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Reference Guide
FunctionMinimizer.h
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1// @(#)root/minuit2:$Id$
2// Authors: M. Winkler, F. James, L. Moneta, A. Zsenei 2003-2005
3
4/**********************************************************************
5 * *
6 * Copyright (c) 2005 LCG ROOT Math team, CERN/PH-SFT *
7 * *
8 **********************************************************************/
9
10#ifndef ROOT_Minuit2_FunctionMinimizer
11#define ROOT_Minuit2_FunctionMinimizer
12
13
14#include "Minuit2/MnConfig.h"
15#include <vector>
16
17namespace ROOT {
18
19 namespace Minuit2 {
20
21
22class FCNBase;
23class FCNGradientBase;
24class FunctionMinimum;
25
26//_____________________________________________________________________________________
27/** base class for function minimizers; user may give FCN or FCN with Gradient,
28 Parameter starting values and initial Error guess (sigma) (or "step size"),
29 or Parameter starting values and initial covariance matrix;
30 covariance matrix is stored in Upper triangular packed storage format,
31 e.g. the Elements in the array are arranged like
32 {a(0,0), a(0,1), a(1,1), a(0,2), a(1,2), a(2,2), ...},
33 the size is nrow*(nrow+1)/2 (see also MnUserCovariance.h);
34 */
35
37
38public:
39
40 virtual ~FunctionMinimizer() {}
41
42 //starting values for parameters and errors
43 virtual FunctionMinimum Minimize(const FCNBase&, const std::vector<double>& par, const std::vector<double>& err, unsigned int strategy, unsigned int maxfcn, double toler) const = 0;
44
45 //starting values for parameters and errors and FCN with Gradient
46 virtual FunctionMinimum Minimize(const FCNGradientBase&, const std::vector<double>& par, const std::vector<double>& err, unsigned int strategy, unsigned int maxfcn, double toler) const = 0;
47
48 //starting values for parameters and covariance matrix
49 virtual FunctionMinimum Minimize(const FCNBase&, const std::vector<double>& par, unsigned int nrow, const std::vector<double>& cov, unsigned int strategy, unsigned int maxfcn, double toler) const = 0;
50
51 //starting values for parameters and covariance matrix and FCN with Gradient
52 virtual FunctionMinimum Minimize(const FCNGradientBase&, const std::vector<double>& par, unsigned int nrow, const std::vector<double>& cov, unsigned int strategy, unsigned int maxfcn, double toler) const = 0;
53
54};
55
56 } // namespace Minuit2
57
58} // namespace ROOT
59
60#endif // ROOT_Minuit2_FunctionMinimizer
Interface (abstract class) defining the function to be minimized, which has to be implemented by the ...
Definition: FCNBase.h:47
Extension of the FCNBase for providing the analytical Gradient of the function.
base class for function minimizers; user may give FCN or FCN with Gradient, Parameter starting values...
virtual FunctionMinimum Minimize(const FCNBase &, const std::vector< double > &par, unsigned int nrow, const std::vector< double > &cov, unsigned int strategy, unsigned int maxfcn, double toler) const =0
virtual FunctionMinimum Minimize(const FCNGradientBase &, const std::vector< double > &par, unsigned int nrow, const std::vector< double > &cov, unsigned int strategy, unsigned int maxfcn, double toler) const =0
virtual FunctionMinimum Minimize(const FCNBase &, const std::vector< double > &par, const std::vector< double > &err, unsigned int strategy, unsigned int maxfcn, double toler) const =0
virtual FunctionMinimum Minimize(const FCNGradientBase &, const std::vector< double > &par, const std::vector< double > &err, unsigned int strategy, unsigned int maxfcn, double toler) const =0
class holding the full result of the minimization; both internal and external (MnUserParameterState) ...
VSD Structures.
Definition: StringConv.hxx:21