# Rf 1 0 7_Plotstyles¶

Basic functionality: various plotting styles of data, functions in a RooPlot

Author: Wouter Verkerke
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Saturday, November 28, 2020 at 10:37 AM.

In [1]:
%%cpp -d
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"

In [2]:
%%cpp -d
// This is a workaround to make sure the namespace is used inside functions
using namespace RooFit;


## Setup model¶

Create observables

In [3]:
RooRealVar x("x", "x", -10, 10);

RooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University



Create gaussian

In [4]:
RooRealVar sigma("sigma", "sigma", 3, 0.1, 10);
RooRealVar mean("mean", "mean", -3, -10, 10);
RooGaussian gauss("gauss", "gauss", x, mean, sigma);


Generate a sample of 100 events with sigma=3

In [5]:
RooDataSet *data = gauss.generate(x, 100);


Fit pdf to data

In [6]:
gauss.fitTo(*data);

[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
**********
**    1 **SET PRINT           1
**********
**********
**********
PARAMETER DEFINITIONS:
NO.   NAME         VALUE      STEP SIZE      LIMITS
1 mean        -3.00000e+00  2.00000e+00   -1.00000e+01  1.00000e+01
2 sigma        3.00000e+00  9.90000e-01    1.00000e-01  1.00000e+01
**********
**    3 **SET ERR         0.5
**********
**********
**    4 **SET PRINT           1
**********
**********
**    5 **SET STR           1
**********
NOW USING STRATEGY  1: TRY TO BALANCE SPEED AGAINST RELIABILITY
**********
**********
FIRST CALL TO USER FUNCTION AT NEW START POINT, WITH IFLAG=4.
START MIGRAD MINIMIZATION.  STRATEGY  1.  CONVERGENCE WHEN EDM .LT. 1.00e-03
FCN=244.778 FROM MIGRAD    STATUS=INITIATE        6 CALLS           7 TOTAL
EDM= unknown      STRATEGY= 1      NO ERROR MATRIX
EXT PARAMETER               CURRENT GUESS       STEP         FIRST
NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE
1  mean        -3.00000e+00   2.00000e+00   2.11716e-01   7.88402e+00
2  sigma        3.00000e+00   9.90000e-01   2.22742e-01   8.68850e+00
ERR DEF= 0.5
MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.
COVARIANCE MATRIX CALCULATED SUCCESSFULLY
FCN=244.648 FROM MIGRAD    STATUS=CONVERGED      27 CALLS          28 TOTAL
EDM=6.12289e-07    STRATEGY= 1      ERROR MATRIX ACCURATE
EXT PARAMETER                                   STEP         FIRST
NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE
1  mean        -3.06106e+00   3.00167e-01   3.38614e-04  -1.01280e-02
2  sigma        2.89572e+00   2.28664e-01   5.51106e-04   1.31676e-02
ERR DEF= 0.5
EXTERNAL ERROR MATRIX.    NDIM=  25    NPAR=  2    ERR DEF=0.5
9.013e-02 -8.498e-03
-8.498e-03  5.233e-02
PARAMETER  CORRELATION COEFFICIENTS
NO.  GLOBAL      1      2
1  0.12374   1.000 -0.124
2  0.12374  -0.124  1.000
**********
**    7 **SET ERR         0.5
**********
**********
**    8 **SET PRINT           1
**********
**********
**    9 **HESSE        1000
**********
COVARIANCE MATRIX CALCULATED SUCCESSFULLY
FCN=244.648 FROM HESSE     STATUS=OK             10 CALLS          38 TOTAL
EDM=6.13161e-07    STRATEGY= 1      ERROR MATRIX ACCURATE
EXT PARAMETER                                INTERNAL      INTERNAL
NO.   NAME      VALUE            ERROR       STEP SIZE       VALUE
1  mean        -3.06106e+00   3.00196e-01   6.77227e-05  -3.11100e-01
2  sigma        2.89572e+00   2.28685e-01   1.10221e-04  -4.50268e-01
ERR DEF= 0.5
EXTERNAL ERROR MATRIX.    NDIM=  25    NPAR=  2    ERR DEF=0.5
9.015e-02 -8.552e-03
-8.552e-03  5.234e-02
PARAMETER  CORRELATION COEFFICIENTS
NO.  GLOBAL      1      2
1  0.12449   1.000 -0.124
2  0.12449  -0.124  1.000
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization


## Make plot frames¶

Make four plot frames to demonstrate various plotting features

In [7]:
RooPlot *frame1 = x.frame(Name("xframe"), Title("Red Curve / SumW2 Histo errors"), Bins(20));
RooPlot *frame2 = x.frame(Name("xframe"), Title("Dashed Curve / No XError bars"), Bins(20));
RooPlot *frame3 = x.frame(Name("xframe"), Title("Filled Curve / Blue Histo"), Bins(20));
RooPlot *frame4 = x.frame(Name("xframe"), Title("Partial Range / Filled Bar chart"), Bins(20));


## Data plotting styles¶

Use sqrt(sum(weights^2)) error instead of poisson errors

In [8]:
data->plotOn(frame1, DataError(RooAbsData::SumW2));


Remove horizontal error bars

In [9]:
data->plotOn(frame2, XErrorSize(0));


Blue markers and error bors

In [10]:
data->plotOn(frame3, MarkerColor(kBlue), LineColor(kBlue));


Filled bar chart

In [11]:
data->plotOn(frame4, DrawOption("B"), DataError(RooAbsData::None), XErrorSize(0), FillColor(kGray));


## Function plotting styles¶

Change line color to red

In [12]:
gauss.plotOn(frame1, LineColor(kRed));


Change line style to dashed

In [13]:
gauss.plotOn(frame2, LineStyle(kDashed));


Filled shapes in green color

In [14]:
gauss.plotOn(frame3, DrawOption("F"), FillColor(kOrange), MoveToBack());

In [15]:
gauss.plotOn(frame4, Range(-8, 3), LineColor(kMagenta));

TCanvas *c = new TCanvas("rf107_plotstyles", "rf107_plotstyles", 800, 800);
c->Divide(2, 2);
c->cd(1);
frame1->GetYaxis()->SetTitleOffset(1.6);
frame1->Draw();
c->cd(2);
frame2->GetYaxis()->SetTitleOffset(1.6);
frame2->Draw();
c->cd(3);
frame3->GetYaxis()->SetTitleOffset(1.6);
frame3->Draw();
c->cd(4);

[#1] INFO:Plotting -- RooAbsPdf::plotOn(gauss) only plotting range [-8,3], curve is normalized to data in given range

%jsroot on