#include <fuzzy_code_book.h>

Inheritance diagram for FuzzyCodeBook:

Collaboration diagram for FuzzyCodeBook:

Public Types
typedef std::vector< std::vector< floatFeature > >	MM

typedef ClassicTrainingVectors	TS
	Alias for Membership Matrix. More...

typedef ClassificationTrainingSet< std::vector< floatFeature >, floatFeature >	FV
	Alias for a Training set. More...

Public Types inherited from ClassificationDataSet< FeatureVector, Label >
typedef FeatureVector	In
	Class of input vectors. Usually a FeatureVector (vector of Feature) More...

typedef Label	Out
	Class of the target. Can be a double, string, unsigned, even a vector ... More...

typedef ClassificationTrainingSet< In, Out >	TS
	Training set. Set of vectors (training vectors), probably classified. More...

Public Types inherited from ClassificationTrainingSet< FeatureVector, Label >
enum	splitMode
	Ways the training set can be used. More...

enum	useMode
	use of samples More...

typedef std::multimap< unsigned, unsigned, std::less< unsigned > >	splitTS
	Training sets mode. More...

typedef splitTS::iterator	splitIt
	iterator More...

Public Member Functions
	FuzzyCodeBook (const bool &_calib=false)

	FuzzyCodeBook (unsigned _n, unsigned _size, unsigned _data, bool _cal=false)

	FuzzyCodeBook (unsigned _n, unsigned _size, unsigned _data, double _lower=0, double _upper=1, bool _cal=false)

	FuzzyCodeBook (unsigned _n, const ClassicTrainingVectors &_ts, const bool _use_rand_cvs=false)

	FuzzyCodeBook (std::istream &_is, const unsigned _size=0)

virtual	~FuzzyCodeBook ()

floatFeature &	membAt (unsigned _di, unsigned _ci)

unsigned	membClusters () const

unsigned	membVectors () const

virtual FeatureVector &	fuzzyTest (unsigned _in) const

virtual unsigned	fuzzyTestIndex (unsigned _in) const

virtual unsigned	fuzzyWinner (unsigned _in) const

virtual unsigned	fuzzyOutput (unsigned _in) const

virtual void	classify (const ClassicTrainingVectors *_ts)

virtual TS	alphaCore (TS _ts, double _alpha, unsigned _cluster) const

virtual void	writeMembership (std::ostream &_os) const

virtual void	readMembership (std::istream &_is)

virtual void	saveObject (std::ostream &_os) const

virtual void	loadObject (std::istream &_is)

virtual void	readSelf (std::istream &_is, const unsigned _size=0)

Public Member Functions inherited from CodeBook
	CodeBook (const bool &_calib=false)

	CodeBook (unsigned _n, unsigned _size, bool _cal=false)

	CodeBook (unsigned _n, unsigned _size, floatFeature _lower=0, floatFeature _upper=1, bool _cal=false)

	CodeBook (unsigned _n, const ClassicTrainingVectors &_ts, const bool _use_rand_cvs)

	CodeBook (std::istream &_is)

virtual	~CodeBook ()

virtual FeatureVector &	test (const FeatureVector &_in) const

virtual unsigned	testIndex (const FeatureVector &_in) const

virtual const std::vector< unsigned > &	classifAt (const unsigned &_index) const

virtual unsigned	classifSizeAt (const unsigned &_index) const

virtual Label	apply (const FeatureVector &_in) const

virtual void	calibrate (ClassicTrainingVectors &_ts, Label _def="")

virtual unsigned	output (const FeatureVector &_in) const

virtual void	printSelf (std::ostream &_os) const

virtual void	readSelf (std::istream &_is, long _dim=-1, long _size=-1)

virtual void	Normalize (const std::vector< ClassicTrainingVectors::statsStruct > &_varStats)

virtual void	unNormalize (const std::vector< ClassicTrainingVectors::statsStruct > &_varStats)

virtual void	printHistogram (std::ostream &_os) const

virtual void	printQuantError (std::ostream &_os) const

Public Member Functions inherited from ClassificationDataSet< FeatureVector, Label >
	ClassificationDataSet ()

virtual	~ClassificationDataSet ()

Public Member Functions inherited from ClassificationTrainingSet< FeatureVector, Label >
	ClassificationTrainingSet (const bool &_calib=true, unsigned _n=0)

	ClassificationTrainingSet (std::istream &_is)

virtual	~ClassificationTrainingSet ()

void	setSplit (float _tp, float _vp)

splitIt	beginSubset (unsigned _um)

splitIt	endSubset (unsigned _um)
	Returns an iterator to the end of the subset. More...

virtual void	add (const FeatureVector &_i, const Label &_tg)

virtual void	add (const FeatureVector &_i)

virtual bool	remove (unsigned int _idx)

size_t	size () const

const Label &	targetAt (unsigned _i) const

Label &	targetAt (unsigned _i)

const FeatureVector &	itemAt (unsigned _i) const

FeatureVector &	itemAt (unsigned _i)

bool	calibrated () const

void	calibrated (const bool &_calib)

void	clear ()

virtual void	readSelf (std::istream &_is)

unsigned	numTargets () const

virtual bool	swapItems (unsigned _i, unsigned _j)

Public Attributes
MM	memb
	Alias for Fuzzy vectors. More...

Public Attributes inherited from CodeBook
std::vector< std::vector< unsigned > >	classifVectors

std::vector< double >	aveDistances

Public Attributes inherited from ClassificationTrainingSet< FeatureVector, Label >
std::vector< FeatureVector >	theItems

std::vector< Label >	theTargets

Additional Inherited Members
Protected Member Functions inherited from CodeBook
void	readClassifVectors (std::istream &_is)

void	writeClassifVectors (std::ostream &_os) const

Protected Member Functions inherited from ClassificationTrainingSet< FeatureVector, Label >
void	computeNumTargets ()

void	checkCalibrated (std::istream &_is)

void	readItems (std::istream &_is)

void	writeCalibrated (std::ostream &_os) const

void	writeItems (std::ostream &_os, bool _delim=false) const

void	skipComments (std::istream &_is) const

std::vector< FeatureVector >::const_iterator	itemsBegin () const

std::vector< FeatureVector >::const_iterator	itemsEnd () const

std::vector< Label >::const_iterator	targetsBegin () const

std::vector< Label >::const_iterator	targetsEnd () const

Protected Attributes inherited from ClassificationTrainingSet< FeatureVector, Label >
bool	isCalibrated

splitTS	splitTrainingSet

unsigned	nTargets

Detailed Description

This class implements an specific Data Structure for Fuzzy algorithms. It inherits fron CodeBook, so this Data Structure is basically a codebook with a Fuzzy-membership Matrix. Some of the methods from CodeBook are redefined.

Definition at line 44 of file fuzzy_code_book.h.

Member Typedef Documentation

◆ FV

typedef ClassificationTrainingSet<std::vector<floatFeature>, floatFeature > FuzzyCodeBook::FV

Alias for a Training set.

Definition at line 53 of file fuzzy_code_book.h.

◆ MM

typedef std::vector< std::vector< floatFeature > > FuzzyCodeBook::MM

Definition at line 48 of file fuzzy_code_book.h.

◆ TS

typedef ClassicTrainingVectors FuzzyCodeBook::TS

Alias for Membership Matrix.

Definition at line 51 of file fuzzy_code_book.h.

Constructor & Destructor Documentation

◆ FuzzyCodeBook() [1/5]

FuzzyCodeBook::FuzzyCodeBook ( const bool & _calib = false )

inline

Default constructor Parameter: _calib Calibrated or not, that is, a CB with class labels or not

Definition at line 63 of file fuzzy_code_book.h.

63 : CodeBook(_calib)

64 {};

CodeBook::CodeBook

CodeBook(const bool &_calib=false)

Definition: code_book.h:69

◆ FuzzyCodeBook() [2/5]

FuzzyCodeBook::FuzzyCodeBook	(	unsigned	_n,
		unsigned	_size,
		unsigned	_data,
		bool	_cal = `false`
	)

Constructor. Constructs a fuzzy codebook with initial code vectors filled with zero. Parameter: _n Number of code vectors Parameter: _size Size of code vectors Parameter: _data Size of the training set Parameter: _cal Calibrated or not, that is, a CB with class labels or not It calls Base Class constructor (CodeBook)

Constructor. Constructs a codebook with initial code vectors filled with zero. Parameter: _n Number of vectors (clusters) Parameter: _size Size of code vectors Parameter: _cal Calibrated or not, that is, a CB with class labels or not It calls Base Class constructor (CodeBook)

Definition at line 41 of file fuzzy_code_book.cpp.

                              : CodeBook(_n, _size, _cal)
 {
 
     // Initialize Fuzzy membership Matrix
 
     numClusters = _n;
     numVectors = _data;
     memb.resize(numVectors);
     for (unsigned k = 0; k < numVectors; k++)
     {
         std::vector <floatFeature> v;
         v.resize(numClusters, 0);
         memb[k] = v;
     } // for k
 
 }

◆ FuzzyCodeBook() [3/5]

FuzzyCodeBook::FuzzyCodeBook	(	unsigned	_n,
		unsigned	_size,
		unsigned	_data,
		double	_lower = `0`,
		double	_upper = `1`,
		bool	_cal = `false`
	)

Constructor. Constructs a fuzzy codebook with random initial code vectors. Parameter: _n Number of code vectors Parameter: _size Size of code vectors Parameter: _data Size of the training set Parameter: _lower Lower value for random elements Parameter: _upper Upper value for random elements Parameter: _cal Calibrated or not, that is, a CB with class labels or not It calls Base Class constructor (CodeBook)

Constructor. Constructs a codebook with random initial code vectors. Parameter: _n Number of vectors Parameter: _size Size of code vectors Parameter: _lower Lower value for random elements Parameter: _upper Upper value for random elements Parameter: _cal Calibrated or not, that is, a CB with class labels or not It calls Base Class constructor (CodeBook)

Definition at line 72 of file fuzzy_code_book.cpp.

                              : CodeBook(_n, _size, _lower, _upper, _cal)
 {
 
     // Initialize Fuzzy membership Matrix
 
     numClusters = _n;
     numVectors = _data;
     memb.resize(numVectors);
     for (unsigned k = 0; k < numVectors; k++)
     {
         std::vector <floatFeature> v;
         v.resize(numClusters, 0);
         memb[k] = v;
     } // for k
 
 }

◆ FuzzyCodeBook() [4/5]

FuzzyCodeBook::FuzzyCodeBook	(	unsigned	_n,
		const ClassicTrainingVectors &	_ts,
		const bool	_use_rand_cvs = `false`
	)

Constructor. Constructs a fuzzy codebook with initial code vectors taken randomly from the training file. Parameter: _n Number of vectors Parameter: _ts Training set; will be used to get initial values Parameter: _use_rand_cvs Use random code vectors (inherited from base class) It calls Base Class constructor (CodeBook)

Constructor. Constructs a codebook with initial code vectors taken randomly from the training file. Parameter: _n Number of vectors Parameter: _ts Training set; will be used to get initial values Parameter: _use_rand_cvs Use random code vectors (inherited from base class) It calls Base Class constructor (CodeBook)

Definition at line 105 of file fuzzy_code_book.cpp.

                                   : CodeBook(_n, _ts, _use_rand_cvs)
 {
     // Initialize Fuzzy membership Matrix
 
     numClusters = _n;
     numVectors = _ts.size();
     memb.resize(numVectors);
     std::vector <floatFeature> v;
     v.resize(numClusters, 0);
     for (unsigned k = 0; k < numVectors; k++)
     {
         memb[k] = v;
     } // for k
 }

◆ FuzzyCodeBook() [5/5]

FuzzyCodeBook::FuzzyCodeBook	(	std::istream &	_is,
		const unsigned	_size = `0`
	)

Constructs a fuzzy code book given a stream Parameter: _is The input stream Parameter: _size Size of code vectors (number of data points)

Exceptions

runtime_error If there are problems with the stream

Definition at line 127 of file fuzzy_code_book.cpp.

 {
     readSelf(_is);
     // Initialize Fuzzy membership Matrix
 
     numClusters = theItems.size();
     numVectors = _size;
     memb.clear();
     memb.resize(numVectors);
     for (unsigned k = 0; k < numVectors; k++)
     {
         std::vector <floatFeature> v;
         v.resize(numClusters, 0);
         memb[k] = v;
     } // for k
 }

◆ ~FuzzyCodeBook()

virtual FuzzyCodeBook::~FuzzyCodeBook ( )

inlinevirtual

Virtual destructor

Definition at line 120 of file fuzzy_code_book.h.

121 {};

Member Function Documentation

◆ alphaCore()

FuzzyCodeBook::TS FuzzyCodeBook::alphaCore	(	TS	_ts,
		double	_alpha,
		unsigned	_cluster
	)		const

virtual

Returns the alpha-core set (also called alpha-level set or simply "core") Parameter: _ts The training set Parameter: _alpha A threshold to identify the core. Parameter: _cluster The cluster or partition Returns a training vector "contained" in the cluster

Returns the alpha-core set (also called alpha-level set or simply "core") Parameter: _ts The training set Parameter: _alpha A threshold to identify the core. Parameter: _cluster The cluster or partition

Definition at line 369 of file fuzzy_code_book.cpp.

 {
     FuzzyCodeBook::TS _alphaSet(0, _ts.calibrated());
 
     _alphaSet.theItems.resize(membVectors());
     if (_ts.calibrated())
         _alphaSet.theTargets.resize(membVectors());
 
     if ((_alpha < 0) || (_alpha > 1))
     {
         std::ostringstream msg;
         msg << "threshold must be in [0,1]";
         throw std::runtime_error(msg.str());
     }
 
     if ((_cluster < 0) || (_cluster >= membClusters()))
     {
         std::ostringstream msg;
         msg << "Invalid cluster number";
         throw std::runtime_error(msg.str());
     }
     for (unsigned k = 1; k < membVectors(); k++)
     {     // Number of input vectors
 
         double maxMemb = memb[k][_cluster];
         unsigned maxIndex = _cluster;                 // Impossible cluster index
         for (unsigned i = 0; i < membClusters(); i++)
         {   // Number of clusters
             if (i != _cluster)
                 if (maxMemb < memb[k][i])
                 {      // Always find the maximum
                     maxMemb = memb[k][i];
                     maxIndex = i;
                 }
         } // for i
 
         if (maxIndex == _cluster && maxMemb >= _alpha)        // If above threshold
             _alphaSet.theItems[k] = _ts.theItems[k];
         if (_ts.calibrated())
             _alphaSet.theTargets[k] =  _ts.theTargets[k];
 
     } // for k
 
     return _alphaSet;
 }

◆ classify()

void FuzzyCodeBook::classify ( const ClassicTrainingVectors * _ts )

virtual

Fills the classifVectors with the list of the best input vectors associated to it. In this case, it uses the Fuzzy Memberships to make the assignments Parameter: _ts Sample list to classify

Reimplemented from CodeBook.

Definition at line 310 of file fuzzy_code_book.cpp.

 {
     classifVectors.clear(); // clear previous classification.
     classifVectors.resize(size());
     aveDistances.clear(); // clear previous classification.
     aveDistances.resize(size());
 
     for (unsigned j = 0 ; j < _ts->size() ; j++)
         classifVectors[fuzzyTestIndex(j)].push_back(j);
 
     for (unsigned i = 0 ; i < size() ; i++)
     {
         double aveDist = 0;
         for (unsigned j = 0 ; j < classifVectors[i].size() ; j++)
             aveDist += euclideanDistance(theItems[i], _ts->theItems[classifVectors[i][j]]);
         if (classifVectors[i].size() != 0)
             aveDist /= (double) classifVectors[i].size();
         aveDistances[i] = (double) aveDist;
     }
 
 }

◆ fuzzyOutput()

unsigned FuzzyCodeBook::fuzzyOutput ( unsigned _in ) const

virtual

Returns the index of the codevector closest to an input. This is the method used to classify inputs Parameter: _in Index to the Sample to be classified

Definition at line 299 of file fuzzy_code_book.cpp.

 {
     return fuzzyTestIndex(_in);
 }

◆ fuzzyTest()

FeatureVector & FuzzyCodeBook::fuzzyTest ( unsigned _in ) const

virtual

Returns the code vector that represents the input in the codebook Parameter: _in Sample to classify Note: The difference between Fuzzy codevector and non-Fuzzy codevector is that the best (winner) is estimated using the fuzzy membership matrix.

Definition at line 209 of file fuzzy_code_book.cpp.

 {
     double maxMemb = 0;
     unsigned best = 0;
 
     for (unsigned c = 0; c < membClusters(); c++)
     {
         if (maxMemb < memb[_in][c])
         {
             maxMemb = (double) memb[_in][c];
             best = c;
         } //if
     } // for i
 
     return (FeatureVector&) theItems[best];
 }

◆ fuzzyTestIndex()

unsigned FuzzyCodeBook::fuzzyTestIndex ( unsigned _in ) const

virtual

Returns the index to the code vector that represents the input in the codebook Parameter: _in Sample to classify Note: The difference between Fuzzy codevector and non-Fuzzy codevector is that the best (winner) is estimated using the fuzzy membership matrix.

Definition at line 233 of file fuzzy_code_book.cpp.

 {
     double maxMemb = 0;
     unsigned best = 0;
 
     for (unsigned c = 0; c < membClusters(); c++)
     {
         if (maxMemb < memb[_in][c])
         {
             maxMemb = (double) memb[_in][c];
             best = c;
         } //if
     } // for i
 
     return best;
 }

◆ fuzzyWinner()

unsigned FuzzyCodeBook::fuzzyWinner ( unsigned _in ) const

virtual

Returns the index of the codevector closest to an input. This is the method used to classify inputs Parameter: _in Index to the Sample to be classified

Definition at line 289 of file fuzzy_code_book.cpp.

 {
     return fuzzyTestIndex(_in);
 }

◆ loadObject()

void FuzzyCodeBook::loadObject ( std::istream & _is )

virtual

Loads the xmippFuzzyCodeBook class from a stream. this method can be used to load the status of the class. Parameter: _is The output stream

Loads the FuzzyCodeBook class from a stream. this method can be used to load the status of the class. Parameter: _is The output stream

Reimplemented from CodeBook.

Reimplemented in FuzzyMap.

Definition at line 483 of file fuzzy_code_book.cpp.

 {
     clear();
     readMembership(_is);
     CodeBook::loadObject(_is);
 }

◆ membAt()

floatFeature & FuzzyCodeBook::membAt	(	unsigned	_di,
		unsigned	_ci
	)

Fuctions to access the Fuzzy Membership Matrix Returns a reference to the specified item Parameter: _ci cluster index Parameter: _di data index

Exceptions

out_of_range If _i is out of range

Definition at line 174 of file fuzzy_code_book.cpp.

 {
     std::ostringstream msg;
     if ((_di >= membVectors()) || (_ci >= membClusters()))
     {
         msg << "Out of range. No item at position " << _di << "," << _ci << std::endl;
         throw std::out_of_range(msg.str());
     }
 
     return memb[_di][_ci];
 }

◆ membClusters()

unsigned FuzzyCodeBook::membClusters ( ) const

Returns dimensions of the Membership matrix

Definition at line 191 of file fuzzy_code_book.cpp.

 {
     return numClusters;
 }

◆ membVectors()

unsigned FuzzyCodeBook::membVectors ( ) const

Definition at line 195 of file fuzzy_code_book.cpp.

 {
     return numVectors;
 }

◆ readMembership()

void FuzzyCodeBook::readMembership ( std::istream & _is )

virtual

Reads the membership values Parameter: _is The input stream

Definition at line 432 of file fuzzy_code_book.cpp.

 {
     _is >> numVectors;
     memb.resize(numVectors);
     for (unsigned k = 0; k < numVectors; k++)    // Number of input vectors
         _is >> memb[k];
     numClusters = memb[0].size();
 }

◆ readSelf()

void FuzzyCodeBook::readSelf	(	std::istream &	_is,
		const unsigned	_size = `0`
	)

virtual

Constructs a fuzzy code book given a stream Parameter: _is The input stream Parameter: _size Size of code vectors (number of data points)

Exceptions

runtime_error If there are problems with the stream

Reimplemented in FuzzyMap.

Definition at line 460 of file fuzzy_code_book.cpp.

 {
     CodeBook::readSelf(_is);
     // Initialize Fuzzy membership Matrix
     numClusters = theItems.size();
     numVectors = _size;
     memb.clear();
     memb.resize(numVectors);
     for (size_t k = 0; k < numVectors; k++)
     {
         std::vector <floatFeature> v;
         v.resize(numClusters, 0);
         memb[k] = v;
     } // for k
 }

◆ saveObject()

void FuzzyCodeBook::saveObject ( std::ostream & _os ) const

virtual

Saves the xmippFuzzyCodeBook class into a stream. this method can be used to save the status of the class. Parameter: _os The output stream

Saves the FuzzyCodeBook class into a stream. this method can be used to save the status of the class. Parameter: _os The output stream

Reimplemented from CodeBook.

Reimplemented in FuzzyMap.

Definition at line 447 of file fuzzy_code_book.cpp.

 {
     writeMembership(_os);
     CodeBook::saveObject(_os);
 }

◆ writeMembership()

void FuzzyCodeBook::writeMembership ( std::ostream & _os ) const

virtual

Writes the membership values Parameter: _os The output stream

Definition at line 420 of file fuzzy_code_book.cpp.

 {
     _os << membVectors() << std::endl;
     for (unsigned k = 0; k < numVectors; k++)   // Number of input vectors
         _os << memb[k] << std::endl;
 }

Member Data Documentation

◆ memb

MM FuzzyCodeBook::memb

Alias for Fuzzy vectors.

Definition at line 57 of file fuzzy_code_book.h.

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

xmipp/libraries/classification/fuzzy_code_book.h
xmipp/libraries/classification/fuzzy_code_book.cpp

Public Types

Public Member Functions

Public Attributes

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ FV

◆ MM

◆ TS

Constructor & Destructor Documentation

◆ FuzzyCodeBook() [1/5]

◆ FuzzyCodeBook() [2/5]

◆ FuzzyCodeBook() [3/5]

◆ FuzzyCodeBook() [4/5]

◆ FuzzyCodeBook() [5/5]

◆ ~FuzzyCodeBook()

Member Function Documentation

◆ alphaCore()

◆ classify()

◆ fuzzyOutput()

◆ fuzzyTest()

◆ fuzzyTestIndex()

◆ fuzzyWinner()

◆ loadObject()

◆ membAt()

◆ membClusters()

◆ membVectors()

◆ readMembership()

◆ readSelf()

◆ saveObject()

◆ writeMembership()

Member Data Documentation

◆ memb