root/Minuit2/FumiliErrorUpdator.h

0001 // @(#)root/minuit2:$Id$
0002 // Authors: M. Winkler, F. James, L. Moneta, A. Zsenei   2003-2005
0003
0004 /**********************************************************************
0005  *                                                                    *
0006  * Copyright (c) 2005 LCG ROOT Math team,  CERN/PH-SFT                *
0007  *                                                                    *
0008  **********************************************************************/
0009
0010 #ifndef ROOT_Minuit2_FumiliErrorUpdator
0011 #define ROOT_Minuit2_FumiliErrorUpdator
0012
0013 #include "Minuit2/MinimumErrorUpdator.h"
0014
0015 namespace ROOT {
0016
0017 namespace Minuit2 {
0018
0019 class MinimumState;
0020 class MinimumParameters;
0021 class GradientCalculator;
0022 class FumiliFCNBase;
0023 class FunctionGradient;
0024
0025 /**
0026
0027 In the case of the Fumili algorithm the Error matrix (or the Hessian
0028 matrix containing the (approximate) second derivatives) is calculated
0029 using a linearization of the model function negleting second
0030 derivatives. (In some sense the Name Updator is a little bit misleading
0031 as the Error matrix is not calculated by iteratively updating, like
0032 in Davidon's or other similar variable metric methods, but by
0033 recalculating each time).
0034
0035
0036 @author  Andras Zsenei and Lorenzo Moneta, Creation date: 28 Sep 2004
0037
0038 @see <A HREF="http://www.cern.ch/winkler/minuit/tutorial/mntutorial.pdf">MINUIT Tutorial</A> on function minimization,
0039 section 5
0040
0041 @see DavidonErrorUpdator
0042
0043 @ingroup Minuit
0044
0045 */
0046
0047 class FumiliErrorUpdator : public MinimumErrorUpdator {
0048
0049 public:
0050    FumiliErrorUpdator() {}
0051
0052    ~FumiliErrorUpdator() override {}
0053
0054    /**
0055
0056    Member function that calculates the Error matrix (or the Hessian
0057    matrix containing the (approximate) second derivatives) using a
0058    linearization of the model function negleting second derivatives.
0059
0060    @param fMinimumState used to calculate the change in the covariance
0061    matrix between the two iterations
0062
0063    @param fMinimumParameters the parameters at the present iteration
0064
0065    @param fGradientCalculator the Gradient calculator used to retrieved the Parameter transformation
0066
0067    @param lambda the Marquard lambda factor
0068
0069
0070    \todo Some nice latex mathematical formuli...
0071
0072    */
0073
0074    virtual MinimumError Update(const MinimumState &fMinimumState, const MinimumParameters &fMinimumParameters,
0075                                const GradientCalculator &fGradientCalculator, double lambda) const;
0076
0077    /**
0078
0079    Member function which is only present due to the design already in place
0080    of the software. As all classes calculating the Error matrix are supposed
0081    inherit from the MinimumErrorUpdator they must inherit this method. In some
0082    methods calculating the aforementioned matrix some of these parameters are
0083    not needed and other parameters are necessary... Hopefully, a more elegant
0084    solution will be found in the future.
0085
0086    \todo How to get rid of this dummy method which is only due to the inheritance
0087
0088    */
0089
0090    MinimumError Update(const MinimumState &, const MinimumParameters &, const FunctionGradient &) const override;
0091
0092 private:
0093 };
0094
0095 } // namespace Minuit2
0096
0097 } // namespace ROOT
0098
0099 #endif // ROOT_Minuit2_FumiliErrorUpdator