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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 | fN(0), | |
20 | fOrder(0), | |
21 | fX(0), | |
22 | fW(0){ | |
23 | // | |
24 | // default contructor | |
25 | // | |
26 | } | |
27 | ||
28 | ||
29 | AliITSstatistics::AliITSstatistics(Int_t order) : TObject(), | |
30 | fN(0), | |
31 | fOrder(order), | |
32 | fX(0), | |
33 | fW(0){ | |
34 | // | |
35 | // contructor to a specific order in the moments | |
36 | // | |
37 | fX = new Double_t[order]; | |
38 | fW = new Double_t[order]; | |
39 | for(Int_t i=0;i<order;i++) {fX[i] = 0.0; fW[i] = 0.0;} | |
40 | return; | |
41 | } | |
42 | ||
43 | AliITSstatistics::~AliITSstatistics(){ | |
44 | // | |
45 | // default destructor | |
46 | // | |
47 | if(fX!=0) delete[] fX; | |
48 | if(fW!=0) delete[] fW; | |
49 | fX = 0; | |
50 | fW = 0; | |
51 | fN = 0; | |
52 | fOrder = 0; | |
53 | } | |
54 | //_______________________________________________________________ | |
55 | AliITSstatistics& AliITSstatistics::operator=(const AliITSstatistics &source){ | |
56 | // operator = | |
57 | ||
58 | if(this==&source) return *this; | |
59 | if(source.fOrder!=0){ | |
60 | this->fOrder = source.fOrder; | |
61 | this->fN = source.fN; | |
62 | this->fX = new Double_t[this->fOrder]; | |
63 | this->fW = new Double_t[this->fOrder]; | |
64 | for(Int_t i=0;i<source.fOrder;i++){ | |
65 | this->fX[i] = source.fX[i]; | |
66 | this->fW[i] = source.fW[i]; | |
67 | } // end for i | |
68 | }else{ | |
69 | this->fX = 0; | |
70 | this->fW = 0; | |
71 | this->fN = 0; | |
72 | this->fOrder = 0; | |
73 | }// end if source.fOrder!=0 | |
74 | return *this; | |
75 | } | |
76 | //_______________________________________________________________ | |
77 | AliITSstatistics::AliITSstatistics(const AliITSstatistics &source) : TObject(source), | |
78 | fN(0), | |
79 | fOrder(0), | |
80 | fX(0), | |
81 | fW(0){ | |
82 | // Copy constructor | |
83 | ||
84 | if(this==&source) return; | |
85 | if(source.fOrder!=0){ | |
86 | this->fOrder = source.fOrder; | |
87 | this->fN = source.fN; | |
88 | this->fX = new Double_t[this->fOrder]; | |
89 | this->fW = new Double_t[this->fOrder]; | |
90 | for(Int_t i=0;i<source.fOrder;i++){ | |
91 | this->fX[i] = source.fX[i]; | |
92 | this->fW[i] = source.fW[i]; | |
93 | } // end for i | |
94 | }else{ | |
95 | this->fX = 0; | |
96 | this->fW = 0; | |
97 | this->fN = 0; | |
98 | this->fOrder = 0; | |
99 | }// end if source.fOrder!=0 | |
100 | } | |
101 | //_______________________________________________________________ | |
102 | void AliITSstatistics::Reset(){ | |
103 | // | |
104 | // reset all values to zero | |
105 | // | |
106 | for(Int_t i=0;i<fOrder;i++) {fX[i] = 0.0; fW[i] = 0.0;} | |
107 | fN = 0; | |
108 | return; | |
109 | } | |
110 | ||
111 | //_______________________________________________________________ | |
112 | void AliITSstatistics::AddValue(Double_t x,Double_t w){ | |
113 | // | |
114 | // accumulate element x with weight w. | |
115 | // | |
116 | ||
117 | //it was AddValue(Double_t x,Double_t w=1.0); | |
118 | ||
119 | Double_t y=1.0,z=1.0; | |
120 | ||
121 | Int_t i; | |
122 | const Double_t kBig=1.0e+38; | |
123 | ||
124 | if(y>kBig || x>kBig || w>kBig) return; | |
125 | ||
126 | fN++; | |
127 | for(i=0;i<fOrder;i++){ | |
128 | y *= x; | |
129 | z *= w; | |
130 | fX[i] += y*w; | |
131 | fW[i] += z; | |
132 | } // end for i | |
133 | } | |
134 | ||
135 | Double_t AliITSstatistics::GetNth(Int_t order){ | |
136 | // This give the unbiased estimator for the RMS. | |
137 | Double_t s; | |
138 | ||
139 | if(fW[0]!=0.0&&order<=fOrder) s = fX[order-1]/fW[0]; | |
140 | else { | |
141 | s = 0.0; | |
142 | printf("AliITSstatistics: error in GetNth: fOrder=%d fN=%d fW[0]=%f\n", | |
143 | fOrder,fN,fW[0]); | |
144 | } // end else | |
145 | return s; | |
146 | } | |
147 | ||
148 | Double_t AliITSstatistics::GetRMS(){ | |
149 | // This give the unbiased estimator for the RMS. | |
150 | Double_t x,x2,w,ww,s; | |
151 | ||
152 | x = GetMean(); // first order | |
153 | x2 = GetNth(2); // second order | |
154 | w = fW[0]; // first order - 1. | |
155 | ww = fW[1]; // second order - 1. | |
156 | ||
157 | if(w*w==ww) return (-1.0); | |
158 | s = (x2-x*x)*w*w/(w*w-ww); | |
159 | return TMath::Sqrt(s); | |
160 | } | |
161 | ||
162 | Double_t AliITSstatistics::GetErrorMean(){ | |
163 | //This is the error in the mean or the square root of the variance of the mean. | |
164 | Double_t rms,w,ww,s; | |
165 | ||
166 | rms = GetRMS(); | |
167 | w = fW[0]; | |
168 | ww = fW[1]; | |
169 | s = rms*rms*ww/(w*w); | |
170 | return TMath::Sqrt(s); | |
171 | } | |
172 | ||
173 | ||
174 | Double_t AliITSstatistics::GetErrorRMS(){ | |
175 | //This is the error in the mean or the square root of the variance of the mean. | |
176 | // at this moment this routine is only defined for weights=1. | |
177 | Double_t x,x2,x3,x4,w,ww,m2,m4,n,s; | |
178 | ||
179 | if(fW[0]!=(Double_t)fN||GetN()<4) return (-1.); | |
180 | x = GetMean(); // first order | |
181 | x2 = GetNth(2); // second order | |
182 | w = fW[0]; // first order - 1. | |
183 | ww = fW[1]; // second order - 1. | |
184 | if(w*w==ww) return (-1.0); | |
185 | s = (x2-x*x)*w*w/(w*w-ww); | |
186 | ||
187 | m2 = s; | |
188 | n = (Double_t) GetN(); | |
189 | x3 = GetNth(3); | |
190 | x4 = GetNth(4); | |
191 | // This equation assumes that all of the weights are equal to 1. | |
192 | m4 = (n/(n-1.))*(x4-3.*x*x3+6.*x*x*x2-2.*x*x*x*x); | |
193 | s = (m4-(n-3.)*m2*m2/(n-1.))/n; | |
194 | return TMath::Sqrt(s); | |
195 | } |