37 xvalues1[i] =
r.Uniform(0.1, 5);
38 xvalues2[i] =
r.Uniform(3, 8);
39 xvalues3[i] =
r.Uniform(9, 15);
40 yvalues1[i] = 3 + 2*xvalues1[i] + xvalues1[i]*xvalues1[i] +
r.Gaus();
41 yvalues2[i] = 3 + 2*xvalues2[i] + xvalues2[i]*xvalues2[i] +
r.Gaus()*10;
45 yvalues3[i] = 3 + 2*xvalues3[i] + xvalues3[i]*xvalues3[i] +
r.Gaus()*20;
62 "TMultiGraph of 3 TGraphErrors");
68 "Fitting a MultiGraph of 3 TGraphErrors");
100 for (i=0; i<
n; i++) {
101 xvalues1[i] =
r.Uniform(-3, -1);
102 xvalues2[i] =
r.Uniform(-1, 1);
103 xvalues3[i] =
r.Uniform(1, 3);
106 evalues1[i] = 0.00001;
107 evalues2[i] = 0.00001;
108 evalues3[i] = 0.00001;
112 {xtotal[i]=xvalues1[i]; ytotal[i]=yvalues1[i]; etotal[i]=0.00001;}
113 for (i=
n; i<2*
n; i++)
114 {xtotal[i] = xvalues2[i-
n]; ytotal[i]=yvalues2[i-
n]; etotal[i]=0.00001;}
115 for (i=2*
n; i<3*
n; i++)
116 {xtotal[i] = xvalues3[i-2*
n]; ytotal[i]=yvalues3[i-2*
n]; etotal[i]=0.00001;}
132 grtotal->
Fit(
"gaus");
virtual void SetLineWidth(Width_t lwidth)
Set the line width.
virtual void SetLineColor(Color_t lcolor)
Set the line color.
virtual void SetMarkerStyle(Style_t mstyle=1)
Set the marker style.
virtual void SetMarkerSize(Size_t msize=1)
Set the marker size.
A TGraphErrors is a TGraph with error bars.
virtual TFitResultPtr Fit(const char *formula, Option_t *option="", Option_t *goption="", Axis_t xmin=0, Axis_t xmax=0)
Fit this graph with function with name fname.
A TMultiGraph is a collection of TGraph (or derived) objects.
virtual TFitResultPtr Fit(const char *formula, Option_t *option="", Option_t *goption="", Axis_t xmin=0, Axis_t xmax=0)
Fit this graph with function with name fname.
virtual void Add(TGraph *graph, Option_t *chopt="")
Add a new graph to the list of graphs.
TF1 * GetFunction(const char *name) const
Return pointer to function with name.
virtual void Draw(Option_t *chopt="")
Draw this multigraph with its current attributes.
void SetGrid(Int_t valuex=1, Int_t valuey=1) override
This is the base class for the ROOT Random number generators.
Double_t Gaus(Double_t x, Double_t mean=0, Double_t sigma=1, Bool_t norm=kFALSE)
Calculate a gaussian function with mean and sigma.