34double f(
double * 
x, 
double * p) {
 
   41   fitFunc = 
new TF1(
"f",
f,0,1,NPAR);
 
   44   double  par[NPAR] = { 3.14, 1.};
 
   54   double integral = fitFunc->
Integral(0,1);
 
   63   std::cout << 
"Integral = " << integral << 
" +/- " << sigma_integral
 
   69   double ic  = p[1]* (1-
std::cos(p[0]) )/p[0];
 
   71   double c1c = (1-
std::cos(p[0]) )/p[0];
 
   74   double sic = 
std::sqrt( c0c*c0c * covMatrix[0] + c1c*c1c * covMatrix[3]
 
   75      + 2.* c0c*c1c * covMatrix[1]);
 
   77   if ( 
std::fabs(sigma_integral-sic) > 1.E-6*sic )
 
   78      std::cout << 
" ERROR: test failed : different analytical  integral : " 
   79                << ic << 
" +/- " << sic << std::endl;
 
virtual Double_t Integral(Double_t a, Double_t b, Double_t epsrel=1.e-12)
IntegralOneDim or analytical integral.
virtual Double_t * GetParameters() const
virtual void SetParameters(const Double_t *params)
virtual void SetParameter(Int_t param, Double_t value)
virtual Double_t IntegralError(Double_t a, Double_t b, const Double_t *params=0, const Double_t *covmat=0, Double_t epsilon=1.E-2)
Return Error on Integral of a parametric function between a and b due to the parameter uncertainties.
1-D histogram with a double per channel (see TH1 documentation)}
virtual void FillRandom(const char *fname, Int_t ntimes=5000)
Fill histogram following distribution in function fname.
virtual TFitResultPtr Fit(const char *formula, Option_t *option="", Option_t *goption="", Double_t xmin=0, Double_t xmax=0)
Fit histogram with function fname.
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Abstract Base Class for Fitting.
virtual Double_t * GetCovarianceMatrix() const =0
static TVirtualFitter * GetFitter()
static: return the current Fitter
VecExpr< UnaryOp< Fabs< T >, VecExpr< A, T, D >, T >, T, D > fabs(const VecExpr< A, T, D > &rhs)