmoothing class, namely the computePluginBandwidth() and computeMixedBandwidth() methods.
* Added the getMoment() and getCenteredMoment() methods to the Distribution class, with a generic implementation.
* Added the setDistribution() method to the LHSExperiment class.
* Added the getRoots() and getNodesAndWeights() methods to the OrthogonalUniVariatePolynomial and OrthogonalProductPolynomialFactory classes.
* Added a constructor from two 1D NumericalSample to the cloud class.
* Added the PDF format as export formats to the Graph class.
* Added the computeSingularValues() method to the Matrix class.
* Added a fill() method to the Indices class, that aloows to fill an Indices object with the terms of an arithmetic progression.
* Added a constructor from a collection of String to the Description class.
* Added a getNumericalVolume() method to the Interval class. It computes the volume of the interval based on its numerical bounds, which gives a finite number even for infinite intervals.
* Added the printToLogDebug(), setWrapperError(), clearWrapperError(), getWrapperError() methods to the WrapperCommonFunctions class.
* Added the setError() function to the WrapperCommon class.
* Added the GetInstallationDirectory(), GetModuleDirectory(), CreateTemporaryDirectory(), DeleteTemporaryDirectory() methods to the Path class.
* Added the getReccurenceCoefficients() method to the OrthogonalUnivariatePolynomialFamily class to give access to the three term reccurence coefficients verified by an orthonormal family of univariate polynomials.
* Added a generate() method that also gives access to the weigths of the realizations to all the weighted experiements, namely:
* BootstrapExperiment
* FixedExperiment
* ImportanceSamplingExperiment
* LHSExperiment
* LowDiscrepancyExperiment
* MonteCarloExperiment

==== Miscellaneous ====
General:
* Added the ability to set the log severity through the environment variable OPENTURNS_LOG_SEVERITY.
* Deactivated the cache by default in the NumericalMathFunction class.
* Added a warning about the use of the default implementation of the gradient and hessian in the NumericalMathFunction class.
* Removed the exception declarations to all the methods.

Moved classes:
* LeastSquaresAlgorithm became PenalizedLeastSquaresAlgorithm, which allows one to specify a general definite positive L2 penalization term to the least squares optimization problem.
* Removed the classes related to the inverse marginal transformation: they have been merged with the corresponding marginal transformation classes.
* Moved the BoundConstrainedAlgorithmImplementation::Result class into the BoundConstrainedAlgorithmImplementationResult class to ease the maintenance of the TUI.

==== Bug fixes ====
Fixes:
* Unregistered Weibull factory.
* Very bad performance of wrappers on analytical formulas.
* The computeCDF() method of the UserDefined distribution invert the meaning of the tail flag.
* Compilation options defined by OpenTURNS have errors.
* And many more little bugs or missing sanity tests that have been added along the lines...

=== Python module ===
==== Enhancements ====
* Any collection of objects can now be built from a sequence of such objects.
* Improved the compatibility between the OpenTURNS classes and the Python structures. The following classes can now be built from Python sequences:
* ConfidenceInterval
* Description
* Graph
* Histogram
* HistogramPair
* Indices
* Interval
* NumericalPoint
* NumericalPointWithDescription
* TestResult
* UniVariatePolynomial
* UserDefinedPair
* Improved the use of interface classes in place of implementation classes: it removes the need to explicitly cast an implementation class into an interface class.
* Split the module into 16 sub-modules, to allow for a fine grain loading of OpenTURNS.

==== Bug fixes ====
* 1Gb of RAM required to build openturns

==== Miscellaneous ====
* The ViewImage facility is now based on Qt4.
* The Show facility is now based on rpy2, with an improved stability.

=== Documentation ===
see [wiki:NewFeaturesDocJanuary2010 here]

----

=== Library ===

==== Enhancements ====
New classes:
* Added the LowDiscrepancyExperiment class to allow for the
generation of a sample from any distribution with independent
copula using low discrepancy sequences.
* Added pretty printing to C++ library.
* Added the ImportanceSamplingExperiment class, that allows one to generate a sample according to a distribution and weights such that the weighted sample is representative of another distribution.

Enhancement of existing classes:
* TruncatedDistribution.
* Changed the constructor of the FunctionalChaosResult class in order to store the orthogonal basis instead of just the measure defining the dot product.
* QuasiMonteCarlo now uses sample generation.
* More accurate range computation in Gamma class.
* NumericalMathEvaluationImplementation
* Added a default description to the ProductPolynomialEvaluationImplementation class.
* Added debug logs to the DistributionImplementation class.
* Made minor enhancements to the RandomMixture class.
* Improvement of poutre.cxx in order to support multithreading.
* Added a switching strategy to the RandomMixture class for bandwidth selection.
* Improved the computeScalarQuantile() method of the DistributionImplementation class.
* Improved the project() and computeProbability() methods of the RandomMixture class.
* Adopted a more conventionnal representation of the class that will change the results when using non-centered kernels compared to the previous implementation for the KernelMixture class.
* Improved const correctness of the MatrixImplementation class.
* Improved const correctness of the SquareMatrix class.
* Improved const correctness of the SymmetricMatrix class.
* Improved the numerical stability of the computePDF() method for the Gamma class. It avoids NaNs for Gamma distributions with large k parameter.
* Improved the RandomMixture class performance and robustness.
* DistributionImplementation.
* Added the specification of input and output dimensions for the MethodBoundNumericalMathEvaluationImplementation class.
* Improved const usage in the NumericalSampleImplementation class.
* Added ResourceMap cast methods to integral and base types.
* Added streaming to WrapperFile class
* Add optional framework tag to XML DTD (for use with Salome).
* Started implementation of output filtering for libxml2.
* Changed some debug messages.
* Minor enhancement of the ComposedNumericalMathFunction class to improve the save/load mechanism.
* Enhanced the Curve class to allow the drawing of 1D sample or the drawing of a pair of 1D samples.
* Changed the default precision for the PDF and CDF computations in the RandomMixture class.
* Enhanced the Indices class: is now persistent.
* Enhanced the WeightedExperiment class in order to add a non-uniform scalar weight to each realization of the generated sample.
* Enhanced the LeastSquaresStrategy class to use the non-uniformly weighted experiments.
* Enhanced the ProjectionStrategy class to prepare the development of the IntegrationStrategy class.
* Enhanced the ProjectionStrategyImplementation class to prepare the development of the IntegrationStrategy class.
* Enhanced the AdaptiveStrategy class to prepare the development of the IntegrationStrategy class.
* Enhanced the CleaningStrategy class to take into account the changes in the AdaptiveStrategy class.
* Enhanced the SequentialStrategy class to take into account the changes in the AdaptiveStrategy class.
* Enhanced the FixedStrategy class to take into account the changes in the AdaptiveStrategy class.
* Enhanced the FunctionalChaosAlgorithm class to take into account the changes in the AdaptiveStrategy class.

Methods:
* Added the computeRange() method to the NonCentralStudent class.
* Added an accessor to the enumerate function in the OrthogonalBasis, OrthogonalFunctionFactory and
OrthogonalProductPolynomialFactory classes.
* Added the computeCharacteristicFunction() method to the Gumbel class.
* Added the computeCharacteristicFunction() method to the LogNormal class.
* Added the computePDF(), computeCDF(), computeQuantile() methods based on a regular grid for the 1D case of the DistributionImplementation class.
* Added a setParametersCollection() method to the DistributionImplementation class.
* Added the computePDF(), computeCDF() and computeQuantile() methods based on a regular grid to the RandomMixture class.
* Added accessors to the reference bandwidth to the RandomMixture class.
* Added the getStandardDeviation(), getSkewness() and getKurtosis() methods to the KernelMixture class
* Added a flag to the computeCharacteristicFunction() method to perform the computation on a logarithmic scale to the ChiSquare, Exponential, Gamma, Geometric, KernelMixture, Laplace, Logistic, LogNormal, Mixture, Normal, RandomMixture, Rayleigh, Triangular, TruncatedNormal and Uniform classes.
* Changed the quantile computation of the Beta, ChiSquare, Epanechnikov, Exponential, Gamma, Geometric, Gumbel, Histogram, Laplace, Logistic, LogNormal, Poisson, RandomMixture, Rayleigh, Triangular, TruncatedDistribution, TruncatedNormal, Uniform and Weibull classes.
* Added a setParametersCollection method to the Beta, ChiSquare, ClaytonCopula, Exponential, FrankCopula, Gamma, Geometric, GumbelCopula, Gumbel, Laplace, Logistic, LogNormal, NonCentralStudent, Poisson, Rayleigh, Triangular, TruncatedNormal, Uniform and Weibull classes.
* Added a buildImplementation() method based on parameters to the BetaFactory, ChiSquareFactory, ClaytonCopulaFactory, ExponentialFactory, FrankCopulaFactory, GammaFactory, GeometricFactory, GumbelCopulaFactory, GumbelFactory, LaplaceFactory, LogisticFactory, LogNormalFactory, PoissonFactory, RayleighFactory, TriangularFactory, TruncatedNormalFactory, UniformFactory and WeibullFactory classes.
* Added a new buildImplementation() to the DistributionFactory and DistributionImplementationFactory classes. It allows one to build the default representative instance of any distribution. All the distribution factories have been updated.
* Added a default constructor to the MultiNomial and Histogram classes.
* Added a setParametersCollection() method to the EllipticalDistribution class.
* Added a method to compute centered moments of any order on a component basis in the NumericalSample and NumericalSampleImplementation classes.
* Added the computation of arbitrary Sobol indices and total indices in the FunctionalChaosRandomVector class.

==== Miscellaneous ====
General:
* Added patch in order to support MS Windows platform (mingw).
* Defined the name of OpenTURNS home environment variable in OTconfig.h.
* Changed messages printed to log in wrapper substitution functions.
* Added an include file to allow the compilation of the Log class for windows.
* Cleaned TODO file.
* Checked multi-repos behavior.
* Checked repository is working
* Started refactoring of header files.
* Prepared the loading of const data from a configuration file.
* Removed the initialization during declaration of all the static const attributes.
* Started implementation of output filtering for libxml2.
* Changed some debug messages.

Moved classes:
* Removed SVMRegression from lib and python. Removed tests files too.

Renamed methods:
* Renamed the generateSample() method of the
LowDiscrepancySequence, LowDiscrepancySequenceImplementation and
SobolSequence classes in order to be more coherent with the
RandomGenerator class.
* Fixed a typo in the name of the sorting method of the NumericalSample class: sortAccordingAComponent() became sortAccordingToAComponent().

==== Bug fixes ====
Fixes:
* Fixed a bug in the computeRange() method of several distributions.
* Fixed a bug in the SequentialStrategy, it was not storing the index of the first vector.
* Fixed a bug in the PythonNumericalMathEvaluationImplementation class. This closes ticket 204.
* Fixed a bug in the ComputedNumericalMathEvaluationImplementation class. This closes ticket 205.
* Fixed bug 505650 from Debian.
* Fixed an overflow bug in the computeRange() method of the ChiSquared and Gamma distributions.
* Fixed a bug in the computeCharacteristicFunction() method of the KernelMixture class.
* Fixed an aliasing issue for bounded distributions in the RandomMixture class.
* Fixed bug in t_Cache_std.cxx : double definition for TEMPLATE_CLASSNAMEINIT.
* Fixed bug in openturns_preload.c: look for the library libOT.so.0 in the standard paths, ${OPENTURNS_HOME}/lib/openturns and install path. Closes 211.
* Fixed bug in Path.cxx: Use env var OPENTURNS_HOME to find OpenTURNS standard paths. Closes 212.
* Correct compilation error that are not detected by linux distcheck.
* Fixed bug in ot_check_openturns.m4 macro. Closes 207.
* Fixed bug in WrapperMacros.h file. Closes 209.
* Fixed bug in wrapper substitution function when a regexp matched two similar lines in file. Closes 199.
* Fixed a bug in the drawPDF() method of the Distribution class, due to a change in the Box class. It closed ticket 208.
* Fixed a typo in the LogNormal class.
* Fixed a bug in the computeCovariance() method of the KernelMixture class.
* Fixed a typo in WrapperFile class.
* Fixed a bug in the computeCharacteristicFunction() method of the Gamma class.
* Fixed a bug in the computeSkewness() and computeKurtosis() methods of the KernelMixture class.
* Fixed a bug in the computeRange() method of the Laplace class.
* Fixed bug concerning DTD validation for wrapper description files.
* Fixed bug concerning wrapper templates that didn't link to OpenTURNS correctly.
* Fixed bug on wrapper description structure.
* Fixed minor cast warnings.

=== Python module ===
==== Enhancements ====
* Welcome message is now printed to stderr.
* Added new python modules common and wrapper (from base).

==== Bug fixes ====
* Fixed bug concerning openturns_viewer module, now called as
openturns.viewer.
* Fixed bug in base_all.i interface file.
* Added the missing SWIG files in base.i and uncertainty.i that prevented the FunctionalChaosAlgorithm and SVMRegression classes to be useable from the TUI.

==== Miscellaneous ====

=== External Modules ===
==== Enhancements ====
* Added curl support for URLs.

==== Bug fixes ====
* Fixed many bugs preventing from using the library and the python module from an external component.

=== Documentation ===
==== UseCase Guide ====
* Added a description on how to manage the welcome message of the TUI in the UseCase guide.
* Updated the UseCaseGuide in order to reflect the new functionalities.

==== Constribution Guide ====
* How to use version control system
* How to develop an external module
* Typos fixed

==== User Manual ====
* Updated the UserManual in order to reflect the new functionalities.
* Fixed various typos.

==== Examples Guide ====
* Updated the ExamplesGuide in order to reflect the new functionalities.

==== Bug fixes ====
* Fixed bug concerning doc directory (autotools crashed).

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