本文整理汇总了C++中TVectorD::Print方法的典型用法代码示例。如果您正苦于以下问题：C++ TVectorD::Print方法的具体用法？C++ TVectorD::Print怎么用？C++ TVectorD::Print使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类TVectorD的用法示例。
在下文中一共展示了TVectorD::Print方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: dumpElements
void dumpElements(TVectorD& a)
{
cout << endl << endl;
a.Print();
cout << endl << endl;
return;
}示例2: operator
double operator() (double *x, double *p) {
// 4 parameters
int dim = X.GetNrows();
int k = 0;
for (int i = 0; i<dim; ++i) { X[i] = x[i] - p[k]; k++; }
for (int i = 0; i<dim; ++i) {
CovMat(i,i) = p[k]*p[k];
k++;
}
for (int i = 0; i<dim; ++i) {
for (int j = i+1; j<dim; ++j) {
// p now are the correlations N(N-1)/2
CovMat(i,j) = p[k]*sqrt(CovMat(i,i)*CovMat(j,j));
CovMat(j,i) = CovMat(i,j);
k++;
}
}
if (debug) {
X.Print();
CovMat.Print();
}
double det = CovMat.Determinant();
if (det <= 0) {
Fatal("GausND","Determinant is <= 0 det = %f",det);
CovMat.Print();
return 0;
}
double norm = std::pow( 2. * TMath::Pi(), dim/2) * sqrt(det);
// compute the gaussians
CovMat.Invert();
double fval = std::exp( - 0.5 * CovMat.Similarity(X) )/ norm;
if (debug) {
std::cout << "det " << det << std::endl;
std::cout << "norm " << norm << std::endl;
std::cout << "fval " << fval << std::endl;
}
return fval;
}示例3: ratioPlots_Zxx
//.........这里部分代码省略.........
c1->cd();
TPad *pad2 = new TPad("pad2","pad2",0,0,1,0.5);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.4);
pad2->Draw();
pad2->cd();
pad2->SetGrid();
h2->SetStats(0);
h2->Divide(h1);
//h2->SetMarkerStyle(21);
h2->Draw("ep");
h2->GetYaxis()->SetLabelSize(0.1);
h2->GetYaxis()->SetRangeUser(-0.5, 2.5);// ,yTopLimit);
h2->GetYaxis()->SetTitle("[email protected]+PY8 / MG5+PY6");
h2->GetYaxis()->SetTitleSize(0.06);
h2->GetYaxis()->SetTitleOffset(0.7);
h2->GetXaxis()->SetLabelSize(0.1);
h2->GetXaxis()->SetTitle(x_title);
h2->GetXaxis()->SetTitleSize(0.16);
h2->GetXaxis()->SetTitleOffset(0.9);
// Double_t matrix[4][4];
h2->Fit("pol3","","",50.0,1200.0);
TF1 *ratio = h2->GetFunction("pol3");
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
TMatrixD matrix(4,4,fitter->GetCovarianceMatrix());
Double_t errorPar00 = fitter->GetCovarianceMatrixElement(0,0);
Double_t errorPar11 = fitter->GetCovarianceMatrixElement(1,1);
Double_t errorPar22 = fitter->GetCovarianceMatrixElement(2,2);
Double_t errorPar33 = fitter->GetCovarianceMatrixElement(3,3);
// c1->cd();
matrix.Print();
//const TMatrixDSym m = matrix;
const TMatrixDEigen eigen(matrix);
const TMatrixD eigenVal = eigen.GetEigenValues();
const TMatrixD V = eigen.GetEigenVectors();
cout << "V" << endl;
V.Print();
cout << "eigenVal" << endl;
eigenVal.Print();
cout << "Recomputed diag" << endl;
//const TMatrixD Vt(TMatrixD::kTransposed,V);
//const TMatrixD Vinv = V.Invert();
const TMatrixD Vt(TMatrixD::kTransposed,V);
//cout << "V-1" << endl;
//Vinv.Print();
cout << "Vt" << endl;
Vt.Print();
const TMatrixD VAVt = Vt*matrix*V;
VAVt.Print();
const TVectorD FittedParam(4);
FittedParam(0) = fitter->GetParameter(0);