Description

Implementation of relative difference metric. With default L2 norm and weighting off corresponds to the formula.

$Result = \sum \frac{(I - D)^2}{(I + D)^2}$

where is the simulated intensity, - experimental data. If weighting is on, falls back to the standard $\chi^2$ metric.

Definition at line 168 of file ObjectiveMetric.h.

Inheritance diagram for meanRelativeDifferenceMetric:

Collaboration diagram for meanRelativeDifferenceMetric:

Public Member Functions
	meanRelativeDifferenceMetric ()

meanRelativeDifferenceMetric *	clone () const override

virtual double	compute (const SimDataPair &data_pair, bool use_weights) const
	Computes metric value from SimDataPair object. Calls computeFromArrays internally. More...

double	computeFromArrays (std::vector< double > sim_data, std::vector< double > exp_data, std::vector< double > exp_stdv, std::vector< double > weight_factors) const override
	Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors and uncertainties. All arrays involved in the computation must be of the same size. More...

double	computeFromArrays (std::vector< double > sim_data, std::vector< double > exp_data, std::vector< double > exp_stdv, std::vector< double > weight_factors) const override
	Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors and uncertainties. All arrays involved in the computation must be of the same size. More...

double	computeFromArrays (std::vector< double > sim_data, std::vector< double > exp_data, std::vector< double > weight_factors) const override
	Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors. All arrays involved in the computation must be of the same size. More...

double	computeFromArrays (std::vector< double > sim_data, std::vector< double > exp_data, std::vector< double > weight_factors) const override
	Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors. All arrays involved in the computation must be of the same size. More...

auto	norm () const
	Returns a copy of the normalization function used. More...

void	setNorm (std::function< double(double)> norm)

virtual void	transferToCPP ()
	Used for Python overriding of clone (see swig/tweaks.py) More...

Private Attributes
std::function< double(double)>	m_norm

Constructor & Destructor Documentation

◆ meanRelativeDifferenceMetric()

meanRelativeDifferenceMetric::meanRelativeDifferenceMetric ( )

Definition at line 209 of file ObjectiveMetric.cpp.

     : Chi2Metric()
 {
 }

Member Function Documentation

◆ clone()

meanRelativeDifferenceMetric * meanRelativeDifferenceMetric::clone ( ) const

overridevirtual

Reimplemented from Chi2Metric.

Definition at line 214 of file ObjectiveMetric.cpp.

 {
     return copyMetric(*this);
 }

◆ compute()

double ObjectiveMetric::compute	(	const SimDataPair &	data_pair,
		bool	use_weights
	)		const

virtualinherited

Computes metric value from SimDataPair object. Calls computeFromArrays internally.

Parameters

data_pair	SimDataPair object. Can optionally contain data uncertainties
use_weights	boolean, defines if data uncertainties should be taken into account

Reimplemented in RQ4Metric.

Definition at line 66 of file ObjectiveMetric.cpp.

 {
     if (use_weights && !data_pair.containsUncertainties())
         throw std::runtime_error("Error in ObjectiveMetric::compute: the metric is weighted, but "
                                  "the simulation-data pair does not contain uncertainties");
  
     if (use_weights)
         return computeFromArrays(data_pair.simulation_array(), data_pair.experimental_array(),
                                  data_pair.uncertainties_array(), data_pair.user_weights_array());
     return computeFromArrays(data_pair.simulation_array(), data_pair.experimental_array(),
                              data_pair.user_weights_array());
 }

References ObjectiveMetric::computeFromArrays(), SimDataPair::containsUncertainties(), SimDataPair::experimental_array(), SimDataPair::simulation_array(), SimDataPair::uncertainties_array(), and SimDataPair::user_weights_array().

Referenced by RQ4Metric::compute().

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◆ computeFromArrays() [1/4]

double Chi2Metric::computeFromArrays	(	std::vector< double >	sim_data,
		std::vector< double >	exp_data,
		std::vector< double >	exp_stdv,
		std::vector< double >	weight_factors
	)		const

overridevirtualinherited

Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors and uncertainties. All arrays involved in the computation must be of the same size.

Parameters

sim_data	array with simulated intensities.
exp_data	array with intensity values obtained from an experiment.
exp_stdv	array with experimental data uncertainties.
weight_factors	user-defined weighting factors. Used linearly, no matter which norm is chosen.

Implements ObjectiveMetric.

Definition at line 96 of file ObjectiveMetric.cpp.

 {
     checkIntegrity(sim_data, exp_data, exp_stdv, weight_factors);
  
     double result = 0.0;
     auto norm_fun = norm();
     for (size_t i = 0, sim_size = sim_data.size(); i < sim_size; ++i)
         if (exp_data[i] >= 0.0 && weight_factors[i] > 0.0 && exp_stdv[i] > 0.0)
             result += norm_fun((exp_data[i] - sim_data[i]) / exp_stdv[i]) * weight_factors[i];
  
     return std::isfinite(result) ? result : double_max;
 }

Referenced by RQ4Metric::compute().

◆ computeFromArrays() [2/4]

double Chi2Metric::computeFromArrays

override

Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors and uncertainties. All arrays involved in the computation must be of the same size.

Parameters

sim_data	array with simulated intensities.
exp_data	array with intensity values obtained from an experiment.
exp_stdv	array with experimental data uncertainties.
weight_factors	user-defined weighting factors. Used linearly, no matter which norm is chosen.

Definition at line 90 of file ObjectiveMetric.cpp.

 {
     checkIntegrity(sim_data, exp_data, exp_stdv, weight_factors);
  
     double result = 0.0;
     auto norm_fun = norm();
     for (size_t i = 0, sim_size = sim_data.size(); i < sim_size; ++i)
         if (exp_data[i] >= 0.0 && weight_factors[i] > 0.0 && exp_stdv[i] > 0.0)
             result += norm_fun((exp_data[i] - sim_data[i]) / exp_stdv[i]) * weight_factors[i];
  
     return std::isfinite(result) ? result : double_max;
 }

◆ computeFromArrays() [3/4]

double Chi2Metric::computeFromArrays

override

Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors. All arrays involved in the computation must be of the same size.

Parameters

sim_data	array with simulated intensities.
exp_data	array with intensity values obtained from an experiment.
weight_factors	user-defined weighting factors. Used linearly, no matter which norm is chosen.

Definition at line 101 of file ObjectiveMetric.cpp.

 {
     checkIntegrity(sim_data, exp_data, weight_factors);
  
     auto norm_fun = norm();
     double result = 0.0;
     for (size_t i = 0, sim_size = sim_data.size(); i < sim_size; ++i)
         if (exp_data[i] >= 0.0 && weight_factors[i] > 0.0)
             result += norm_fun(exp_data[i] - sim_data[i]) * weight_factors[i];
  
     return std::isfinite(result) ? result : double_max;
 }

◆ computeFromArrays() [4/4]

double meanRelativeDifferenceMetric::computeFromArrays	(	std::vector< double >	sim_data,
		std::vector< double >	exp_data,
		std::vector< double >	weight_factors
	)		const

overridevirtual

Computes metric value from data arrays. Negative values in exp_data are ignored as well as non-positive weight_factors. All arrays involved in the computation must be of the same size.

Parameters

sim_data	array with simulated intensities.
exp_data	array with intensity values obtained from an experiment.
weight_factors	user-defined weighting factors. Used linearly, no matter which norm is chosen.

Reimplemented from Chi2Metric.

Definition at line 219 of file ObjectiveMetric.cpp.

 {
     checkIntegrity(sim_data, exp_data, weight_factors);
  
     double result = 0.0;
     auto norm_fun = norm();
     for (size_t i = 0, sim_size = sim_data.size(); i < sim_size; ++i) {
         if (weight_factors[i] <= 0.0 || exp_data[i] < 0.0)
             continue;
         const double sim_val = std::max(double_min, sim_data[i]);
         const double exp_val = std::max(double_min, exp_data[i]);
         result += norm_fun((exp_val - sim_val) / (exp_val + sim_val)) * weight_factors[i];
     }
  
     return std::isfinite(result) ? result : double_max;
 }

References ObjectiveMetric::norm().

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◆ norm()

auto ObjectiveMetric::norm ( ) const

inlineinherited

Returns a copy of the normalization function used.

Definition at line 67 of file ObjectiveMetric.h.

67 { return m_norm; }

ObjectiveMetric::m_norm

std::function< double(double)> m_norm

Definition: ObjectiveMetric.h:70

References ObjectiveMetric::m_norm.

Referenced by LogMetric::computeFromArrays(), Chi2Metric::computeFromArrays(), PoissonLikeMetric::computeFromArrays(), computeFromArrays(), and ObjectiveMetric::setNorm().

◆ setNorm()

void ObjectiveMetric::setNorm ( std::function< double(double)> norm )

inherited

Definition at line 79 of file ObjectiveMetric.cpp.

 {
     m_norm = std::move(norm);
 }

References ObjectiveMetric::m_norm, and ObjectiveMetric::norm().

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◆ 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_norm

std::function<double(double)> ObjectiveMetric::m_norm

privateinherited

Definition at line 70 of file ObjectiveMetric.h.

Referenced by ObjectiveMetric::norm(), and ObjectiveMetric::setNorm().

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

/home/build/builds/o5h8MZZm/0/mlz/bornagain/Sim/Fitting/ObjectiveMetric.h
/home/build/builds/o5h8MZZm/0/mlz/bornagain/Sim/Fitting/ObjectiveMetric.cpp

Description

Public Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ meanRelativeDifferenceMetric()

Member Function Documentation

◆ clone()

◆ compute()

◆ computeFromArrays() [1/4]

◆ computeFromArrays() [2/4]

◆ computeFromArrays() [3/4]

◆ computeFromArrays() [4/4]

◆ norm()

◆ setNorm()

◆ transferToCPP()

Member Data Documentation

◆ m_norm