/usr/include/openturns/Normal.hxx is in libopenturns-dev 1.7-3.
This file is owned by root:root, with mode 0o644.
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/**
* @brief The Normal distribution
*
* Copyright 2005-2015 Airbus-EDF-IMACS-Phimeca
*
* This library is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* along with this library. If not, see <http://www.gnu.org/licenses/>.
*
*/
#ifndef OPENTURNS_NORMAL_HXX
#define OPENTURNS_NORMAL_HXX
#include "OTprivate.hxx"
#include "EllipticalDistribution.hxx"
BEGIN_NAMESPACE_OPENTURNS
/**
* @class Normal
*
* The Normal (gaussian) distribution.
*/
class OT_API Normal
: public EllipticalDistribution
{
CLASSNAME;
public:
/** Default constructor */
explicit Normal(const UnsignedInteger dimension = 1);
/** Dimension 1 constructor */
Normal(const NumericalScalar mu, const NumericalScalar sd);
/** Constructor for multiD normal distribution */
Normal(const NumericalPoint & mean,
const NumericalPoint & sigma,
const CorrelationMatrix & R);
Normal(const NumericalPoint & mean,
const CovarianceMatrix & C);
/** String converter */
String __repr__() const;
String __str__(const String & offset = "") const;
/* Interface inherited from Distribution */
/** Virtual constructor */
virtual Normal * clone() const;
/** Compute the density generator of the ellipticalal generator, i.e.
* the function phi such that the density of the distribution can
* be written as p(x) = phi(t(x-mu)R^(-1)(x-mu)) */
NumericalScalar computeDensityGenerator(const NumericalScalar betaSquare) const;
/** Compute the derivative of the density generator */
NumericalScalar computeDensityGeneratorDerivative(const NumericalScalar betaSquare) const;
/** Compute the seconde derivative of the density generator */
NumericalScalar computeDensityGeneratorSecondDerivative(const NumericalScalar betaSquare) const;
/** Get one realization of the Normal distribution */
NumericalPoint getRealization() const;
NumericalSample getSample(const UnsignedInteger size) const;
/** Get the CDF of the Normal distribution */
using EllipticalDistribution::computeCDF;
NumericalScalar computeCDF(const NumericalPoint & point) const;
/** Get the characteristic function of the distribution, i.e. phi(u) = E(exp(I*u*X)) */
NumericalComplex computeCharacteristicFunction(const NumericalScalar x) const;
NumericalComplex computeCharacteristicFunction(const NumericalPoint & x) const;
NumericalComplex computeLogCharacteristicFunction(const NumericalScalar x) const;
NumericalComplex computeLogCharacteristicFunction(const NumericalPoint & x) const;
/** Get the probability content of an interval */
NumericalScalar computeProbability(const Interval & interval) const;
/** Get the CDF gradient of the distribution */
using EllipticalDistribution::computeCDFGradient;
NumericalPoint computeCDFGradient(const NumericalPoint & point) const;
/** Compute the radial distribution CDF */
NumericalScalar computeRadialDistributionCDF(const NumericalScalar radius,
const Bool tail = false) const;
/** Compute the PDF of Xi | X1, ..., Xi-1. x = Xi, y = (X1,...,Xi-1) */
NumericalScalar computeConditionalPDF(const NumericalScalar x, const NumericalPoint & y) const;
/** Compute the CDF of Xi | X1, ..., Xi-1. x = Xi, y = (X1,...,Xi-1) */
NumericalScalar computeConditionalCDF(const NumericalScalar x, const NumericalPoint & y) const;
/** Compute the quantile of Xi | X1, ..., Xi-1, i.e. x such that CDF(x|y) = q with x = Xi, y = (X1,...,Xi-1) */
NumericalScalar computeConditionalQuantile(const NumericalScalar q, const NumericalPoint & y) const;
/** Get the i-th marginal distribution */
Implementation getMarginal(const UnsignedInteger i) const;
/** Get the distribution of the marginal distribution corresponding to indices dimensions */
Implementation getMarginal(const Indices & indices) const;
/** Get the roughness, i.e. the L2-norm of the PDF */
NumericalScalar getRoughness() const;
/** Get the skewness of the distribution */
NumericalPoint getSkewness() const;
/** Get the kurtosis of the distribution */
NumericalPoint getKurtosis() const;
/** Get the raw moments of the standardized distribution */
NumericalPoint getStandardMoment(const UnsignedInteger n) const;
/** Get the standard representative in the parametric family, associated with the standard moments */
Implementation getStandardRepresentative() const;
/** Correlation matrix accessor */
void setCorrelation(const CorrelationMatrix & R);
/** Get the copula of a distribution */
Implementation getCopula() const;
/* Interface specific to Implementation */
/** Tell if the distribution has independent copula */
Bool hasIndependentCopula() const;
/** Method save() stores the object through the StorageManager */
void save(Advocate & adv) const;
/** Method load() reloads the object from the StorageManager */
void load(Advocate & adv);
protected:
private:
/** Compute the numerical range of the distribution given the parameters values */
void computeRange();
/** Quantile computation for dimension=1 */
NumericalScalar computeScalarQuantile(const NumericalScalar prob,
const Bool tail = false) const;
/** Check if the distribution has independent copula */
void checkIndependentCopula();
/** The normalization factor of the Normal distribution */
NumericalScalar normalizationFactor_;
/** Store the independence status */
Bool hasIndependentCopula_;
}; /* class Normal */
END_NAMESPACE_OPENTURNS
#endif /* OPENTURNS_NORMAL_HXX */
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