ROOT   Reference Guide
rf303_conditional.C
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1/// \file
2/// \ingroup tutorial_roofit
3/// \notebook -js
4///
5/// Multidimensional models: use of tailored p.d.f as conditional p.d.fs.s
6///
7/// pdf = gauss(x,f(y),sx | y ) with f(y) = a0 + a1*y
8///
9/// \macro_image
10/// \macro_output
11/// \macro_code
12///
13/// \date 07/2008
14/// \author Wouter Verkerke
15
16#include "RooRealVar.h"
17#include "RooDataSet.h"
18#include "RooDataHist.h"
19#include "RooGaussian.h"
20#include "RooPolyVar.h"
21#include "RooProdPdf.h"
22#include "RooPlot.h"
23#include "TRandom.h"
24#include "TCanvas.h"
25#include "TAxis.h"
26#include "TH1.h"
27
28using namespace RooFit;
29
30RooDataSet *makeFakeDataXY();
31
32void rf303_conditional()
33{
34 // S e t u p c o m p o s e d m o d e l g a u s s ( x , m ( y ) , s )
35 // -----------------------------------------------------------------------
36
37 // Create observables
38 RooRealVar x("x", "x", -10, 10);
39 RooRealVar y("y", "y", -10, 10);
40
41 // Create function f(y) = a0 + a1*y
42 RooRealVar a0("a0", "a0", -0.5, -5, 5);
43 RooRealVar a1("a1", "a1", -0.5, -1, 1);
44 RooPolyVar fy("fy", "fy", y, RooArgSet(a0, a1));
45
46 // Create gauss(x,f(y),s)
47 RooRealVar sigma("sigma", "width of gaussian", 0.5, 0.1, 2.0);
48 RooGaussian model("model", "Gaussian with shifting mean", x, fy, sigma);
49
50 // Obtain fake external experimental dataset with values for x and y
51 RooDataSet *expDataXY = makeFakeDataXY();
52
53 // G e n e r a t e d a t a f r o m c o n d i t i o n a l p . d . f m o d e l ( x | y )
54 // ---------------------------------------------------------------------------------------------
55
56 // Make subset of experimental data with only y values
57 RooDataSet *expDataY = (RooDataSet *)expDataXY->reduce(y);
58
59 // Generate 10000 events in x obtained from _conditional_ model(x|y) with y values taken from experimental data
60 RooDataSet *data = model.generate(x, ProtoData(*expDataY));
61 data->Print();
62
63 // F i t c o n d i t i o n a l p . d . f m o d e l ( x | y ) t o d a t a
64 // ---------------------------------------------------------------------------------------------
65
66 model.fitTo(*expDataXY, ConditionalObservables(y));
67
68 // P r o j e c t c o n d i t i o n a l p . d . f o n x a n d y d i m e n s i o n s
69 // ---------------------------------------------------------------------------------------------
70
71 // Plot x distribution of data and projection of model on x = 1/Ndata sum(data(y_i)) model(x;y_i)
72 RooPlot *xframe = x.frame();
73 expDataXY->plotOn(xframe);
74 model.plotOn(xframe, ProjWData(*expDataY));
75
76 // Speed up (and approximate) projection by using binned clone of data for projection
77 RooAbsData *binnedDataY = expDataY->binnedClone();
78 model.plotOn(xframe, ProjWData(*binnedDataY), LineColor(kCyan), LineStyle(kDotted));
79
80 // Show effect of projection with too coarse binning
81 ((RooRealVar *)expDataY->get()->find("y"))->setBins(5);
82 RooAbsData *binnedDataY2 = expDataY->binnedClone();
83 model.plotOn(xframe, ProjWData(*binnedDataY2), LineColor(kRed));
84
85 // Make canvas and draw RooPlots
86 new TCanvas("rf303_conditional", "rf303_conditional", 600, 460);
88 xframe->GetYaxis()->SetTitleOffset(1.2);
89 xframe->Draw();
90}
91
92RooDataSet *makeFakeDataXY()
93{
94 RooRealVar x("x", "x", -10, 10);
95 RooRealVar y("y", "y", -10, 10);
96 RooArgSet coord(x, y);
97
98 RooDataSet *d = new RooDataSet("d", "d", RooArgSet(x, y));
99
100 for (int i = 0; i < 10000; i++) {
101 Double_t tmpy = gRandom->Gaus(0, 10);
102 Double_t tmpx = gRandom->Gaus(0.5 * tmpy, 1);
103 if (fabs(tmpy) < 10 && fabs(tmpx) < 10) {
104 x = tmpx;
105 y = tmpy;
107 }
108 }
109
110 return d;
111}
#define d(i)
Definition: RSha256.hxx:102
@ kRed
Definition: Rtypes.h:64
@ kCyan
Definition: Rtypes.h:64
@ kDotted
Definition: TAttLine.h:48
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
RooAbsArg * find(const char *name) const
Find object with given name in list.
RooAbsData is the common abstract base class for binned and unbinned datasets.
Definition: RooAbsData.h:44
RooAbsData * reduce(const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg(), const RooCmdArg &arg3=RooCmdArg(), const RooCmdArg &arg4=RooCmdArg(), const RooCmdArg &arg5=RooCmdArg(), const RooCmdArg &arg6=RooCmdArg(), const RooCmdArg &arg7=RooCmdArg(), const RooCmdArg &arg8=RooCmdArg())
Create a reduced copy of this dataset.
Definition: RooAbsData.cxx:381
virtual void Print(Option_t *options=0) const
Print TNamed name and title.
Definition: RooAbsData.h:175
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
Calls RooPlot* plotOn(RooPlot* frame, const RooLinkedList& cmdList) const ;.
Definition: RooAbsData.cxx:546
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
virtual RooPlot * plotOn(RooPlot *frame, PlotOpt o) const
Back end function to plotting functionality.
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
virtual const RooArgSet * get(Int_t index) const override
Return RooArgSet with coordinates of event 'index'.
RooDataHist * binnedClone(const char *newName=0, const char *newTitle=0) const
Return binned clone of this dataset.
Definition: RooDataSet.cxx:951
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
A RooPlot is a plot frame and a container for graphics objects within that frame.
Definition: RooPlot.h:44
TAxis * GetYaxis() const
Definition: RooPlot.cxx:1277
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:712
Class RooPolyVar is a RooAbsReal implementing a polynomial in terms of a list of RooAbsReal coefficie...
Definition: RooPolyVar.h:28
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:35
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:294
The Canvas class.
Definition: TCanvas.h:27
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...
Definition: TRandom.cxx:263
RooCmdArg ConditionalObservables(const RooArgSet &set)
RooCmdArg ProtoData(const RooDataSet &protoData, Bool_t randomizeOrder=kFALSE, Bool_t resample=kFALSE)
RooCmdArg ProjWData(const RooAbsData &projData, Bool_t binData=kFALSE)
RooCmdArg LineColor(Color_t color)
RooCmdArg LineStyle(Style_t style)
const Double_t sigma
Double_t y[n]
Definition: legend1.C:17
Double_t x[n]
Definition: legend1.C:17
VecExpr< UnaryOp< Fabs< T >, VecExpr< A, T, D >, T >, T, D > fabs(const VecExpr< A, T, D > &rhs)
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...