RangedDistributionLorentz Class Reference

Lorentz distribution with median and hwhm. More...

Inheritance diagram for RangedDistributionLorentz:

Collaboration diagram for RangedDistributionLorentz:

Public Member Functions
	RangedDistributionLorentz ()
	RangedDistributionLorentz (size_t n_samples, double hwhm_factor, const RealLimits &limits=RealLimits::limitless())
	RangedDistributionLorentz (size_t n_samples, double hwhm_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). More...
	~RangedDistributionLorentz () override=default
RangedDistributionLorentz *	clone () const override
std::unique_ptr< 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
std::unique_ptr< IDistribution1D >	distribution_impl (double median, double hwhm) 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

Detailed Description

Lorentz distribution with median and hwhm.

Definition at line 124 of file RangedDistributions.h.

Constructor & Destructor Documentation

RangedDistributionLorentz() [1/3]

RangedDistributionLorentz::RangedDistributionLorentz

(

)

Definition at line 153 of file RangedDistributions.cpp.

: IRangedDistribution() {}

RangedDistributionLorentz() [2/3]

RangedDistributionLorentz::RangedDistributionLorentz	(	size_t	n_samples,
		double	hwhm_factor,
		const RealLimits &	limits = RealLimits::limitless()
	)

Definition at line 155 of file RangedDistributions.cpp.

    : IRangedDistribution(n_samples, hwhm_factor, limits)
{
}

RangedDistributionLorentz() [3/3]

RangedDistributionLorentz::RangedDistributionLorentz	(	size_t	n_samples,
		double	hwhm_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, hwhm_factor = 2.0, while the limits are (-inf, +inf).

Definition at line 161 of file RangedDistributions.cpp.

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

~RangedDistributionLorentz()

RangedDistributionLorentz::~RangedDistributionLorentz ( )

overridedefault

Member Function Documentation

checkInitialization()

void IRangedDistribution::checkInitialization ( )

privateinherited

Definition at line 95 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()

RangedDistributionLorentz * RangedDistributionLorentz::clone ( ) const

overridevirtual

Implements IRangedDistribution.

Definition at line 167 of file RangedDistributions.cpp.

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

distribution()

std::unique_ptr< IDistribution1D > IRangedDistribution::distribution ( double  mean, double  stddev  ) const

inherited

Public interface function to underlying IDistribution1D object.

Definition at line 87 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()

std::unique_ptr< IDistribution1D > RangedDistributionLorentz::distribution_impl ( double  median, double  hwhm  ) const

overrideprotectedvirtual

Returns underlying IDistribution1D object.

Implements IRangedDistribution.

Definition at line 177 of file RangedDistributions.cpp.

{
    return std::make_unique<DistributionLorentz>(median, hwhm);
}

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 71 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 57 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 64 of file RangedDistributions.h.

{ return m_limits; }

References IRangedDistribution::m_limits.

Referenced by pyfmt2::printRangedDistribution(), and IRangedDistribution::setLimits().

name()

std::string RangedDistributionLorentz::name ( ) const

overridevirtual

Returns distribution name for python-formatted text.

Implements IRangedDistribution.

Definition at line 172 of file RangedDistributions.cpp.

{
    return "RangedDistributionLorentz";
}

nSamples()

size_t IRangedDistribution::nSamples ( ) const

inlineinherited

Returns number of samples to generate.

Definition at line 68 of file RangedDistributions.h.

{ return m_n_samples; }

References IRangedDistribution::m_n_samples.

Referenced by pyfmt2::printRangedDistribution().

setLimits()

void IRangedDistribution::setLimits ( const RealLimits &  limits )

inlineinherited

Definition at line 72 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 66 of file RangedDistributions.h.

{ return m_sigma_factor; }

References IRangedDistribution::m_sigma_factor.

Referenced by pyfmt2::printRangedDistribution().

transferToCPP()

virtual void ICloneable::transferToCPP ( )

inlinevirtualinherited

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

Definition at line 34 of file ICloneable.h.

Member Data Documentation

m_limits

RealLimits IRangedDistribution::m_limits

privateinherited

Definition at line 87 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 85 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 86 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/www/ba/Param/Distrib/RangedDistributions.h
• /home/www/ba/Param/Distrib/RangedDistributions.cpp