33 for (
int i = 0; i <
n; ++i) {
37 v[i] =
sin(x[i] ) +
cos(y[i]) + z[i] + r.
Gaus(0,ev);
43 for(
int i = 0; i <
n; ++i) {
48 data.Add(xx, v[i], ev);
51 TF3 * f3 =
new TF3(
"f3",
"[0] * sin(x) + [1] * cos(y) + [2] * z",0,10,0,10,0,10);
66 double prob = res.
Prob();
68 Error(
"exampleFit3D",
"Bad data fit - fit p-value is %f",prob);
70 std::cout <<
"Good fit : p-value = " << prob << std::endl;
74 Error(
"exampleFit3D",
"3D fit failed");
virtual void SetParameters(const Double_t *params)
virtual Double_t Gaus(Double_t mean=0, Double_t sigma=1)
Samples a random number from the standard Normal (Gaussian) Distribution with the given mean and sigm...
Class to Wrap a ROOT Function class (like TF1) in a IParamMultiFunction interface of multi-dimensions...
Random number generator class based on the maximally quidistributed combined Tausworthe generator by ...
double Prob() const
p value of the fit (chi2 probability)
const FitResult & Result() const
get fit result
void Error(const char *location, const char *msgfmt,...)
bool Fit(const Data &data, const Function &func)
fit a data set using any generic model function If data set is binned a least square fit is performed...
A 3-Dim function with parameters.
Fitter class, entry point for performing all type of fits.
Class describing the binned data sets : vectors of x coordinates, y values and optionally error on y ...
void SetFunction(const IModelFunction &func, bool useGradient=false)
Set the fitted function (model function) from a parametric function interface.
class containg the result of the fit and all the related information (fitted parameter values...
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
you should not use this method at all Int_t Int_t z
void Print(std::ostream &os, bool covmat=false) const
print the result and optionaly covariance matrix and correlations
virtual void SetFitResult(const ROOT::Fit::FitResult &result, const Int_t *indpar=0)
Set the result from the fit parameter values, errors, chi2, etc...