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Пелипенко Иван
2022-12-14 14:13:52 +03:00
parent 430a41fefc
commit c2b8a8d6da
297 changed files with 27331 additions and 24162 deletions
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56
libs/main/math/pistatistic.h
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@@ -5,22 +5,22 @@
* \~russian Вычисление математической статистики у массива чисел
*/
/*
PIP - Platform Independent Primitives
Class for calculacing math statistic in values array
Andrey Bychkov work.a.b@yandex.ru
PIP - Platform Independent Primitives
Class for calculacing math statistic in values array
Andrey Bychkov work.a.b@yandex.ru
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
You should have received a copy of the GNU Lesser General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef PISTATISTIC_H
@@ -28,17 +28,17 @@
#include "pimathbase.h"
template <typename T>
template<typename T>
class PIStatistic {
static_assert(std::is_arithmetic<T>::value, "Type must be arithmetic");
public:
PIStatistic() {mean = variance = skewness = kurtosis = T();}
PIStatistic() { mean = variance = skewness = kurtosis = T(); }
static T calculateMean(const PIVector<T> & val) {
T ret = T();
int n = val.size();
if (n < 1)
return ret;
if (n < 1) return ret;
for (int i = 0; i < n; i++)
ret += val[i];
return ret / n;
@@ -46,26 +46,24 @@ public:
bool calculate(const PIVector<T> & val, const T & given_mean) {
T v = T(), v1 = T(), v2 = T(), stddev = T(), var = T();
int i, n = val.size();
if (n < 2)
return false;
mean = given_mean;
if (n < 2) return false;
mean = given_mean;
variance = skewness = kurtosis = T();
// Variance (using corrected two-pass algorithm)
for (i = 0; i < n; i++)
v1 += sqr(val[i] - mean);
for (i = 0; i < n; i++)
v2 += val[i] - mean;
v2 = sqr(v2) / n;
v2 = sqr(v2) / n;
variance = v1 / n;
var = (v1 / n - v2) / (n - 1);
if (var < T())
var = T();
var = (v1 / n - v2) / (n - 1);
if (var < T()) var = T();
stddev = sqrt(var);
// Skewness and kurtosis
if (stddev != T()) {
for (i = 0; i < n; i++) {
v = (val[i] - mean) / stddev;
v2 = sqr(v);
v = (val[i] - mean) / stddev;
v2 = sqr(v);
skewness = skewness + v2 * v;
kurtosis = kurtosis + sqr(v2);
}
@@ -74,8 +72,8 @@ public:
}
return true;
}
bool calculate(const PIVector<T> & val) {return calculate(val, calculateMean(val));}
bool calculate(const PIVector<T> & val) { return calculate(val, calculateMean(val)); }
T mean;
T variance;
T skewness;