LHAPDF: LHAPDF::PDFSet Class Reference

Class for PDF-set metadata and manipulation. More...

#include <PDFSet.h>

Inheritance diagram for LHAPDF::PDFSet:

Public Member Functions
	PDFSet ()

	PDFSet (const std::string &setname)

void	print (std::ostream &os=std::cout, int verbosity=1) const
	Summary printout.

PDF set metadata specialisations
std::string	name () const
	PDF set name. More...

std::string	description () const
	Description of the set.

int	lhapdfID () const
	First LHAPDF global index in this PDF set.

int	dataversion () const
	Version of this PDF set's data files.

std::string	errorType () const
	Get the type of PDF errors in this set (replicas, symmhessian, hessian, custom, etc.)

PDFErrInfo	errorInfo () const
	Get the structured decomposition of the error-type string.

double	errorConfLevel () const
	Get the confidence level of the Hessian eigenvectors, in percent. More...

size_t	size () const
	Number of members in this set.

size_t	errorSize () const

size_t	errSize () const

Creating PDF members
PDF *	mkPDF (size_t member) const

template<typename PTR >
void	mkPDFs (std::vector< PTR > &pdfs) const

std::vector< PDF * >	mkPDFs () const

template<typename PTR >
std::vector< PTR >	mkPDFs () const

Generic metadata cascading mechanism
Todo: Add AlphaS getter for set-level alphaS?
std::vector< std::string >	keys () const
	Get the keys defined on this object or higher.

bool	has_key (const std::string &key) const
	Can this Info object return a value for the given key? (it may be defined non-locally)

const std::string &	get_entry (const std::string &key) const
	Retrieve a metadata string by key name.

const std::string &	get_entry (const std::string &key, const std::string &fallback) const
	Retrieve a metadata string by key name, with a fallback.

PDF set uncertainty functions
See the Calculating PDF uncertainties group for more details
PDFUncertainty	uncertainty (const std::vector< double > &values, double cl=CL1SIGMA, bool alternative=false) const
	Calculate the central value and PDF uncertainty on an observable. More...

void	uncertainty (PDFUncertainty &rtn, const std::vector< double > &values, double cl=CL1SIGMA, bool alternative=false) const
	Calculate the PDF uncertainty on an observable (as above), with efficient no-copy return to the `rtn` argument. More...

std::vector< PDFUncertainty >	uncertainties (const std::vector< std::vector< double >> &observables_values, double cl=CL1SIGMA, bool alternative=false) const
	Calculate PDF uncertainties on multiple observables at once. More...

void	uncertainties (std::vector< PDFUncertainty > &rtn, const std::vector< std::vector< double >> &observables_values, double cl=CL1SIGMA, bool alternative=false) const
	Calculate multiple PDF uncertainties (as above), with efficient no-copy return to the `rtn` argument. More...

double	correlation (const std::vector< double > &valuesA, const std::vector< double > &valuesB) const
	Calculate the PDF correlation between `valuesA` and `valuesB` using appropriate formulae for this set. More...

double	randomValueFromHessian (const std::vector< double > &values, const std::vector< double > &randoms, bool symmetrise=true) const
	Generate a random value from Hessian `values` and Gaussian random numbers. More...

void	_checkPdfType (const std::vector< string > &pdftypes) const

Public Member Functions inherited from LHAPDF::Info
	Info ()
	Default constructor.

	Info (const std::string &path)
	Constructor.

virtual	~Info ()
	Virtual destructor to allow inheritance.

void	load (const std::string &filepath)

std::vector< std::string >	keys_local () const
	Get the keys defined on this specific object.

std::vector< std::string >	keys () const

bool	has_key_local (const std::string &key) const
	Is a value defined for the given key on this specific object?

const std::string &	get_entry_local (const std::string &key) const
	Retrieve a metadata string by key name, as defined on this specific object.

template<typename T >
T	get_entry_as (const std::string &key) const

template<typename T >
T	get_entry_as (const std::string &key, const T &fallback) const
	Retrieve a metadata entry by key name, with an inline type cast and default fallback.

template<typename T >
void	set_entry (const std::string &key, const T &val)
	Set a keyed value entry.

template<>
bool	get_entry_as (const std::string &key) const

Private Attributes
std::string	_setname
	Name of this set.

PDFErrInfo	_errinfo
	Cached PDF error-info breakdown struct.

Additional Inherited Members
Protected Attributes inherited from LHAPDF::Info
std::map< std::string, std::string >	_metadict
	The string -> string native metadata storage container.

Detailed Description

Class for PDF-set metadata and manipulation.

Examples: /examples/testpdfunc.cc, and /tests/testinfo.cc.

Constructor & Destructor Documentation

◆ PDFSet() [1/2]

LHAPDF::PDFSet::PDFSet ( )

inline

Default constructor (for container compatibility)

Todo:: Remove?

◆ PDFSet() [2/2]

LHAPDF::PDFSet::PDFSet ( const std::string & setname )

Constructor from a set name

Todo:: Remove?

Member Function Documentation

◆ _checkPdfType()

void LHAPDF::PDFSet::_checkPdfType ( const std::vector< string > & pdftypes ) const

Check that the type of each member matches the ErrorType of the set.

Todo:: We need to make the signature clearer – what is the arg? Why not automatically check the members? Why not a plural name? Why not on PDF? "Hiding" the name for now with the leading underscore.

◆ correlation()

double LHAPDF::PDFSet::correlation	(	const std::vector< double > &	valuesA,
		const std::vector< double > &	valuesB
	)		const

Calculate the PDF correlation between valuesA and valuesB using appropriate formulae for this set.

The correlation can vary between -1 and +1 where values close to {-1,0,+1} mean that the two quantities A and B are {anticorrelated,uncorrelated,correlated}, respectively.

For a combined set, the parameter variations are not included in the calculation of the correlation.

See the Calculating PDF uncertainties group for more details

◆ errorConfLevel()

double LHAPDF::PDFSet::errorConfLevel ( ) const

Get the confidence level of the Hessian eigenvectors, in percent.

If not defined, assume 1-sigma = erf(1/sqrt(2)) =~ 68.268949% by default, unless this is a replica set for which return -1.

◆ errorSize()

size_t LHAPDF::PDFSet::errorSize ( ) const

inline

Number of error members in this set

Note: Equal to size()-1

◆ errSize()

size_t LHAPDF::PDFSet::errSize ( ) const

inline

Number of error members in this set

Note: Alias for preferred/consistent errorSize()

◆ mkPDF()

PDF* LHAPDF::PDFSet::mkPDF ( size_t member ) const

inline

Make the nth PDF member in this set, returned by pointer

Note: As with the mkPDF factory method, the PDF pointer returned by this method is heap allocated and its memory management is now the responsibility of the caller.

◆ mkPDFs() [1/3]

std::vector<PDF*> LHAPDF::PDFSet::mkPDFs ( ) const

inline

Make all the PDFs in this set, returning as a vector of PDF pointers

Note: As with the mkPDF method and factory function, the PDF pointers returned by this method are heap allocated and their memory management is now the responsibility of the caller.

◆ mkPDFs() [2/3]

template<typename PTR >

std::vector<PTR> LHAPDF::PDFSet::mkPDFs ( ) const

inline

Todo:: Use the following with default function template args if C++11 is being used

◆ mkPDFs() [3/3]

template<typename PTR >

void LHAPDF::PDFSet::mkPDFs ( std::vector< PTR > & pdfs ) const

inline

Make all the PDFs in this set, filling a supplied vector with PDF pointers

This version may be preferred in many circumstances, since it can avoid the overhead of creating a new temporary vector.

A vector of smart pointers can be used, for any smart pointer type which supports construction from a raw pointer argument, e.g. unique_ptr<PDF>(PDF*).

Note: The supplied vector will be cleared before filling!; As with the mkPDF method and factory function, the PDF pointers returned by this method are heap allocated and their memory management is now the responsibility of the caller, either manually for raw pointers or automatically if smart pointers are used.; Use an appropriate smart pointer, of course! This depends in detail on how you will use the PDF objects (do you want shared or unique pointers?), but they also need to be compatible with storage in STL containers, e.g. std::unique_ptr or std::shared_ptr but not the deprecated std::auto_ptr.

Todo:: Needs to be implemented in the header since the arg type is templated.

Todo:: Need to use an std::move here, or write differently, for unique_ptr to work?

◆ name()

std::string LHAPDF::PDFSet::name ( ) const

inline

PDF set name.

Note: Not taken from the .info metadata file.

Examples: /examples/testpdfunc.cc.

◆ randomValueFromHessian()

double LHAPDF::PDFSet::randomValueFromHessian	(	const std::vector< double > &	values,
		const std::vector< double > &	randoms,
		bool	symmetrise = `true`
	)		const

Generate a random value from Hessian values and Gaussian random numbers.

Note: This routine is intended for advanced users!

See Section 6 of G. Watt and R.S. Thorne, JHEP 1208 (2012) 052 [arXiv:1205.4024 [hep-ph]].

Pass a vector values containing a value for each member of the Hessian PDF set. Pass a vector randoms containing neigen random numbers, where neigen is the number of distinct eigenvectors.

Option symmetrise equal to true will symmetrise the random values (in the case of an asymmetric Hessian set) using a corrected Eq. (6.5) of arXiv:1205.4024v2, so that the average tends to the best-fit for a large number of replicas.

Option symmetrise equal to false will use Eq. (6.4) of arXiv:1205.4024v2 (for an asymmetric Hessian set), then the average differs from the best-fit. Option symmetrise has no effect for a symmetric Hessian set.

Random values generated in this way can subsequently be used for applications such as Bayesian reweighting or combining predictions from different groups (as an alternative to taking the envelope). See, for example, supplementary material at http://mstwpdf.hepforge.org/random/.

Use of this routine with a non-Hessian PDF set will throw a UserError.

For a combined set, the parameter variations are not included in the generation of the random value.

See the Calculating PDF uncertainties group for more details

◆ uncertainties() [1/2]

std::vector<PDFUncertainty> LHAPDF::PDFSet::uncertainties	(	const std::vector< std::vector< double >> &	observables_values,
		double	cl = `CL1SIGMA`,
		bool	alternative = `false`
	)		const

inline

Calculate PDF uncertainties on multiple observables at once.

The observables_values nested vector is a list of variation-value lists, with the first (outer) index corresponding to the M observables, e.g. a set of differential-observable bins, and the inner index the N PDF members.

The return value is an M-element vector of PDFUncertainty summaray structs, one per observable.

Warning: The inner _values vector corresponds to the members of this PDF set and must be ordered accordingly.

◆ uncertainties() [2/2]

void LHAPDF::PDFSet::uncertainties	(	std::vector< PDFUncertainty > &	rtn,
		const std::vector< std::vector< double >> &	observables_values,
		double	cl = `CL1SIGMA`,
		bool	alternative = `false`
	)		const

Calculate multiple PDF uncertainties (as above), with efficient no-copy return to the rtn argument.

Warning: The inner _values vector corresponds to the members of this PDF set and must be ordered accordingly.

◆ uncertainty() [1/2]

PDFUncertainty LHAPDF::PDFSet::uncertainty	(	const std::vector< double > &	values,
		double	cl = `CL1SIGMA`,
		bool	alternative = `false`
	)		const

inline

Calculate the central value and PDF uncertainty on an observable.

Warning: The values vector corresponds to the members of this PDF set and must be ordered accordingly.

In the Hessian approach, the central value is the best-fit "values[0]" and the uncertainty is given by either the symmetric or asymmetric formula using eigenvector PDF sets.

If the PDF set is given in the form of replicas, by default, the central value is given by the mean and is not necessarily "values[0]" for quantities with a non-linear dependence on PDFs, while the uncertainty is given by the standard deviation.

Optional argument cl is used to rescale uncertainties to a particular confidence level (in percent); a negative number will rescale to the default CL for this set.

Note: If cl is omitted, automatically rescale to normal 1-sigma ~ 68.268949% uncertainties.

If the PDF set is given in the form of replicas, then optional argument alternative equal to true (default: false) will construct a confidence interval from the probability distribution of replicas, with the central value given by the median.

For a combined set, a breakdown of the separate PDF and parameter variation uncertainties is available. The parameter variation uncertainties are computed from the last 2*n members of the set, with n the number of parameters.

See the Calculating PDF uncertainties group for more details

Todo:: Add option to restrict replica mean & stddev calculation to a central CI set?

Examples: /examples/testpdfunc.cc.

◆ uncertainty() [2/2]

void LHAPDF::PDFSet::uncertainty	(	PDFUncertainty &	rtn,
		const std::vector< double > &	values,
		double	cl = `CL1SIGMA`,
		bool	alternative = `false`
	)		const

Calculate the PDF uncertainty on an observable (as above), with efficient no-copy return to the rtn argument.

Warning: The values vector corresponds to the members of this PDF set and must be ordered accordingly.

Todo:: For real efficiency, the chaining of these functions should be the other way around

See the Calculating PDF uncertainties group for more details

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

/builds/hepcedar/lhapdf/include/LHAPDF/PDFSet.h

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PDFSet() [1/2]

◆ PDFSet() [2/2]

Member Function Documentation

◆ _checkPdfType()

◆ correlation()

◆ errorConfLevel()

◆ errorSize()

◆ errSize()

◆ mkPDF()

◆ mkPDFs() [1/3]

◆ mkPDFs() [2/3]

◆ mkPDFs() [3/3]

◆ name()

◆ randomValueFromHessian()

◆ uncertainties() [1/2]

◆ uncertainties() [2/2]

◆ uncertainty() [1/2]

◆ uncertainty() [2/2]