void PairRegressionAnalyzer::printResults(QTableWidget * table) {
table->setColumnCount(results.count());
table->setRowCount(results[0].count());
table->setHorizontalHeaderItem(0,new QTableWidgetItem("x"));
table->setHorizontalHeaderItem(1,new QTableWidgetItem("y"));
table->setHorizontalHeaderItem(2,new QTableWidgetItem("y''"));
for(int col=0;col<results.count();col++)
for(int row=0;row<results[col].count();row++)
table->setItem(row,col,new QTableWidgetItem(QString::number(results[col][row])));
Point3D coords;
coords.x = 5.0f;
coords.y = 5.0f;
coords.z = 5.0f;
Point3D coordsScale;
coordsScale.x = 5.0/maxElement(results[0]);
coordsScale.y = 5.0/maxElement(results[1]);
coordsScale.z = 1;
QList<QString> coordLables;
QWidget * tab1 = AdditionalWidgets.at(0);
tab1->setObjectName("График");
PairRegressionAnalyzerGraphic * g1 = new PairRegressionAnalyzerGraphic(tab1);
coordLables.append("");
coordLables.append("");
g1->SetCoordsData(coords, coordLables,Figure3D::black, Figure3D::darkGreen, &coordsScale);
g1->SetPoints(getYPoints());
g1->SetLinePoints(getY2Points());
g1->SetErrorText("Качество оценивания: " + QString::number(R));
g1->SetEquation("y'' = " + QString::number(A) + " + " + QString::number(B) + "x");
tab1->setLayout(new QGridLayout());
tab1->layout()->addWidget(g1);
}
QList<Point3D> PairRegressionAnalyzer::getY2Points() {
double xScale = 5.0/maxElement(results[0]);
double yScale = 5.0/maxElement(results[1]);
QList<Point3D> result;
for (int i=0;i<results[0].size();i++) {
Point3D p;
p.x = results[0][i]*xScale;
p.y = results[2][i]*yScale;
result.append(p);
}
return result;
}
QList<Point3DEx> PairRegressionAnalyzer::getYPoints() {
double xScale = 5.0/maxElement(results[0]);
double yScale = 5.0/maxElement(results[1]);
QList<Point3DEx> result;
for (int i=0;i<results[0].size(); i++) {
Point3DEx p;
p.x = results[0][i]*xScale;
p.y = results[1][i]*yScale;
p.label = QString::number(i+1);
p.color = Figure3D::red;
result.append(p);
}
return result;
}
void setHilbertParams(Parameters ðer, Aux &aux,Geometry const &geometry)
{
int n=geometry.volume(), d=geometry.dim();
int i;
ether.typeofmodel="MODEL_KONDO_DMS_ZINCBLENDE";
ether.hilbertSize=4*n;
ether.nonzero= ether.numberOfOrbitals*(1+ether.numberOfOrbitals*geometry.z(0)) * n+
ether.numberOfOrbitals*n*0.5*(ether.numberOfOrbitals-1);
if (!(geometry.latticeName()=="zincblende")) {
cerr<<"I was expecting zincblende geometry but instead you input "<<geometry.latticeName()<<endl;
cerr<<"At this point: "<<__FILE__<<" "<<__LINE__<<endl;
exit(1);
}
cerr<<ether.bandHoppings.size()<<endl;
vectorPrint(ether.bandHoppings,"hoppings=",cerr);
ether.energy1= -3-maxElement(ether.J);
ether.energy2= -ether.energy1;
aux.varTpem_a = 0.5*(ether.energy2-ether.energy1);
aux.varTpem_b = 0.5*(ether.energy2+ether.energy1);
ether.classFieldList.push_back(0);
}
void setHilbertParams(Parameters ðer, Aux &aux,Geometry const &geometry)
{
int n=geometry.volume(), d=geometry.dim();
ether.typeofmodel="MODEL_KONDO_INF_TWOBANDS";
ether.hilbertSize=2*n;
ether.nonzero= 4 * (2*d + 1) * n;
if (!ether.isSet("spectrumbounds")) {
ether.energy1= -2*d*maxElement(ether.bandHoppings)-maxElement(ether.potential);
ether.energy2= -ether.energy1;
}
aux.varTpem_a = 1; //0.5*(ether.energy2-ether.energy1);
aux.varTpem_b = 0; //0.5*(ether.energy2+ether.energy1);
ether.classFieldList.push_back(0);
ether.classFieldList.push_back(1);
}
void decompose( const Matnnt<3,float> &mat, Quatt<float> &orientation, Vecnt<3,float> &scaling
, Quatt<float> &scaleOrientation )
{
#if 0
//NVSG_PRIVATE_ASSERT( std::numeric_limits<float>::epsilon() < abs( determinant( mat ) ) );
Matnnt<3,float> rot, sca;
float det = _polarDecomposition( mat, rot, sca );
#if !defined(NDEBUG)
{
//NVSG_PRIVATE_ASSERT( isRotation( rot, 3*std::numeric_limits<float>::epsilon() ) );
Matnnt<3,float> diff = mat - (float)sign(det) * sca * rot;
float eps = std::max( 1.0f, maxElement( sca ) ) * std::numeric_limits<float>::epsilon();
//NVSG_PRIVATE_ASSERT( isNull( diff, 4*eps ) );
}
#endif
orientation = Quatt<float>(rot);
// get the scaling out of sca
Matnnt<3,float> so;
scaling = (float)sign(det) * _spectralDecomposition( sca, so );
#if !defined( NDEBUG )
{
//NVSG_PRIVATE_ASSERT( isRotation( so, 3*std::numeric_limits<float>::epsilon() ) );
Matnnt<3,float> k( scaling[0], 0, 0, 0, scaling[1], 0, 0, 0, scaling[2] );
Matnnt<3,float> diff = sca - ~so * k * so;
float eps = std::max( 1.0f, maxElement( scaling ) ) * std::numeric_limits<float>::epsilon();
//NVSG_PRIVATE_ASSERT( isNull( diff, 4*eps ) );
}
#endif
scaleOrientation = Quatt<float>( so );
#if !defined( NDEBUG )
{
Matnnt<3,float> ms( scaling[0], 0, 0, 0, scaling[1], 0, 0, 0, scaling[2] );
Matnnt<3,float> mso( so );
Matnnt<3,float> diff = mat - ~mso * ms * mso * rot;
float eps = std::max( 1.0f, maxElement( scaling ) ) * std::numeric_limits<float>::epsilon();
//NVSG_PRIVATE_ASSERT( isNull( diff, 5*eps ) );
}
#endif
#else
Matnnt<3,double> rot, sca;
double det = _polarDecomposition( Matnnt<3,double>(mat), rot, sca );
#if !defined(NDEBUG)
{
//NVSG_PRIVATE_ASSERT( isRotation<double>( rot, std::numeric_limits<float>::epsilon() ) );
Matnnt<3,double> diff = Matnnt<3,double>(mat) - sca * rot;
double eps = std::max( 1.0, maxElement( sca ) ) * std::numeric_limits<float>::epsilon();
//NVSG_PRIVATE_ASSERT( isNull( diff, eps ) );
}
#endif
orientation = Quatt<float>(Quatt<double>(rot));
// get the scaling out of sca
Matnnt<3,double> so;
if( fabs(det) > FLT_EPSILON )
{
scaling = (double)sign(det) * _spectralDecomposition( sca, so );
scaleOrientation = Quatt<float>(Quatt<double>( so ));
}
else
{
scaling = Vec3f(0.0f, 0.0f, 0.0f);
scaleOrientation = Quatf( Vec3f(0.0f, 0.0f, 1.0f), 0.0f );
}
#endif
}
void LinearRegressionAnalyzer::DoAnalyze() {
BaseAnalyzer::DoAnalyze();
QList<double> yList = matrix[0];
QList<QList<double> > xMatrix;
for (int i=1;i<matrix.size();i++) {
xMatrix.append(matrix[i]);
}
QList<QList<double> > xNMatrix;
for (int i=0;i<xMatrix.size();i++) {
QList<double> xNiMatrix;
double avg = average(xMatrix[i]);
QList<double> razn;
for (int j=0;j<xMatrix[i].size();j++) {
razn.append(fabs(xMatrix[i][j] - avg));
}
double R = maxElement(razn);
for (int j=0;j<xMatrix[i].size();j++)
xNiMatrix.append((xMatrix[i][j] - avg)/R);
xNMatrix.append(xNiMatrix);
}
QList<double> bMatrix;
double temp = 0.0;
for (int i=0;i<yList.size();i++)
temp += yList[i];
bMatrix.append(temp);
for (int i=0;i<xNMatrix.size();i++) {
temp = 0.0;
for (int j=0;j<xNMatrix[i].size();j++) {
temp += yList[j] * xNMatrix[i][j];
}
bMatrix.append(temp);
}
QList<QList<double> > aMatrix;
QList<double> firstRow;
firstRow.append(yList.size());
for (int i=0;i<xNMatrix.size();i++)
firstRow.append(sumElements(xNMatrix[i]));
aMatrix.append(firstRow);
for (int row=0;row<xNMatrix.size();row++) {
QList<double> tempRow;
for (int col=0;col<bMatrix.size();col++) {
if (col<=row) {
tempRow.append(0.0);
}
else {
if (col>0) {
tempRow.append(sumListsElements(xNMatrix[col-1], xNMatrix[row]));
}
}
}
aMatrix.append(tempRow);
}
for (int row = 0;row<aMatrix.size();row++) {
for (int col = 0; col < aMatrix[row].size();col++) {
if (row <= col)
continue;
aMatrix[row][col] = aMatrix[col][row];
}
}
results = Gauss(aMatrix, bMatrix);
QList<double> y2List;
for (int i=0;i<xNMatrix[0].size();i++) {
temp = 0.0;
for (int j= 0;j<results.size();j++) {
if (j<results.size()-1)
temp += results[j] * xNMatrix[j][i];
else
temp += results[j];
}
y2List.append(temp);
}
double y2Avg = average(y2List);
double yAvg = average(yList);
double RUp = 0.0, RDown = 0.0;
for (int i=0;i<yList.size();i++) {
RUp += (y2List[i]-y2Avg)*(y2List[i]-y2Avg);
RDown += (yList[i] - yAvg)*(yList[i] - yAvg);
}
R2 = RUp/RDown;
}
