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1 | /************************************************************************** | |
2 | * Copyright(c) 2001-2002, ALICE Experiment at CERN, All rights reserved. * | |
3 | * * | |
4 | * Author: The ALICE Off-line Project. * | |
5 | * Contributors are mentioned in the code where appropriate. * | |
6 | * * | |
7 | * Permission to use, copy, modify and distribute this software and its * | |
8 | * documentation strictly for non-commercial purposes is hereby granted * | |
9 | * without fee, provided that the above copyright notice appears in all * | |
10 | * copies and that both the copyright notice and this permission notice * | |
11 | * appear in the supporting documentation. The authors make no claims * | |
12 | * about the suitability of this software for any purpose. It is * | |
13 | * provided "as is" without express or implied warranty. * | |
14 | **************************************************************************/ | |
15 | ||
16 | //////////////////////////////////////////////////////////////////////// | |
17 | // Class used to generate correlated gaussian numbers with mean | |
18 | // zero and known covariance matrix. | |
19 | // Adapted from the Fortran code in Cernlib V122 (corset, corgen) | |
20 | // F. James, Monte Carlo theory and practice, | |
21 | // Rep. Prog. Phys. 43 (1980) 1145-1189. | |
22 | // M.Masera 15.03.2001 9:30 - modified on 26.02.2002 17:40 | |
23 | //////////////////////////////////////////////////////////////////////// | |
24 | ||
25 | #include <Riostream.h> | |
26 | #include <TArrayD.h> | |
27 | #include <TMatrixD.h> | |
28 | #include <TRandom.h> | |
29 | #include "AliGausCorr.h" | |
30 | ||
31 | ClassImp(AliGausCorr) | |
32 | ||
33 | //_______________________________________________________________________ | |
34 | AliGausCorr::AliGausCorr(): | |
35 | fSize(0), | |
36 | fCv(0) | |
37 | { | |
38 | // | |
39 | // Default constructor | |
40 | // | |
41 | } | |
42 | ||
43 | //_______________________________________________________________________ | |
44 | AliGausCorr::AliGausCorr(const TMatrixD & vec, Int_t size): | |
45 | fSize(size), | |
46 | fCv(new TMatrixD(fSize,fSize)) | |
47 | { | |
48 | // | |
49 | // Standard constructor | |
50 | // | |
51 | for(Int_t j=0;j<fSize;j++){ | |
52 | double accum = 0; | |
53 | for(Int_t k=0;k<j;k++){ | |
54 | accum += (*fCv)(j,k)* (*fCv)(j,k); | |
55 | } | |
56 | (*fCv)(j,j)=TMath::Sqrt(TMath::Abs(vec(j,j)-accum)); | |
57 | for(Int_t i=j+1;i<fSize;i++){ | |
58 | accum = 0; | |
59 | for(Int_t k=0;k<j;k++){ | |
60 | accum+=(*fCv)(i,k)* (*fCv)(j,k); | |
61 | } | |
62 | (*fCv)(i,j) = (vec(i,j)-accum) / (*fCv)(j,j); | |
63 | } | |
64 | } | |
65 | } | |
66 | ||
67 | //_______________________________________________________________________ | |
68 | AliGausCorr::AliGausCorr(const AliGausCorr & tgcorr): | |
69 | TObject(tgcorr), | |
70 | fSize(tgcorr.fSize), | |
71 | fCv(new TMatrixD(fSize,fSize)) | |
72 | { | |
73 | // | |
74 | // Copy contructor | |
75 | // | |
76 | for(Int_t i=0;i<fSize;i++){ | |
77 | for(Int_t j=0;j<fSize;j++)(*fCv)(i,j)=(*tgcorr.fCv)(i,j); | |
78 | } | |
79 | } | |
80 | ||
81 | //_______________________________________________________________________ | |
82 | AliGausCorr::~AliGausCorr() | |
83 | { | |
84 | // Destructor | |
85 | delete fCv; | |
86 | } | |
87 | ||
88 | //_______________________________________________________________________ | |
89 | void AliGausCorr::GetGaussN(TArrayD &vec) const | |
90 | { | |
91 | // return fSize correlated gaussian numbers | |
92 | ||
93 | TArrayD tmpv(fSize); | |
94 | ||
95 | for(Int_t i=0; i<fSize; i++){ | |
96 | Double_t x, y, z; | |
97 | do { | |
98 | y = gRandom->Rndm(); | |
99 | } while (!y); | |
100 | z = gRandom->Rndm(); | |
101 | x = z * 6.283185; | |
102 | tmpv[i] = TMath::Sin(x)*TMath::Sqrt(-2*TMath::Log(y)); | |
103 | } | |
104 | ||
105 | for(Int_t i=0;i<fSize;i++){ | |
106 | vec[i]=0; | |
107 | for(Int_t j=0;j<=i;j++)vec[i] += (*fCv)(i,j)* tmpv[j]; | |
108 | } | |
109 | ||
110 | } | |
111 | ||
112 | //_______________________________________________________________________ | |
113 | void AliGausCorr::PrintCv() const | |
114 | { | |
115 | // Printout of the "square root" cov. matrix | |
116 | printf("\n AliGausCorr - triangular matrix \n"); | |
117 | for(Int_t i=0; i<fSize;i++){ | |
118 | for(Int_t j=0;j<(fSize-1);j++){ | |
119 | if(j==0){ | |
120 | printf("| %12.4f ",(*fCv)(i,j)); | |
121 | } | |
122 | else { | |
123 | printf(" %12.4f ",(*fCv)(i,j)); | |
124 | } | |
125 | } | |
126 | printf(" %12.4f | \n",(*fCv)(i,fSize-1)); | |
127 | } | |
128 | printf("\n"); | |
129 | } | |
130 | ||
131 | //_______________________________________________________________________ | |
132 | AliGausCorr & AliGausCorr::operator=(const AliGausCorr & tgcorr) | |
133 | { | |
134 | if(&tgcorr != this && tgcorr.fSize!=fSize){ | |
135 | if(fCv)delete fCv; | |
136 | fSize = tgcorr.fSize; | |
137 | fCv = new TMatrixD(fSize,fSize); | |
138 | } | |
139 | if(&tgcorr != this){ | |
140 | for(Int_t i=0;i<fSize;i++){ | |
141 | for(Int_t j=0;j<fSize;j++)(*fCv)(i,j)=(*tgcorr.fCv)(i,j); | |
142 | } | |
143 | } | |
144 | ||
145 | return *this; | |
146 | } |