RecoTracker
DeDx
interface
UnbinnedLikelihoodFit.h
Go to the documentation of this file.
1
#ifndef __UnbinnedLikelihoodFit_h_
2
#define __UnbinnedLikelihoodFit_h_
3
#include <TObject.h>
4
#include <TF1.h>
5
#include <TVirtualFitter.h>
6
#include <cstdint>
7
8
// a class to perform a likelihood fit
9
// Author: Christophe Delaere
10
11
/* Example of a Landau fit:
12
* ------------------------
13
* UnbinnedLikelihoodFit myfit;
14
* double x[4] = {89,110,70,80};
15
* myfit.setData(4,x);
16
* TF1* myfunction = new TF1("myLandau","TMath::Landau(x,[0],[1],1)",0,255);
17
* myfunction->SetParameters(100,10);
18
* myfit.setFunction(myfunction);
19
* myfit.fit();
20
* myfit.getFunction()->Print();
21
* double MPV = myfit.getFunction()->GetParameter(0);
22
* double MPVerror = myfit.getFunction()->GetParError(0);
23
*/
24
class
UnbinnedLikelihoodFit
:
public
TObject {
25
public
:
26
// Constructor and destructor
27
UnbinnedLikelihoodFit
();
28
~UnbinnedLikelihoodFit
()
override
;
29
30
// Set the data for the fit: a set of measurements
31
void
setData
(uint32_t
n
,
double
*
x
);
32
33
// Set the fit function
34
void
setFunction
(TF1*
f
);
35
36
// Set the fit options
37
void
setTolerance
(
double
tol) {
tolerance_
= tol; }
38
void
setMaxIterations
(uint32_t
n
) {
maxIterations_
=
n
; }
39
40
// Fit
41
int32_t
fit
(int32_t
verbosity
= -1);
42
int32_t
fit
(int32_t
n
,
double
*
x
, int32_t
verbosity
= -1) {
43
setData
(
n
,
x
);
44
return
fit
(
verbosity
);
45
}
46
47
// Results a retrieved via the TF1
48
TF1*
getFunction
()
const
{
return
function_
; }
49
double
getParameterValue
(uint32_t
i
) {
return
function_
?
function_
->GetParameter(
i
) : 0; }
50
double
getParameterError
(uint32_t
i
) {
return
function_
?
function_
->GetParError(
i
) : 0; }
51
double
*
getParameterValues
() {
return
function_
?
function_
->GetParameters() :
nullptr
; }
52
const
double
*
getParameterErrors
() {
return
function_
?
function_
->GetParErrors() :
nullptr
; }
53
54
private
:
55
// input data
56
uint32_t
datasize_
;
57
double
*
x_
;
58
// the function
59
TF1*
function_
;
60
uint32_t
nparameters_
;
61
// arguments for Minuit methods
62
double
arglist_
[10];
63
uint32_t
maxIterations_
;
64
double
tolerance_
;
65
// the minimizer (minuit)
66
TVirtualFitter*
min
;
67
68
private
:
69
// LL function
70
double
logL
(
const
double
*
x
)
const
;
71
// The function to minimize
72
friend
void
UnbinnedLL
(Int_t& npar, Double_t* gin, Double_t&
val
, Double_t* par, Int_t iflag);
73
};
74
75
#endif
UnbinnedLikelihoodFit::datasize_
uint32_t datasize_
Definition:
UnbinnedLikelihoodFit.h:56
UnbinnedLikelihoodFit::UnbinnedLikelihoodFit
UnbinnedLikelihoodFit()
Definition:
UnbinnedLikelihoodFit.cc:30
HIPAlignmentAlgorithm_cfi.verbosity
verbosity
Definition:
HIPAlignmentAlgorithm_cfi.py:7
mps_fire.i
i
Definition:
mps_fire.py:428
UnbinnedLikelihoodFit::~UnbinnedLikelihoodFit
~UnbinnedLikelihoodFit() override
Definition:
UnbinnedLikelihoodFit.cc:40
dqmiodumpmetadata.n
n
Definition:
dqmiodumpmetadata.py:28
UnbinnedLikelihoodFit::getParameterErrors
const double * getParameterErrors()
Definition:
UnbinnedLikelihoodFit.h:52
f
double f[11][100]
Definition:
MuScleFitUtils.cc:78
UnbinnedLikelihoodFit::logL
double logL(const double *x) const
Definition:
UnbinnedLikelihoodFit.cc:90
UnbinnedLikelihoodFit::arglist_
double arglist_[10]
Definition:
UnbinnedLikelihoodFit.h:62
DDAxes::x
UnbinnedLikelihoodFit::getParameterValues
double * getParameterValues()
Definition:
UnbinnedLikelihoodFit.h:51
UnbinnedLikelihoodFit::nparameters_
uint32_t nparameters_
Definition:
UnbinnedLikelihoodFit.h:60
UnbinnedLikelihoodFit::min
TVirtualFitter * min
Definition:
UnbinnedLikelihoodFit.h:66
UnbinnedLikelihoodFit::fit
int32_t fit(int32_t verbosity=-1)
Definition:
UnbinnedLikelihoodFit.cc:56
UnbinnedLikelihoodFit::fit
int32_t fit(int32_t n, double *x, int32_t verbosity=-1)
Definition:
UnbinnedLikelihoodFit.h:42
UnbinnedLikelihoodFit::x_
double * x_
Definition:
UnbinnedLikelihoodFit.h:57
UnbinnedLikelihoodFit::setTolerance
void setTolerance(double tol)
Definition:
UnbinnedLikelihoodFit.h:37
heppy_batch.val
val
Definition:
heppy_batch.py:351
UnbinnedLikelihoodFit::setMaxIterations
void setMaxIterations(uint32_t n)
Definition:
UnbinnedLikelihoodFit.h:38
UnbinnedLikelihoodFit
Definition:
UnbinnedLikelihoodFit.h:24
UnbinnedLikelihoodFit::getParameterValue
double getParameterValue(uint32_t i)
Definition:
UnbinnedLikelihoodFit.h:49
UnbinnedLikelihoodFit::getFunction
TF1 * getFunction() const
Definition:
UnbinnedLikelihoodFit.h:48
UnbinnedLikelihoodFit::setData
void setData(uint32_t n, double *x)
Definition:
UnbinnedLikelihoodFit.cc:44
UnbinnedLikelihoodFit::UnbinnedLL
friend void UnbinnedLL(Int_t &npar, Double_t *gin, Double_t &val, Double_t *par, Int_t iflag)
Definition:
UnbinnedLikelihoodFit.cc:22
UnbinnedLikelihoodFit::getParameterError
double getParameterError(uint32_t i)
Definition:
UnbinnedLikelihoodFit.h:50
UnbinnedLikelihoodFit::setFunction
void setFunction(TF1 *f)
Definition:
UnbinnedLikelihoodFit.cc:50
UnbinnedLikelihoodFit::maxIterations_
uint32_t maxIterations_
Definition:
UnbinnedLikelihoodFit.h:63
UnbinnedLikelihoodFit::function_
TF1 * function_
Definition:
UnbinnedLikelihoodFit.h:59
UnbinnedLikelihoodFit::tolerance_
double tolerance_
Definition:
UnbinnedLikelihoodFit.h:64
Generated for CMSSW Reference Manual by
1.8.16