RangedDistributionGaussian Class Reference

Inheritance diagram for RangedDistributionGaussian:

Collaboration diagram for RangedDistributionGaussian:

Public Member Functions
	RangedDistributionGaussian ()
	RangedDistributionGaussian (size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
	RangedDistributionGaussian (size_t n_samples, double sigma_factor, double min, double max)
RangedDistributionGaussian *	clone () const override
	~RangedDistributionGaussian () override=default
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
std::string	name () const override
std::unique_ptr< IDistribution1D >	distribution_impl (double mean, double stddev) const override

Private Member Functions
void	checkInitialization ()

Private Attributes
size_t	m_n_samples
double	m_sigma_factor
RealLimits	m_limits

Detailed Description

Gaussian distribution with standard deviation std_dev.

Definition at line 148 of file RangedDistributions.h.

Constructor & Destructor Documentation

RangedDistributionGaussian() [1/3]

RangedDistributionGaussian::RangedDistributionGaussian

(

)

Definition at line 180 of file RangedDistributions.cpp.

: RangedDistribution() {}

RangedDistributionGaussian() [2/3]

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

Definition at line 182 of file RangedDistributions.cpp.

    : RangedDistribution(n_samples, sigma_factor, limits)
{
}

RangedDistributionGaussian() [3/3]

RangedDistributionGaussian::RangedDistributionGaussian	(	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 188 of file RangedDistributions.cpp.

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

~RangedDistributionGaussian()

RangedDistributionGaussian::~RangedDistributionGaussian ( )

overridedefault

Member Function Documentation

clone()

RangedDistributionGaussian * RangedDistributionGaussian::clone ( ) const

overridevirtual

Implements RangedDistribution.

Definition at line 194 of file RangedDistributions.cpp.

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

References anonymous_namespace{RangedDistributions.cpp}::makeCopy().

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name()

std::string RangedDistributionGaussian::name ( ) const

overrideprotectedvirtual

Returns distribution name for python-formatted text.

Implements RangedDistribution.

Definition at line 199 of file RangedDistributions.cpp.

{
    return "ba.RangedDistributionGaussian";
}

distribution_impl()

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

overrideprotectedvirtual

Returns underlying IDistribution1D object.

Implements RangedDistribution.

Definition at line 204 of file RangedDistributions.cpp.

{
    return std::make_unique<DistributionGaussian>(mean, stddev);
}

generateSamples() [1/2]

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

inherited

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

Referenced by RangedDistribution::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

inherited

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 RangedDistribution::generateSamples().

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distribution()

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

inherited

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 RangedDistribution::distribution_impl().

Referenced by RangedDistribution::generateSamples().

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limits()

RealLimits RangedDistribution::limits ( ) const

inlineinherited

Returns current limits of the distribution.

Definition at line 63 of file RangedDistributions.h.

{ return m_limits; }

References RangedDistribution::m_limits.

Referenced by RangedDistribution::setLimits().

sigmaFactor()

double RangedDistribution::sigmaFactor ( ) const

inlineinherited

Returns sigma factor to use during sampling.

Definition at line 65 of file RangedDistributions.h.

{ return m_sigma_factor; }

References RangedDistribution::m_sigma_factor.

nSamples()

size_t RangedDistribution::nSamples ( ) const

inlineinherited

Returns number of samples to generate.

Definition at line 67 of file RangedDistributions.h.

{ return m_n_samples; }

References RangedDistribution::m_n_samples.

setLimits()

void RangedDistribution::setLimits ( const RealLimits &  limits )

inlineinherited

Definition at line 71 of file RangedDistributions.h.

{ m_limits = limits; }

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

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pyString()

std::string RangedDistribution::pyString ( ) const

inherited

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(), RangedDistribution::m_limits, RangedDistribution::m_n_samples, RangedDistribution::m_sigma_factor, RangedDistribution::name(), pyfmt::printDouble(), and pyfmt::printRealLimitsArg().

Referenced by operator<<().

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checkInitialization()

void RangedDistribution::checkInitialization ( )

privateinherited

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(), RangedDistribution::m_limits, RangedDistribution::m_n_samples, RangedDistribution::m_sigma_factor, and RealLimits::upperLimit().

Referenced by RangedDistribution::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

privateinherited

Definition at line 86 of file RangedDistributions.h.

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

m_sigma_factor

double RangedDistribution::m_sigma_factor

privateinherited

Definition at line 87 of file RangedDistributions.h.

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

m_limits

RealLimits RangedDistribution::m_limits

privateinherited

Definition at line 88 of file RangedDistributions.h.

Referenced by RangedDistribution::checkInitialization(), RangedDistribution::generateSamples(), RangedDistribution::limits(), RangedDistribution::pyString(), and RangedDistribution::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