- added statistics folder

git-svn-id: http://moon:8086/svn/software/trunk/libsrc/cpp@1042 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
2022-06-20 10:58:03 +00:00
parent dce7a3cade
commit a7976e4365
2 changed files with 137 additions and 0 deletions
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#ifndef _STATISTICS_SLIDINGMINMAX_HPP_
#define _STATISTICS_SLIDINGMINMAX_HPP_
#pragma once
#include <cpp/radio/Vector.hpp>
#include <cpp/radio/statistics/SlidingMinMax.hpp>
#include <stddef.h>
#include <blaze/Blaze.h>
namespace Radio
{
namespace Statistics
{
// Sliding Min/Max based on MAXLIST-Algorithm, based on:
// "AN EFFICIENT ALGORITHM FOR RUNNING MAX MIN CALCULATION", 1996, S.C. Douglas, University of Utah
// Dependeding on 'mode' this algorithm calculates either minimum (mode = -1) or maximum (mode = +1)
template <typename T>
class SlidingMinMax
{
public:
enum Mode
{
Min,
Max
};
SlidingMinMax(Mode mode, size_t L, T P);
~SlidingMinMax();
void process(T const &xin);
T getWinner()
{
return m_win_value;
}
private:
size_t m_L;
T m_P;
size_t m_N;
Mode m_mode;
RealScalar m_mode_value;
T m_win_value;
size_t m_win_index;
blaze::DynamicVector<T> m_pU;
blaze::DynamicVector<T> m_pU_last;
blaze::DynamicVector<size_t> m_pP;
blaze::DynamicVector<size_t> m_pP_last;
};
#include "SlidingMinMax.tcc"
} // Statistics
} // Radio
#endif // _STATISTICS_SLIDINGMINMAX_HPP_
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#include "SlidingMinMax.hpp"
template <typename T>
SlidingMinMax<T>::SlidingMinMax(Mode mode, size_t L, T P)
: m_mode(mode)
, m_L(L)
, m_P(P)
, m_N(0)
, m_win_value(0)
, m_win_index(0)
{
m_pP.resize(L);
m_pP_last.resize(L);
m_pU.resize(L);
m_pU_last.resize(L);
m_pP = 0;
m_pP_last = 0;
m_pU = T(0);
m_pU_last = T(0);
m_pU_last[1] = P;
m_mode_value = 1.0;
if (mode == Mode::Min)
{
m_mode_value = -1.0;
}
}
template <typename T>
SlidingMinMax<T>::~SlidingMinMax()
{
}
template <typename T>
void SlidingMinMax<T>::process(T const &xin)
{
T x = xin*m_mode_value;
size_t m = 1;
if (m_pP_last[m_N] == m_L)
{
m = 0;
m_pU_last[m_N] = m_P;
}
size_t i = 0;
while (x >= m_pU_last[i+1])
{
i++;
}
m_N = m_N - i + m;
for (size_t j=1; j < m_N; j++)
{
m_pU[j+1] = m_pU_last[j+i];
m_pP[j+1] = m_pP_last[j+i] + 1;
}
m_pU[m_N+1] = m_P;
m_pU[1] = x;
m_pP[1] = 1;
i=0;
while(m_pU[i] != m_P)
{
m_pU_last[i] = m_pU[i];
m_pP_last[i] = m_pP[i];
i++;
}
m_pU_last[i] = m_pU[i];
m_pP_last[i] = m_pP[i];
m_win_value = m_pU[m_N];
m_win_index = m_pP[m_N];
}