RangedDistribution Class Reference

Inheritance diagram for RangedDistribution:

Collaboration diagram for RangedDistribution:

Public Member Functions
	RangedDistribution ()
	RangedDistribution (size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
	RangedDistribution (size_t n_samples, double sigma_factor, double min, double max)
RangedDistribution *	clone () const override=0
	~RangedDistribution () override
std::vector< ParameterSample >	generateSamples (double mean, double stddev) const
std::vector< std::vector< ParameterSample > >	generateSamples (const std::vector< double > &mean, const std::vector< double > &stddev) const
std::unique_ptr< IDistribution1D >	distribution (double mean, double stddev) const
RealLimits	limits () const
double	sigmaFactor () const
size_t	nSamples () const
void	setLimits (const RealLimits &limits)
std::string	pyString () const
virtual void	transferToCPP ()

Protected Member Functions
virtual std::string	name () const =0
virtual std::unique_ptr< IDistribution1D >	distribution_impl (double mean, double stddev) const =0

Private Member Functions
void	checkInitialization ()

Private Attributes
size_t	m_n_samples
double	m_sigma_factor
RealLimits	m_limits

Detailed Description

Interface for one-dimensional ranged distributions.

All derived distributions allow for generating samples in-place for known mean and standard deviation (except for RangedDistributionLorentz which uses median and hwhm).

Definition at line 36 of file RangedDistributions.h.

Constructor & Destructor Documentation

RangedDistribution() [1/3]

RangedDistribution::RangedDistribution

(

)

Definition at line 29 of file RangedDistributions.cpp.

    : m_n_samples(5), m_sigma_factor(2.0), m_limits(RealLimits::limitless())
{
    checkInitialization();
}

References checkInitialization().

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RangedDistribution() [2/3]

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

Definition at line 35 of file RangedDistributions.cpp.

    : m_n_samples(n_samples), m_sigma_factor(sigma_factor), m_limits(limits)
{
    checkInitialization();
}

References checkInitialization().

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RangedDistribution() [3/3]

RangedDistribution::RangedDistribution	(	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 42 of file RangedDistributions.cpp.

    : m_n_samples(n_samples), m_sigma_factor(sigma_factor), m_limits(RealLimits::limited(min, max))
{
    checkInitialization();
}

References checkInitialization().

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~RangedDistribution()

RangedDistribution::~RangedDistribution ( )

overridedefault

Member Function Documentation

clone()

RangedDistribution* RangedDistribution::clone ( ) const

overridepure virtual

Implements ICloneable.

Implemented in RangedDistributionCosine, RangedDistributionLogNormal, RangedDistributionGaussian, RangedDistributionLorentz, and RangedDistributionGate.

generateSamples() [1/2]

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

Definition at line 51 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 distribution(), m_limits, m_n_samples, m_sigma_factor, and ParameterSample::weight.

Referenced by generateSamples().

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generateSamples() [2/2]

std::vector< std::vector< ParameterSample > > RangedDistribution::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.

Definition at line 65 of file RangedDistributions.cpp.

{
    if (mean.size() != stddev.size())
        throw std::runtime_error("Error in RangedDistribution::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 generateSamples().

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distribution()

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

Public interface function to underlying IDistribution1D object.

Definition at line 81 of file RangedDistributions.cpp.

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

References distribution_impl().

Referenced by generateSamples().

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limits()

RealLimits RangedDistribution::limits ( ) const

inline

Returns current limits of the distribution.

Definition at line 63 of file RangedDistributions.h.

{ return m_limits; }

References m_limits.

Referenced by setLimits().

sigmaFactor()

double RangedDistribution::sigmaFactor ( ) const

inline

Returns sigma factor to use during sampling.

Definition at line 65 of file RangedDistributions.h.

{ return m_sigma_factor; }

References m_sigma_factor.

nSamples()

size_t RangedDistribution::nSamples ( ) const

inline

Returns number of samples to generate.

Definition at line 67 of file RangedDistributions.h.

{ return m_n_samples; }

References m_n_samples.

setLimits()

void RangedDistribution::setLimits ( const RealLimits &  limits )

inline

Definition at line 71 of file RangedDistributions.h.

{ m_limits = limits; }

References limits(), and m_limits.

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pyString()

std::string RangedDistribution::pyString

(

)

const

Prints python-formatted definition of the distribution.

Definition at line 89 of file RangedDistributions.cpp.

{
    std::stringstream result;
    result << pyfmt::indent() << "distribution = " << name();
    result << "(" << m_n_samples << ", " << pyfmt::printDouble(m_sigma_factor);
    if (!m_limits.isLimitless())
        result << pyfmt::printRealLimitsArg(m_limits);
    result << ")";
    return result.str();
}

References pyfmt::indent(), RealLimits::isLimitless(), m_limits, m_n_samples, m_sigma_factor, name(), pyfmt::printDouble(), and pyfmt::printRealLimitsArg().

Referenced by operator<<().

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name()

virtual std::string RangedDistribution::name ( ) const

protectedpure virtual

Returns distribution name for python-formatted text.

Implemented in RangedDistributionCosine, RangedDistributionLogNormal, RangedDistributionGaussian, RangedDistributionLorentz, and RangedDistributionGate.

Referenced by pyString().

distribution_impl()

virtual std::unique_ptr<IDistribution1D> RangedDistribution::distribution_impl ( double  mean, double  stddev  ) const

protectedpure virtual

Returns underlying IDistribution1D object.

Implemented in RangedDistributionLorentz, RangedDistributionCosine, RangedDistributionLogNormal, RangedDistributionGaussian, and RangedDistributionGate.

Referenced by distribution().

checkInitialization()

void RangedDistribution::checkInitialization ( )

private

Definition at line 100 of file RangedDistributions.cpp.

{
    if (m_n_samples < 1u)
        throw std::runtime_error("Error in RangedDistribution::checkInitialization: number of "
                                 "samples shall be positive");
 
    if (m_sigma_factor < 0.0)
        throw std::runtime_error("Error in RangedDistribution::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 RangedDistribution::checkInitialization: lower limit "
                                 "shall not exceed the upper one.");
}

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

Referenced by RangedDistribution().

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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_n_samples

size_t RangedDistribution::m_n_samples

private

Definition at line 86 of file RangedDistributions.h.

Referenced by checkInitialization(), generateSamples(), nSamples(), and pyString().

m_sigma_factor

double RangedDistribution::m_sigma_factor

private

Definition at line 87 of file RangedDistributions.h.

Referenced by checkInitialization(), generateSamples(), pyString(), and sigmaFactor().

m_limits

RealLimits RangedDistribution::m_limits

private

Definition at line 88 of file RangedDistributions.h.

Referenced by checkInitialization(), generateSamples(), limits(), pyString(), and setLimits().

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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