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/*
* Copyright (C) 2016+ AzerothCore <www.azerothcore.org>, released under GNU AGPL v3 license: https://github.com/azerothcore/azerothcore-wotlk/blob/master/LICENSE-AGPL3
*/
#ifndef _MATH_UTIL_H
#define _MATH_UTIL_H
#include <algorithm>
#include <iterator>
#include <numeric>
#include <vector>
// based on https://stackoverflow.com/questions/7616511/calculate-mean-and-standard-deviation-from-a-vector-of-samples-in-c-using-boos/12405793#comment32490316_12405793
template <typename Container, typename T = typename std::decay<decltype(*std::begin(std::declval<Container>()))>::type>
inline T standard_deviation(Container&& c)
{
auto b = std::begin(c), e = std::end(c);
auto size = std::distance(b, e);
auto sum = std::accumulate(b, e, T());
auto mean = sum / size;
if (size == 1)
{
return (T) 0;
}
T accum = T();
for (const auto d : c)
{
accum += (d - mean) * (d - mean);
}
return std::sqrt(accum / (size - 1));
}
template <typename Container, typename T = typename std::decay<decltype(*std::begin(std::declval<Container>()))>::type>
inline T mean(Container&& c)
{
auto b = std::begin(c), e = std::end(c);
auto size = std::distance(b, e);
auto sum = std::accumulate(b, e, T());
return sum / size;
}
// based off https://www.geeksforgeeks.org/finding-median-of-unsorted-array-in-linear-time-using-c-stl/
template <typename T>
inline T median(std::vector<T> a)
{
size_t n = a.size();
// If size of the arr[] is even
if (n % 2 == 0)
{
// Applying nth_element
// on n/2th index
std::nth_element(a.begin(),
a.begin() + n / 2,
a.end());
// Applying nth_element
// on (n-1)/2 th index
std::nth_element(a.begin(),
a.begin() + (n - 1) / 2,
a.end());
// Find the average of value at
// index N/2 and (N-1)/2
return (T)(a[(n - 1) / 2]
+ a[n / 2])
/ 2.0;
}
// If size of the arr[] is odd
else
{
// Applying nth_element
// on n/2
std::nth_element(a.begin(),
a.begin() + n / 2,
a.end());
// Value at index (N/2)th
// is the median
return (T)a[n / 2];
}
}
#endif
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