void FactorAnalysisStat::getXEstimate(){
if (verbose) cout << "(FactorAnalysisStat) Compute X Estimate "<<endl;
RealVector <double> AUX;
AUX.setSize(_rang);
XLine *pline;
String *pFile;
_matX.setAllValues(0.0);
double *X=_matX.getArray();
double *U=_matU.getArray();
double *S_X_h=_matS_X_h.getArray();
double *aux=AUX.getArray();
double *super_invvar=_super_invvar.getArray();
fileList.rewind();
while((pline=fileList.getLine())!=NULL) {
while((pFile=pline->getElement())!=NULL) {
unsigned long sent=_ndxTable.sessionNb(*pFile);
AUX.setAllValues(0.0);
for(unsigned long i=0;i<_rang;i++)
for(unsigned long k=0;k<_supervsize;k++)
aux[i]+= U[k*_rang+i]*super_invvar[k]*S_X_h[sent*_supervsize+k];
double *l_h_inv=_l_h_inv[sent].getArray();
for(unsigned long i=0;i<_rang;i++)
for(unsigned long k=0;k<_rang;k++)
X[sent*_rang+i]+=l_h_inv[i*_rang+k]*aux[k];
sent++;
}
}
};
void FactorAnalysisStat::getUX(RealVector <double> &ux,String& file) {
ux.setAllValues(0.0);
unsigned long idx=_ndxTable.sessionNb(file);
for (unsigned long i=0;i<_supervsize;i++)
for (unsigned long j=0;j<_rang;j++)
ux[i]+=_matU(i,j)*_matX(idx,j);
};
void FactorAnalysisStat::substractChannelStats(){
if (verbose) cout <<"(FactorAnalysisStat) Compute and Substract Channel FA Stats... "<<endl;
RealVector <double> UX;UX.setSize(_supervsize); UX.setAllValues(0.0);double* ux=UX.getArray();
// Compute Occupations and Statistics
unsigned long loc=0;
unsigned long sent=0;
XLine *pline; String *pFile;
fileList.rewind();
double *super_mean=_super_mean.getArray();
double *N_h=_matN_h.getArray();
double *S_X=_matS_X.getArray();
while((pline=fileList.getLine())!=NULL) {
while((pFile=pline->getElement())!=NULL) {
this->getUX(UX,*pFile);
for(unsigned long k=0;k<_supervsize;k++)
ux[k]+=super_mean[k];
for(unsigned long k=0;k<_mixsize;k++)
for (unsigned long i=0;i<_vsize;i++)
S_X[loc*_supervsize+(k*_vsize+i)]-= N_h[sent*_mixsize+k]*ux[i+k*_vsize];
sent++;
}
loc++;
}
};
void *Uthread(void *threadarg) {
struct Uthread_data *my_data;
my_data = (struct Uthread_data *) threadarg;
// Get data
double *U = my_data->U;
double *N_h=my_data->N_h;
double *S_X_h=my_data->S_X_h;
double *X=my_data->X;
unsigned long _rang=my_data->rang;
unsigned long _supervsize=my_data->sv;
unsigned long _nb_sent=my_data->nbsent;
unsigned long _vsize=my_data->vsize;
unsigned long _mixsize=my_data->mixsize;
unsigned long idxBottom=my_data->idxBottom;
unsigned long idxUp=my_data->idxUp;
RefVector <DoubleSquareMatrix>& _l_h_inv=*(my_data->L);
// Routine
DoubleSquareMatrix L(_rang);
DoubleSquareMatrix L_Inv(_rang);
RealVector <double> R;
R.setSize(_rang);
double *RV=R.getArray();
double *LV=L.getArray();
for (unsigned long g=idxBottom;g<idxUp;g++) {
L.setAllValues(0.0);
// Estimate LU for the gaussian g
for(unsigned long j=0;j<_nb_sent;j++){
double *l_h_inv=_l_h_inv[j].getArray();
for(unsigned long k=0;k<_rang;k++)
for(unsigned long l=0;l<_rang;l++)
LV[k*_rang+l]+=(l_h_inv[k*_rang+l]+X[j*_rang+k]*X[j*_rang+l])*N_h[j*_mixsize+g];
}
L.invert(L_Inv);
double *L_InvV=L_Inv.getArray();
// Estimate LU for the line lineNum
for (unsigned long i=0;i<_vsize;i++) {
unsigned long lineNum=_vsize*g+i;
// estime RU i
R.setAllValues(0.0);
for(unsigned long j=0;j<_nb_sent;j++)
for(unsigned long k=0;k<_rang;k++)
RV[k]+=S_X_h[j*_supervsize+lineNum]*X[j*_rang+k];
// estime U i
for(unsigned long j=0;j<_rang;j++)
for(unsigned long k=0;k<_rang;k++)
U[lineNum*_rang+j]+=L_InvV[j*_rang+k]*RV[k];
}
}
//
pthread_exit((void*) 0);
return(void*)0;
}
void *Lthread(void *threadarg) {
struct Lthread_data *my_data;
my_data = (struct Lthread_data *) threadarg;
double *U = my_data->U;
unsigned long sentBottom = my_data->sentBottom;
unsigned long sentUp = my_data->sentUp;
double *N_h=my_data->N_h;
double *super_invvar=my_data->super_invvar;
unsigned long _rang=my_data->rang;
unsigned long _supervsize=my_data->sv;
unsigned long _vsize=my_data->vsize;
unsigned long _mixsize=my_data->mixsize;
for (unsigned long sent=sentBottom;sent <sentUp;sent++) {
DoubleSquareMatrix L(_rang);
L.setAllValues(0.0);
double *LV=L.getArray();
unsigned long mk;
RealVector <double> AUX;
AUX.setSize(_rang);
AUX.setAllValues(0.0);
for(unsigned long i=0;i<_rang;i++){
for(unsigned long j=0;j<=i;j++){
for(unsigned long k=0;k<_supervsize;k++){
mk=k/_vsize;
LV[i*_rang+j]+=N_h[sent*_mixsize+mk]*super_invvar[k]*U[k*_rang+i]*U[k*_rang+j];
}
}
}
for(unsigned long i=0;i<_rang;i++)
for(unsigned long j=i+1;j<_rang;j++)
LV[i*_rang+j]=LV[j*_rang+i];
for(unsigned long i=0;i<_rang;i++)
LV[i*_rang+i]+=1.0;
DoubleSquareMatrix &linv=(*(my_data->linv))[sent];
L.invert(linv);
}
pthread_exit((void*) 0);
return (void*)0;
}
void FactorAnalysisStat::estimateAndInverseLUnThreaded(){
if (verbose) cout << "(FactorAnalysisStat) Inverse L Matrix ... "<<endl;
unsigned long mk;
DoubleSquareMatrix L(_rang);
L.setAllValues(0.0);
RealVector <double> AUX;
AUX.setSize(_rang);
unsigned long sent=0;
XLine *pline;
String *pFile;
fileList.rewind();
double *N_h=_matN_h.getArray();
double *U=_matU.getArray();
double *LV=L.getArray();
double *super_invvar=_super_invvar.getArray();
while((pline=fileList.getLine())!=NULL) {
while((pFile=pline->getElement())!=NULL) {
L.setAllValues(0.0);
AUX.setAllValues(0.0);
for(unsigned long i=0;i<_rang;i++){
for(unsigned long j=0;j<=i;j++){
for(unsigned long k=0;k<_supervsize;k++){
mk=k/_vsize;
LV[i*_rang+j]+=N_h[sent*_mixsize+mk]*super_invvar[k]*U[k*_rang+i]*U[k*_rang+j];
}
}
}
for(unsigned long i=0;i<_rang;i++)
for(unsigned long j=i+1;j<_rang;j++)
LV[i*_rang+j]=LV[j*_rang+i];
for(unsigned long i=0;i<_rang;i++)
LV[i*_rang+i]+=1.0;
L.invert(_l_h_inv[sent]);
sent++;
}
}
};
// Compute supervector of client M_s_h=M+Dy_s
void FactorAnalysisStat::getMplusDY(RealVector <double> &Sp, String& file) {
Sp.setAllValues(0.0);
unsigned long loc=_ndxTable.locNb(file);
for (unsigned long i=0;i<_supervsize;i++)
Sp[i]=_super_mean[i]+_D[i]*_matY(loc,i);
};
void FactorAnalysisStat::getUEstimateUnThreaded(){
if (verbose) cout << "(FactorAnalysisStat) Compute U Estimate "<<endl;
DoubleSquareMatrix L(_rang);
DoubleSquareMatrix L_Inv(_rang);
RealVector <double> R;
R.setSize(_rang);
double *N_h=_matN_h.getArray();
double *X=_matX.getArray();
double *S_X_h=_matS_X_h.getArray();
double *U=_matU.getArray();
double *RV=R.getArray();
double *LV=L.getArray();
/*for(i=0;i<_supervsize;i++){
unsigned long im=i/_vsize;
L.setAllValues(0.0);
R.setAllValues(0.0);
for(j=0;j<_nb_sent;j++){
double *l_h_inv=_l_h_inv[j].getArray();
for(k=0;k<_rang;k++){
for(l=0;l<_rang;l++)
LV[k*_rang+l]+=(l_h_inv[k*_rang+l]+X[j*_rang+k]*X[j*_rang+l])*N_h[j*_mixsize+im];
RV[k]+=S_X_h[j*_supervsize+i]*X[j*_rang+k];
}
}
L.invert(L_Inv);
double *L_InvV=L_Inv.getArray();
for(j=0;j<_rang;j++)
U[i*_rang+j]=0.0;
for(j=0;j<_rang;j++)
for(k=0;k<_rang;k++)
U[i*_rang+j]+=L_InvV[j*_rang+k]*RV[k];
}*/
_matU.setAllValues(0.0);
for(unsigned long g=0;g<_mixsize;g++){
L.setAllValues(0.0);
// Estimate LU for the gaussian g
for(unsigned long j=0;j<_nb_sent;j++){
double *l_h_inv=_l_h_inv[j].getArray();
for(unsigned long k=0;k<_rang;k++)
for(unsigned long l=0;l<_rang;l++)
LV[k*_rang+l]+=(l_h_inv[k*_rang+l]+X[j*_rang+k]*X[j*_rang+l])*N_h[j*_mixsize+g];
}
L.invert(L_Inv);
double *L_InvV=L_Inv.getArray();
// Estimate LU for the line lineNum
for (unsigned long i=0;i<_vsize;i++) {
unsigned long lineNum=_vsize*g+i;
// estime RU i
R.setAllValues(0.0);
for(unsigned long j=0;j<_nb_sent;j++)
for(unsigned long k=0;k<_rang;k++)
RV[k]+=S_X_h[j*_supervsize+lineNum]*X[j*_rang+k];
// estime U i
for(unsigned long j=0;j<_rang;j++)
for(unsigned long k=0;k<_rang;k++)
U[lineNum*_rang+j]+=L_InvV[j*_rang+k]*RV[k];
}
}
};