RangedDistributionLogNormal Class Reference

Description

Log-normal distribution.

Definition at line 172 of file RangedDistributions.h.

Inheritance diagram for RangedDistributionLogNormal:

Collaboration diagram for RangedDistributionLogNormal:

Public Member Functions
	RangedDistributionLogNormal ()
	RangedDistributionLogNormal (size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
	RangedDistributionLogNormal (size_t n_samples, double sigma_factor, double min, double max)
	Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf). More...
	~RangedDistributionLogNormal () override=default
RangedDistributionLogNormal *	clone () const override
IDistribution1D *	distribution (double mean, double stddev) const
	Public interface function to underlying IDistribution1D object. More...
std::vector< std::vector< ParameterSample > >	generateSamples (const std::vector< double > &mean, const std::vector< double > &stddev) const
	Generates list of sampled values with their weights from given means and standard deviations. More...
std::vector< ParameterSample >	generateSamples (double mean, double stddev) const
RealLimits	limits () const
	Returns current limits of the distribution. More...
std::string	name () const override
	Returns distribution name for python-formatted text. More...
size_t	nSamples () const
	Returns number of samples to generate. More...
void	setLimits (const RealLimits &limits)
double	sigmaFactor () const
	Returns sigma factor to use during sampling. More...
virtual void	transferToCPP ()
	Used for Python overriding of clone (see swig/tweaks.py) More...

Protected Member Functions
IDistribution1D *	distribution_impl (double mean, double stddev) const override
	Returns underlying IDistribution1D object. More...

Private Member Functions
void	checkInitialization ()

Private Attributes
RealLimits	m_limits
size_t	m_n_samples
double	m_sigma_factor

Constructor & Destructor Documentation

RangedDistributionLogNormal() [1/3]

RangedDistributionLogNormal::RangedDistributionLogNormal

(

)

Definition at line 235 of file RangedDistributions.cpp.

    : IRangedDistribution()
{
}

RangedDistributionLogNormal() [2/3]

RangedDistributionLogNormal::RangedDistributionLogNormal	(	size_t	n_samples,
		double	sigma_factor,
		const RealLimits &	limits = RealLimits::limitless()
	)

Definition at line 240 of file RangedDistributions.cpp.

    : IRangedDistribution(n_samples, sigma_factor, limits)
{
}

RangedDistributionLogNormal() [3/3]

RangedDistributionLogNormal::RangedDistributionLogNormal	(	size_t	n_samples,
		double	sigma_factor,
		double	min,
		double	max
	)

Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).

Definition at line 246 of file RangedDistributions.cpp.

    : IRangedDistribution(n_samples, sigma_factor, min, max)
{
}

~RangedDistributionLogNormal()

RangedDistributionLogNormal::~RangedDistributionLogNormal ( )

overridedefault

Member Function Documentation

checkInitialization()

void IRangedDistribution::checkInitialization ( )

privateinherited

Definition at line 103 of file RangedDistributions.cpp.

{
    if (m_n_samples < 1u)
        throw std::runtime_error("Error in IRangedDistribution::checkInitialization: number of "
                                 "samples shall be positive");
 
    if (m_sigma_factor < 0.0)
        throw std::runtime_error("Error in IRangedDistribution::checkInitialization: sigma factor "
                                 "shall be non-negative.");
 
    if (!m_limits.hasLowerAndUpperLimits())
        return;
 
    if (m_limits.lowerLimit() >= m_limits.upperLimit())
        throw std::runtime_error("Error in IRangedDistribution::checkInitialization: lower limit "
                                 "shall not exceed the upper one.");
}

References RealLimits::hasLowerAndUpperLimits(), RealLimits::lowerLimit(), IRangedDistribution::m_limits, IRangedDistribution::m_n_samples, IRangedDistribution::m_sigma_factor, and RealLimits::upperLimit().

Referenced by IRangedDistribution::IRangedDistribution().

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clone()

RangedDistributionLogNormal * RangedDistributionLogNormal::clone ( ) const

overridevirtual

Implements IRangedDistribution.

Definition at line 252 of file RangedDistributions.cpp.

{
    return makeCopy(*this).release();
}

distribution()

IDistribution1D * IRangedDistribution::distribution ( double  mean, double  stddev  ) const

inherited

Public interface function to underlying IDistribution1D object.

Definition at line 95 of file RangedDistributions.cpp.

{
    if (stddev < 0.0)
        throw std::runtime_error(
            "Error in IRangedDistribution::distribution: standard deviation is less than zero");
    return distribution_impl(mean, stddev);
}

References IRangedDistribution::distribution_impl().

Referenced by IRangedDistribution::generateSamples().

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distribution_impl()

IDistribution1D * RangedDistributionLogNormal::distribution_impl ( double  mean, double  stddev  ) const

overrideprotectedvirtual

Returns underlying IDistribution1D object.

Implements IRangedDistribution.

Definition at line 262 of file RangedDistributions.cpp.

{
    const double mean_2 = mean * mean;
    if (mean_2 <= std::numeric_limits<double>::min())
        throw std::runtime_error("Error in DistributionLogNormal::distribution: mean square value "
                                 "is less or indistinguishable from zero.");
 
    const double scale = std::sqrt(std::log(stddev * stddev / mean_2 + 1.0));
    const double median = mean * std::exp(-scale * scale / 2.0);
    return new DistributionLogNormal(median, scale);
}

generateSamples() [1/2]

std::vector< std::vector< ParameterSample > > IRangedDistribution::generateSamples ( const std::vector< double > &  mean, const std::vector< double > &  stddev  ) const

inherited

Generates list of sampled values with their weights from given means and standard deviations.

Definition at line 79 of file RangedDistributions.cpp.

{
    if (mean.size() != stddev.size())
        throw std::runtime_error("Error in IRangedDistribution::generateSamples: mean and variance "
                                 "vectors shall be of the same size");
 
    const size_t size = mean.size();
 
    std::vector<std::vector<ParameterSample>> result;
    result.resize(size);
    for (size_t i = 0; i < size; ++i)
        result[i] = generateSamples(mean[i], stddev[i]);
    return result;
}

References IRangedDistribution::generateSamples().

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generateSamples() [2/2]

std::vector< ParameterSample > IRangedDistribution::generateSamples ( double  mean, double  stddev  ) const

inherited

Definition at line 65 of file RangedDistributions.cpp.

{
    auto generator = distribution(mean, stddev);
    if (!generator->isDelta())
        return generator->equidistantSamples(m_n_samples, m_sigma_factor, m_limits);
 
    // handling the case of delta distributions
    auto samples = generator->equidistantSamples(m_n_samples, m_sigma_factor, m_limits);
    ParameterSample& sample = samples[0]; // there is only one element in the vector
    sample.weight = 1.0 / m_n_samples;
    return std::vector<ParameterSample>(m_n_samples, sample);
}

References IRangedDistribution::distribution(), IRangedDistribution::m_limits, IRangedDistribution::m_n_samples, IRangedDistribution::m_sigma_factor, and ParameterSample::weight.

Referenced by IRangedDistribution::generateSamples().

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limits()

RealLimits IRangedDistribution::limits ( ) const

inlineinherited

Returns current limits of the distribution.

Definition at line 63 of file RangedDistributions.h.

{ return m_limits; }

References IRangedDistribution::m_limits.

Referenced by Py::Fmt2::printRangedDistribution(), and IRangedDistribution::setLimits().

name()

std::string RangedDistributionLogNormal::name ( ) const

overridevirtual

Returns distribution name for python-formatted text.

Implements IRangedDistribution.

Definition at line 257 of file RangedDistributions.cpp.

{
    return "RangedDistributionLogNormal";
}

nSamples()

size_t IRangedDistribution::nSamples ( ) const

inlineinherited

Returns number of samples to generate.

Definition at line 67 of file RangedDistributions.h.

{ return m_n_samples; }

References IRangedDistribution::m_n_samples.

Referenced by Py::Fmt2::printRangedDistribution().

setLimits()

void IRangedDistribution::setLimits ( const RealLimits &  limits )

inlineinherited

Definition at line 71 of file RangedDistributions.h.

{ m_limits = limits; }

References IRangedDistribution::limits(), and IRangedDistribution::m_limits.

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sigmaFactor()

double IRangedDistribution::sigmaFactor ( ) const

inlineinherited

Returns sigma factor to use during sampling.

Definition at line 65 of file RangedDistributions.h.

{ return m_sigma_factor; }

References IRangedDistribution::m_sigma_factor.

Referenced by Py::Fmt2::printRangedDistribution().

transferToCPP()

virtual void ICloneable::transferToCPP ( )

inlinevirtualinherited

Used for Python overriding of clone (see swig/tweaks.py)

Definition at line 32 of file ICloneable.h.

Member Data Documentation

m_limits

RealLimits IRangedDistribution::m_limits

privateinherited

Definition at line 85 of file RangedDistributions.h.

Referenced by IRangedDistribution::checkInitialization(), IRangedDistribution::generateSamples(), IRangedDistribution::limits(), and IRangedDistribution::setLimits().

m_n_samples

size_t IRangedDistribution::m_n_samples

privateinherited

Definition at line 83 of file RangedDistributions.h.

Referenced by IRangedDistribution::checkInitialization(), IRangedDistribution::generateSamples(), and IRangedDistribution::nSamples().

m_sigma_factor

double IRangedDistribution::m_sigma_factor

privateinherited

Definition at line 84 of file RangedDistributions.h.

Referenced by IRangedDistribution::checkInitialization(), IRangedDistribution::generateSamples(), and IRangedDistribution::sigmaFactor().

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The documentation for this class was generated from the following files:

• /home/build/builds/o5h8MZZm/0/mlz/bornagain/Param/Distrib/RangedDistributions.h
• /home/build/builds/o5h8MZZm/0/mlz/bornagain/Param/Distrib/RangedDistributions.cpp