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1 | ////////////////////////////////////////////////////////////////////////// | |
2 | // Alice ITS class to help keep statistical information // | |
3 | // // | |
4 | // version: 0.0.0 Draft. // | |
5 | // Date: April 18 1999 // | |
6 | // By: Bjorn S. Nilsen // | |
7 | // // | |
8 | ////////////////////////////////////////////////////////////////////////// | |
9 | #include <stdio.h> | |
10 | #include <math.h> | |
11 | #include <TMath.h> | |
12 | ||
13 | #include "AliITSstatistics.h" | |
14 | ||
15 | ClassImp(AliITSstatistics) | |
16 | ||
17 | // | |
18 | AliITSstatistics::AliITSstatistics() : TObject(){ | |
19 | // | |
20 | // default contructor | |
21 | // | |
22 | fX = 0; | |
23 | fW = 0; | |
24 | fN = 0; | |
25 | fOrder = 0; | |
26 | return; | |
27 | } | |
28 | ||
29 | ||
30 | AliITSstatistics::AliITSstatistics(Int_t order) : TObject(){ | |
31 | // | |
32 | // contructor to a specific order in the moments | |
33 | // | |
34 | fOrder = order; | |
35 | fX = new Double_t[order]; | |
36 | fW = new Double_t[order]; | |
37 | for(Int_t i=0;i<order;i++) {fX[i] = 0.0; fW[i] = 0.0;} | |
38 | fN = 0; | |
39 | return; | |
40 | } | |
41 | ||
42 | AliITSstatistics::~AliITSstatistics(){ | |
43 | // | |
44 | // default destructor | |
45 | // | |
46 | if(fX!=0) delete[] fX; | |
47 | if(fW!=0) delete[] fW; | |
48 | fX = 0; | |
49 | fW = 0; | |
50 | fN = 0; | |
51 | fOrder = 0; | |
52 | } | |
53 | //_______________________________________________________________ | |
54 | AliITSstatistics& AliITSstatistics::operator=(AliITSstatistics &source){ | |
55 | // operator = | |
56 | ||
57 | if(this==&source) return *this; | |
58 | if(source.fOrder!=0){ | |
59 | this->fOrder = source.fOrder; | |
60 | this->fN = source.fN; | |
61 | this->fX = new Double_t[this->fOrder]; | |
62 | this->fW = new Double_t[this->fOrder]; | |
63 | for(Int_t i=0;i<source.fOrder;i++){ | |
64 | this->fX[i] = source.fX[i]; | |
65 | this->fW[i] = source.fW[i]; | |
66 | } // end for i | |
67 | }else{ | |
68 | this->fX = 0; | |
69 | this->fW = 0; | |
70 | this->fN = 0; | |
71 | this->fOrder = 0; | |
72 | }// end if source.fOrder!=0 | |
73 | return *this; | |
74 | } | |
75 | //_______________________________________________________________ | |
76 | AliITSstatistics::AliITSstatistics(AliITSstatistics &source){ | |
77 | // Copy constructor | |
78 | ||
79 | if(this==&source) return; | |
80 | if(source.fOrder!=0){ | |
81 | this->fOrder = source.fOrder; | |
82 | this->fN = source.fN; | |
83 | this->fX = new Double_t[this->fOrder]; | |
84 | this->fW = new Double_t[this->fOrder]; | |
85 | for(Int_t i=0;i<source.fOrder;i++){ | |
86 | this->fX[i] = source.fX[i]; | |
87 | this->fW[i] = source.fW[i]; | |
88 | } // end for i | |
89 | }else{ | |
90 | this->fX = 0; | |
91 | this->fW = 0; | |
92 | this->fN = 0; | |
93 | this->fOrder = 0; | |
94 | }// end if source.fOrder!=0 | |
95 | } | |
96 | //_______________________________________________________________ | |
97 | void AliITSstatistics::Reset(){ | |
98 | // | |
99 | // reset all values to zero | |
100 | // | |
101 | for(Int_t i=0;i<fOrder;i++) {fX[i] = 0.0; fW[i] = 0.0;} | |
102 | fN = 0; | |
103 | return; | |
104 | } | |
105 | ||
106 | //_______________________________________________________________ | |
107 | void AliITSstatistics::AddValue(Double_t x,Double_t w){ | |
108 | // | |
109 | // accumulate element x with weight w. | |
110 | // | |
111 | ||
112 | //it was AddValue(Double_t x,Double_t w=1.0); | |
113 | ||
114 | Double_t y=1.0,z=1.0; | |
115 | ||
116 | Int_t i; | |
117 | const Double_t kBig=1.0e+38; | |
118 | ||
119 | if(y>kBig || x>kBig || w>kBig) return; | |
120 | ||
121 | fN++; | |
122 | for(i=0;i<fOrder;i++){ | |
123 | y *= x; | |
124 | z *= w; | |
125 | fX[i] += y*w; | |
126 | fW[i] += z; | |
127 | } // end for i | |
128 | } | |
129 | ||
130 | Double_t AliITSstatistics::GetNth(Int_t order){ | |
131 | // This give the unbiased estimator for the RMS. | |
132 | Double_t s; | |
133 | ||
134 | if(fW[0]!=0.0&&order<=fOrder) s = fX[order-1]/fW[0]; | |
135 | else { | |
136 | s = 0.0; | |
137 | printf("AliITSstatistics: error in GetNth: fOrder=%d fN=%d fW[0]=%f\n", | |
138 | fOrder,fN,fW[0]); | |
139 | } // end else | |
140 | return s; | |
141 | } | |
142 | ||
143 | Double_t AliITSstatistics::GetRMS(){ | |
144 | // This give the unbiased estimator for the RMS. | |
145 | Double_t x,x2,w,ww,s; | |
146 | ||
147 | x = GetMean(); // first order | |
148 | x2 = GetNth(2); // second order | |
149 | w = fW[0]; // first order - 1. | |
150 | ww = fW[1]; // second order - 1. | |
151 | ||
152 | if(w*w==ww) return (-1.0); | |
153 | s = (x2-x*x)*w*w/(w*w-ww); | |
154 | return TMath::Sqrt(s); | |
155 | } | |
156 | ||
157 | Double_t AliITSstatistics::GetErrorMean(){ | |
158 | //This is the error in the mean or the square root of the variance of the mean. | |
159 | Double_t rms,w,ww,s; | |
160 | ||
161 | rms = GetRMS(); | |
162 | w = fW[0]; | |
163 | ww = fW[1]; | |
164 | s = rms*rms*ww/(w*w); | |
165 | return TMath::Sqrt(s); | |
166 | } | |
167 | ||
168 | ||
169 | Double_t AliITSstatistics::GetErrorRMS(){ | |
170 | //This is the error in the mean or the square root of the variance of the mean. | |
171 | // at this moment this routine is only defined for weights=1. | |
172 | Double_t x,x2,x3,x4,w,ww,m2,m4,n,s; | |
173 | ||
174 | if(fW[0]!=(Double_t)fN||GetN()<4) return (-1.); | |
175 | x = GetMean(); // first order | |
176 | x2 = GetNth(2); // second order | |
177 | w = fW[0]; // first order - 1. | |
178 | ww = fW[1]; // second order - 1. | |
179 | if(w*w==ww) return (-1.0); | |
180 | s = (x2-x*x)*w*w/(w*w-ww); | |
181 | ||
182 | m2 = s; | |
183 | n = (Double_t) GetN(); | |
184 | x3 = GetNth(3); | |
185 | x4 = GetNth(4); | |
186 | // This equation assumes that all of the weights are equal to 1. | |
187 | m4 = (n/(n-1.))*(x4-3.*x*x3+6.*x*x*x2-2.*x*x*x*x); | |
188 | s = (m4-(n-3.)*m2*m2/(n-1.))/n; | |
189 | return TMath::Sqrt(s); | |
190 | } |