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Foption.h
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1 /* @(#)root/hist:$Id$ */
2 
3 /*************************************************************************
4  * Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *
5  * All rights reserved. *
6  * *
7  * For the licensing terms see $ROOTSYS/LICENSE. *
8  * For the list of contributors see $ROOTSYS/README/CREDITS. *
9  *************************************************************************/
10 
11 #ifndef ROOT_Foption
12 #define ROOT_Foption
13 
14 
15 //////////////////////////////////////////////////////////////////////////
16 // //
17 // Foption //
18 // //
19 // Histogram fit options structure. //
20 // //
21 //////////////////////////////////////////////////////////////////////////
22 
23 
24 struct Foption_t {
25 //*-* chopt may be the concatenation of the following options:
26 //*-* =======================================================
27 //*-*
28 //*-* The following structure members are set to 1 if the option is selected:
29  int Quiet; // "Q" Quiet mode. No print
30  int Verbose; // "V" Verbose mode. Print results after each iteration
31  int Bound; // "B" When using pre-defined functions user parameter settings are used instead of default one
32  int Chi2; // "X" For fitting THnsparse use chi2 method (default is likelihood)
33  int PChi2; // "P" Use Pearson chi2 built with the expected error instead of the observed ones
34  int Like; // "L" Use Log Likelihood. Default is chisquare method except fitting THnsparse
35  int User; // "U" Use a User specified fitting algorithm (via SetFCN)
36  int W1; // "W" Set all the weights to 1. Ignore error bars
37  int Errors; // "E" Performs a better error evaluation, calling HESSE and MINOS
38  int More; // "M" Improve fit results.
39  int Range; // "R" Use the range stored in function
40  int Gradient; // "G" Option to compute derivatives analytically
41  int Nostore; // "N" If set, do not store the function graph
42  int Nograph; // "0" If set, do not display the function graph
43  int Plus; // "+" Add new function (default is replace)
44  int Integral; // "I" Use function integral instead of function in center of bin
45  int Nochisq; // "C" In case of linear fitting, don't calculate the chisquare
46  int Minuit; // "F" If fitting a polN, switch to minuit fitter
47  int NoErrX; // "EX0" or "T" When fitting a TGraphErrors do not consider error in coordinates
48  int Robust; // "ROB" or "H": For a TGraph use robust fitting
49  int StoreResult; // "S": Stores the result in a TFitResult structure
50  int BinVolume; // "WIDTH": scale content by the bin width/volume
51  double hRobust; // value of h parameter used in robust fitting
52 
54  Quiet (0),
55  Verbose (0),
56  Bound (0),
57  Chi2 (0),
58  PChi2 (0),
59  Like (0),
60  User (0),
61  W1 (0),
62  Errors (0),
63  More (0),
64  Range (0),
65  Gradient (0),
66  Nostore (0),
67  Nograph (0),
68  Plus (0),
69  Integral (0),
70  Nochisq (0),
71  Minuit (0),
72  NoErrX (0),
73  Robust (0),
74  StoreResult (0),
75  BinVolume (0),
76  hRobust (0)
77  {}
78 };
79 
80 #endif
int Errors
Definition: Foption.h:37
int Verbose
Definition: Foption.h:30
int Nograph
Definition: Foption.h:42
int Minuit
Definition: Foption.h:46
int Nostore
Definition: Foption.h:41
double hRobust
Definition: Foption.h:51
int Chi2
Definition: Foption.h:32
int Plus
Definition: Foption.h:43
int BinVolume
Definition: Foption.h:50
int User
Definition: Foption.h:35
int PChi2
Definition: Foption.h:33
int Gradient
Definition: Foption.h:40
int StoreResult
Definition: Foption.h:49
int More
Definition: Foption.h:38
int Like
Definition: Foption.h:34
int Integral
Definition: Foption.h:44
int W1
Definition: Foption.h:36
Foption_t()
Definition: Foption.h:53
int Robust
Definition: Foption.h:48
int Range
Definition: Foption.h:39
int Bound
Definition: Foption.h:31
int Nochisq
Definition: Foption.h:45
int NoErrX
Definition: Foption.h:47
int Quiet
Definition: Foption.h:29