FST::Distance< DATATYPE, DIMTYPE, SUBSET > Class Template Reference

Abstract class, defines interface for distance evaluators to be used in Classifier_kNN. More...

#include <distance.hpp>

Inheritance diagram for FST::Distance< DATATYPE, DIMTYPE, SUBSET >:

Public Types
typedef std::shared_ptr< SUBSET >	PSubset
	shared pointer to a feature subset, as consumed by narrow_to()

Public Member Functions
	Distance (const Distance &d)
	Copy-constructor; deep-copies the current _index[] mapping (same narrowed/denarrowed state as d).
void	reset (const DIMTYPE n)
	Allocates for n raw features and makes _index[] the identity map 0..n-1, with all n features active (get_d()==get_n()); narrow_to() restricts that.
void	narrow_to (const PSubset sub)
	Restricts distance() to sub's selected features only. Rewrites _index[] to the subset's selected feature indices (raw-feature order) and sets get_d() to the subset size; distance() then reads only those _d entries of a pattern, through _index[], instead of all _n. Precondition: reset() must have been called with n >= the subset size.
void	denarrow ()
	Undoes narrow_to(): _index[] reverts to the identity map and get_d() returns to get_n().
DIMTYPE	get_n () const
	the full (raw, unnarrowed) feature count fixed by reset()
DIMTYPE	get_d () const
	the currently active feature count: the narrowed subset size after narrow_to(), get_n() after reset()/denarrow()
virtual DATATYPE	distance (const DATATYPE *pattern1, const DATATYPE *pattern2)=0
	Distance between two raw patterns over the currently active features only. Reads exactly get_d() entries of each pattern, at the raw indices in _index[] (identity unless narrow_to() is in effect) – concrete distances must index through _index[], never assume a contiguous 0..get_d()-1 layout.
Distance *	clone () const override=0
Distance *	sharing_clone () const override
Distance *	stateless_clone () const override
Public Member Functions inherited from FST::Clonable
bool	is_clone () const
bool	is_sharing () const
	true if this instance is a sharing_clone() result (referencing, not owning, the source's structures)
bool	is_sharing_clone () const
	true if this instance is BOTH a clone and sharing – i.e. specifically a sharing_clone() result, not a clone()/stateless_clone() one
virtual std::ostream &	print (std::ostream &os) const
	writes a human-readable identification of the object; base default writes nothing

Protected Attributes
DIMTYPE	_n
	full raw feature count, fixed by reset()
DIMTYPE	_d
	currently active feature count (see get_d())
std::unique_ptr< DIMTYPE[]>	_index
	maps active-feature position [0,_d) to a raw feature index in [0,_n)

Additional Inherited Members
Protected Member Functions inherited from FST::Clonable
void	set_cloned (const bool cloned=true)
	marks/unmarks this instance as a clone; call from clone()/stateless_clone() overrides (Clonable_Impl does this automatically)
void	set_sharing (const bool sharing=true)
	marks/unmarks this instance as sharing (see is_sharing())
void	set_sharing_cloned (const bool cloned=true, const bool sharing=true)
	sets both flags at once; call from sharing_clone() overrides (Clonable_Impl does this automatically)

Detailed Description

template<typename DATATYPE, typename DIMTYPE, class SUBSET>
class FST::Distance< DATATYPE, DIMTYPE, SUBSET >

Abstract class, defines interface for distance evaluators to be used in Classifier_kNN.

Member Function Documentation

clone()

template<typename DATATYPE, typename DIMTYPE, class SUBSET>

Distance * FST::Distance< DATATYPE, DIMTYPE, SUBSET >::clone ( ) const

overridepure virtual

create 1:1 independent clone of the current object. The caller owns the returned object. Families that cannot support a given clone kind implement it to throw fst_error; Clonable_Impl's CLONE_INHERIT slot defers to such a body.

Implements FST::Clonable.

Implemented in FST::Clonable_Impl< Distance_Euclid< DATATYPE, DIMTYPE, SUBSET >, Distance< DATATYPE, DIMTYPE, SUBSET > >, FST::Clonable_Impl< Distance_L1< DATATYPE, DIMTYPE, SUBSET >, Distance< DATATYPE, DIMTYPE, SUBSET > >, and FST::Clonable_Impl< Distance_Lp< DATATYPE, REALTYPE, DIMTYPE, SUBSET, 1, 1 >, Distance< DATATYPE, DIMTYPE, SUBSET > >.

distance()

template<typename DATATYPE, typename DIMTYPE, class SUBSET>

virtual DATATYPE FST::Distance< DATATYPE, DIMTYPE, SUBSET >::distance ( const DATATYPE * pattern1, const DATATYPE * pattern2 )

pure virtual

Distance between two raw patterns over the currently active features only. Reads exactly get_d() entries of each pattern, at the raw indices in _index[] (identity unless narrow_to() is in effect) – concrete distances must index through _index[], never assume a contiguous 0..get_d()-1 layout.

Parameters

pattern1,pattern2

raw feature vectors of at least get_n() entries each

Returns

a non-negative dissimilarity: 0 for identical patterns, larger values mean farther apart. Implementations are free to return any monotone transform of a true distance (e.g. a squared or fractionally powered one), so the value need NOT satisfy the triangle inequality and need not be a metric. Only the induced ORDER of neighbours matters to the callers (Classifier_kNN).

Implemented in FST::Distance_Euclid< DATATYPE, DIMTYPE, SUBSET >, FST::Distance_L1< DATATYPE, DIMTYPE, SUBSET >, and FST::Distance_Lp< DATATYPE, REALTYPE, DIMTYPE, SUBSET, numerator, denominator >.

sharing_clone()

template<typename DATATYPE, typename DIMTYPE, class SUBSET>

Distance * FST::Distance< DATATYPE, DIMTYPE, SUBSET >::sharing_clone ( ) const

inlineoverridevirtual

create equivalent clone of the current object, permitting read-only access to structures in the source object (allows referencing instead of copying of large memory structures). may be faster and save space but requires more caution with respect to concurrency Use example: Data_Accessor memory data representation cloning

Implements FST::Clonable.

stateless_clone()

template<typename DATATYPE, typename DIMTYPE, class SUBSET>

Distance * FST::Distance< DATATYPE, DIMTYPE, SUBSET >::stateless_clone ( ) const

inlineoverridevirtual

create clone of the current object, ignoring internal temporary structures to save speed. Does not replicate exact object state. The clone must be used carefully in a way that ensures internal structure re-initialization Use example: Data_Splitter cloning or Classifier_LIBSVM cloning due to inability to clone external structures defined in LibSVM

Implements FST::Clonable.

---

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

• /Users/psms/dev/devtest1/_src_criteria/distance.hpp