FitObjective Class Reference

Holds vector of SimDataPairs (experimental data and simulation results) for use in fitting. More...

Public Member Functions
SimulationResult	absoluteDifference (size_t i_item=0) const
	Returns absolute value of difference between simulation and experimental data in the form of SimulationResult.
template<class T >
void	addSimulationAndData (PyBuilderCallback &callback, const T &data, const T &uncertainties, double weight=1.0)
	Constructs simulation/data pair for later fit. More...
template<class T >
void	addSimulationAndData (PyBuilderCallback &callback, const T &data, double weight=1.0)
	Constructs simulation/data pair for later fit. More...
bool	allPairsHaveUncertainties () const
	Returns true if all the data pairs in FitObjective instance contain uncertainties.
bool	containsUncertainties (size_t i_item) const
	Returns true if the specified DataPair element contains uncertainties.
virtual double	evaluate (const mumufit::Parameters &params)
virtual std::vector< double >	evaluate_residuals (const mumufit::Parameters &params)
std::vector< double >	experimental_array () const
	Returns one dimensional array representing merged experimental data. More...
SimulationResult	experimentalData (size_t i_item=0) const
	Returns experimental data in the form of SimulationResult.
void	finalize (const mumufit::MinimizerResult &result)
	Should be explicitely called on last iteration to notify all observers.
unsigned	fitObjectCount () const
void	initPlot (int every_nth, PyObserverCallback &callback)
	Initializes observer callback to be called on every_nth fit iteration.
void	initPrint (int every_nth)
	Initializes printing to standard output on every_nth fit iteration.
IterationInfo	iterationInfo () const
mumufit::MinimizerResult	minimizerResult () const
size_t	numberOfFitElements () const
SimulationResult	relativeDifference (size_t i_item=0) const
	Returns relative difference between simulation and experimental data in the form of SimulationResult.
void	run_simulations (const mumufit::Parameters &params)
void	setChiSquaredModule (const IChiSquaredModule &module)
void	setObjectiveMetric (const std::string &metric)
void	setObjectiveMetric (const std::string &metric, const std::string &norm)
	Sets objective metric to the FitObjective. More...
std::vector< double >	simulation_array () const
	Returns one dimensional array representing merged simulated intensities data. More...
SimulationResult	simulationResult (size_t i_item=0) const
	Returns simulation result in the form of SimulationResult.
std::vector< double >	uncertainties () const
	Returns one-dimensional array representing merged data uncertainties. More...
SimulationResult	uncertaintyData (size_t i_item=0) const
	Returns experimental data uncertainties in the form of SimulationResult.
std::vector< double >	weights_array () const
	Returns one-dimensional array representing merged user weights. More...

Static Public Member Functions
static std::string	availableMetricOptions ()
	Returns available metrics and norms.

Detailed Description

Holds vector of SimDataPairs (experimental data and simulation results) for use in fitting.

Member Function Documentation

addSimulationAndData() [1/2]

template<class T >

void FitObjective::addSimulationAndData	(	PyBuilderCallback &	callback,
		const T &	data,
		const T &	uncertainties,
		double	weight = 1.0
	)

Constructs simulation/data pair for later fit.

Parameters

callback	simulation builder capable of producing simulations
data	experimental data array
uncertainties	data uncertainties array
weight	weight of dataset in metric calculations

addSimulationAndData() [2/2]

template<class T >

void FitObjective::addSimulationAndData	(	PyBuilderCallback &	callback,
		const T &	data,
		double	weight = 1.0
	)

Constructs simulation/data pair for later fit.

Parameters

callback	simulation builder capable of producing simulations
data	experimental data array
weight	weight of dataset in metric calculations

experimental_array()

std::vector< double > FitObjective::experimental_array

(

)

const

Returns one dimensional array representing merged experimental data.

The area outside of the region of interest is not included, masked data is nullified.

setObjectiveMetric()

void FitObjective::setObjectiveMetric	(	const std::string &	metric,
		const std::string &	norm
	)

Sets objective metric to the FitObjective.

Parameters

metric	metric name
norm	metric norm name (defaults to L2-norm)

simulation_array()

std::vector< double > FitObjective::simulation_array

(

)

const

Returns one dimensional array representing merged simulated intensities data.

The area outside of the region of interest is not included, masked data is nullified.

uncertainties()

std::vector< double > FitObjective::uncertainties

(

)

const

Returns one-dimensional array representing merged data uncertainties.

The area outside of the region of interest is not included, masked data is nullified.

weights_array()

std::vector< double > FitObjective::weights_array

(

)

const

Returns one-dimensional array representing merged user weights.

The area outside of the region of interest is not included, masked data is nullified.