#include <gplvm.h>

Inheritance diagram for GPLVM:

Collaboration diagram for GPLVM:

Public Member Functions
void	setSpecificParameters (double sigma=1.0)
	Set specific parameters. More...

void	reduceDimensionality ()
	Reduce dimensionality. More...

double	objectiveFunction ()
	Objective function. More...

Public Member Functions inherited from PCA
void	reduceDimensionality ()
	Reduce dimensionality. More...

Public Member Functions inherited from DimRedAlgorithm
	DimRedAlgorithm ()
	Empty constructor. More...

void	setInputData (Matrix2D< double > &X)
	Set input data. More...

void	setOutputDimensionality (size_t outputDim)
	Set output dimensionality. More...

const Matrix2D< double > &	getReducedData ()
	Get reduced data. More...

Public Attributes
double	sigma

Matrix2D< double >	K

Matrix2D< double >	tmp

Matrix1D< double >	sumY2

Public Attributes inherited from DimRedAlgorithm
Matrix2D< double > *	X
	Pointer to input data. More...

size_t	outputDim
	Output dim. More...

Matrix2D< double >	Y
	Output data. More...

DimRedDistance2	distance
	Distance function. More...

FileName	fnMapping
	Save mapping. More...

Detailed Description

Class for making a GPLVM dimensionality reduction

Definition at line 39 of file gplvm.h.

Member Function Documentation

◆ objectiveFunction()

double GPLVM::objectiveFunction ( )

Objective function.

Definition at line 34 of file gplvm.cpp.

 {
     sumY2.initZeros(MAT_YSIZE(Y));
     FOR_ALL_ELEMENTS_IN_MATRIX2D(Y)
         VEC_ELEM(sumY2,i)+=MAT_ELEM(Y,i,j)*MAT_ELEM(Y,i,j);
 
     double aux=1.0/(2*sigma*sigma);
     K.resizeNoCopy(MAT_YSIZE(Y),MAT_YSIZE(Y));
     FOR_ALL_ELEMENTS_IN_MATRIX2D(K)
     {
         double aux2=0;
         for (int k=0; k<MAT_XSIZE(Y); k++)
             aux2+=MAT_ELEM(Y,i,k)*MAT_ELEM(Y,j,k);
         MAT_ELEM(K,i,j)=exp((2*aux2-VEC_ELEM(sumY2,i)-VEC_ELEM(sumY2,j))*aux);
     }
 
     matrixOperation_AAt(*X,tmp);
     tmp= K.inv() * tmp;
 
     double d=MAT_YSIZE(*X);
     double n=MAT_XSIZE(*X);
     return(-(d*n/2) * log( 2 * M_PI) - (n/2) * log(K.det()+2.2e-308) - 0.5 * tmp.trace());
 }

◆ reduceDimensionality()

void GPLVM::reduceDimensionality ( )

virtual

Reduce dimensionality.

Implements DimRedAlgorithm.

Definition at line 67 of file gplvm.cpp.

 {
     // Compute the first guess
     PCA::reduceDimensionality();
 
     // Refine
     Matrix1D<double> pY(MAT_XSIZE(Y)*MAT_YSIZE(Y)), steps(MAT_XSIZE(Y)*MAT_YSIZE(Y));
     steps.initConstant(1);
     memcpy(&VEC_ELEM(pY,0),&MAT_ELEM(Y,0,0),VEC_XSIZE(pY)*sizeof(double));
     double goal;
     int iter;
     powellOptimizer(pY,1,VEC_XSIZE(pY),&gplvmObjectiveFuntion,this,0.01,goal,iter,steps,true);
     memcpy(&MAT_ELEM(Y,0,0),&VEC_ELEM(pY,0),VEC_XSIZE(pY)*sizeof(double));
 }

◆ setSpecificParameters()

void GPLVM::setSpecificParameters ( double sigma = 1.0 )

Set specific parameters.

Definition at line 29 of file gplvm.cpp.

 {
     this->sigma=sigma;
 }

Member Data Documentation

◆ K

Matrix2D<double> GPLVM::K

Definition at line 53 of file gplvm.h.

◆ sigma

double GPLVM::sigma

Definition at line 42 of file gplvm.h.

◆ sumY2

Matrix1D<double> GPLVM::sumY2

Definition at line 54 of file gplvm.h.

◆ tmp

Matrix2D<double> GPLVM::tmp