/usr/include/odindata/statistics.h is in libodin-dev 1.8.5-2ubuntu1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 | /***************************************************************************
statistics.h - description
-------------------
begin : Fri Apr 6 2001
copyright : (C) 2001 by Thies Jochimsen
email : jochimse@cns.mpg.de
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
#ifndef STATISTICS_H
#define STATISTICS_H
#include<odindata/data.h>
#include<odindata/utils.h>
/**
* @addtogroup odindata
* @{
*/
///////////////////////////////////////////////////////////
/**
* Results of a statistical analysis
*
*/
struct statisticResult {
/**
* The minimum value
*/
double min;
/**
* The minimum value
*/
double max;
/**
* The mean value
*/
double mean;
/**
* The standard deviation
*/
double stdev;
/**
* The standard deviation of the mean value
*/
double meandev;
/**
* Prints statistics to ostream
*/
friend STD_ostream& operator << (STD_ostream& s, statisticResult stats);
};
///////////////////////////////////////////////////////////
/**
* Returns a statistical description of 'ensemble'. If mask is non-zero,
* only values with mask!=0 are considered.
*
*/
template<typename T, int N_rank>
statisticResult statistics(const Array<T,N_rank>& ensemble, const Array<T,N_rank>* mask=0) {
Log<OdinData> odinlog("","statistics");
statisticResult result;
result.min=0.0;
result.max=0.0;
result.mean=0.0;
result.stdev=0.0;
result.meandev=0.0;
if(mask && !same_shape(ensemble,*mask)) {
ODINLOG(odinlog,errorLog) << "size mismatch (ensemble.shape()=" << ensemble.shape() << ") != (mask.shape()=" << mask->shape() << ")" << STD_endl;
return result;
}
int n=ensemble.numElements();
Data<T,N_rank> ensemble_copy(ensemble);
int nvals=0;
TinyVector<int,N_rank> index;
for(int i=0; i<n; i++) {
index=ensemble_copy.create_index(i);
bool include=true;
if(mask && (*mask)(index)==0.0) include=false;
if(include) {
float val=ensemble(index);
result.mean+=val;
nvals++;
if(i==0) {
result.min=result.max=val;
} else {
if(val<result.min) result.min=val;
if(val>result.max) result.max=val;
}
}
}
result.mean=secureDivision(result.mean,double(nvals));
nvals=0;
for(int i=0; i<n; i++) {
index=ensemble_copy.create_index(i);
bool include=true;
if(mask && (*mask)(index)==0.0) include=false;
if(include) {
double diff=result.mean-ensemble(index);
result.stdev+=diff*diff;
nvals++;
}
}
if(nvals>1) result.stdev=sqrt(result.stdev/double(nvals-1));
else result.stdev=0.0;
result.meandev=result.stdev/sqrt(double(nvals));
return result;
}
///////////////////////////////////////////////////////////
/**
* Returns the median of 'ensemble'.
*
*/
template<typename T, int N_rank>
T median(const Array<T,N_rank>& ensemble) {
Data<T,N_rank> ensemble_copy(ensemble);
Array<T,N_rank> diff(ensemble.shape());
TinyVector<int,N_rank> index;
for(int i=0; i<ensemble.numElements(); i++) {
index=ensemble_copy.create_index(i);
diff(index)=sum(fabs(ensemble-ensemble(index)));
}
return ensemble(minIndex(diff));
}
///////////////////////////////////////////////////////////
/**
* Returns the weighted mean of 'ensemble' using 'weight'
* for the weighting.
*
*/
template<typename T, int N_rank>
T weightmean(const Array<T,N_rank>& ensemble, const Array<float,N_rank>& weight) {
Log<OdinData> odinlog("","weightmean");
T result;
result=0; // double-stage init for TinyVector
Data<T,N_rank> ensemble_copy(ensemble);
if(ensemble.shape()!=weight.shape()) {
ODINLOG(odinlog,errorLog) << "size mismatch (ensemble.shape()=" << ensemble.shape() << ") != (weight.shape()=" << weight.shape() << ")" << STD_endl;
return result;
}
float weightsum=0.0;
TinyVector<int,N_rank> index;
for(int i=0; i<ensemble_copy.numElements(); i++) {
index=ensemble_copy.create_index(i);
float w=fabs(weight(index));
result+=w*ensemble_copy(index);
weightsum+=w;
}
result/=weightsum;
return result;
}
/** @}
*/
#endif
|