GY-63_MS5611/libraries/Correlation/Correlation.cpp

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//
// FILE: Correlation.cpp
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// AUTHOR: Rob Tillaart
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// VERSION: 0.2.3
// PURPOSE: Arduino Library to determine correlation between X and Y dataset
//
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// HISTORY: see cjhangelog.md
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#include "Correlation.h"
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Correlation::Correlation(uint8_t size)
{
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_size = 20;
if (size > 0) _size = size;
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_x = (float *) malloc(_size * sizeof(float));
_y = (float *) malloc(_size * sizeof(float));
clear();
}
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Correlation::~Correlation()
{
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if (_x) free(_x);
if (_y) free(_y);
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}
void Correlation::clear()
{
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_count = 0;
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_index = 0;
_needRecalculate = true;
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_runningMode = false;
_avgX = 0;
_avgY = 0;
_a = 0;
_b = 0;
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_div_b = -1; // as 1/_b is undefined
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_r = 0;
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_sumErrorSquare = 0;
_sumXiYi = 0;
_sumXi2 = 0;
_sumYi2 = 0;
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_doR2 = true;
_doE2 = true;
}
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bool Correlation::add(float x, float y)
{
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if ( (_count < _size) || _runningMode)
{
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_x[_index] = x;
_y[_index] = y;
_index++;
if (_index >= _size) _index = 0;
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if (_count < _size) _count++;
_needRecalculate = true;
return true;
}
return false;
}
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bool Correlation::calculate(bool forced)
{
if (_count == 0) return false;
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if (! (_needRecalculate || forced)) return true;
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// CALC AVERAGE X, AVERAGE Y
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float avgx = 0;
float avgy = 0;
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float div_count = 1.0 / _count; // speed up averaging
for (uint8_t i = 0; i < _count; i++)
{
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avgx += _x[i];
avgy += _y[i];
}
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avgx *= div_count;
avgy *= div_count;
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_avgX = avgx;
_avgY = avgy;
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// CALC A and B ==> formula Y = A + B * X
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float sumXiYi = 0;
float sumXi2 = 0;
float sumYi2 = 0;
for (uint8_t i = 0; i < _count; i++)
{
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float xi = _x[i] - avgx;
float yi = _y[i] - avgy;
sumXiYi += (xi * yi);
sumXi2 += (xi * xi);
sumYi2 += (yi * yi);
}
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float b = sumXiYi / sumXi2;
float a = avgy - b * avgx;
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_a = a;
_b = b;
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_div_b = 1.0 / b;
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_sumXiYi = sumXiYi;
_sumXi2 = sumXi2;
_sumYi2 = sumYi2;
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if (_doR2 == true)
{
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// R is calculated instead of rSquared so we do not loose the sign.
// Rsquared from R is much faster than R from Rsquared.
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_r = sumXiYi / sqrt(sumXi2 * sumYi2);
}
if (_doE2 == true)
{
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float sumErrorSquare = 0;
for (uint8_t i = 0; i < _count; i++)
{
float EY = a + b * _x[i];
float ei = _y[i] - EY;
sumErrorSquare += (ei * ei);
}
_sumErrorSquare = sumErrorSquare;
}
_needRecalculate = false;
return true;
}
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float Correlation::getEstimateY(float x)
{
if (_count == 0) return NAN;
if (_needRecalculate) calculate();
return _a + _b * x;
}
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float Correlation::getEstimateX(float y)
{
if (_count == 0) return NAN;
if (_needRecalculate) calculate();
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return (y - _a) * _div_b;
}
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//////////////////////////////////////////////////////
//
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// STATISTICAL
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//
float Correlation::getMaxX()
{
if (_count == 0) return NAN;
float rv = _x[0];
for (uint8_t i = 1; i < _count; i++)
{
if (_x[i] > rv) rv = _x[i];
}
return rv;
}
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float Correlation::getMinX()
{
if (_count == 0) return NAN;
float rv = _x[0];
for (uint8_t i = 1; i < _count; i++)
{
if (_x[i] < rv) rv = _x[i];
}
return rv;
}
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float Correlation::getMaxY()
{
if (_count == 0) return NAN;
float rv = _y[0];
for (uint8_t i = 1; i < _count; i++)
{
if (_y[i] > rv) rv = _y[i];
}
return rv;
}
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float Correlation::getMinY()
{
if (_count == 0) return NAN;
float rv = _y[0];
for (uint8_t i = 1; i < _count; i++)
{
if (_y[i] < rv) rv = _y[i];
}
return rv;
}
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//////////////////////////////////////////////////////
//
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// DEBUGGING - access to internal arrays.
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//
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bool Correlation::setXY(uint8_t index, float x, float y)
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{
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if (index >= _count) return false;
_x[index] = x;
_y[index] = y;
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_needRecalculate = true;
return true;
}
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bool Correlation::setX(uint8_t index, float x)
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{
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if (index >= _count) return false;
_x[index] = x;
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_needRecalculate = true;
return true;
}
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float Correlation::getX(uint8_t index)
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{
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if (index >= _count) return NAN;
return _x[index];
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}
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bool Correlation::setY(uint8_t index, float y)
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{
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if (index >= _count) return false;
_y[index] = y;
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_needRecalculate = true;
return true;
}
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float Correlation::getY(uint8_t index)
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{
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if (index > _count) return NAN;
return _y[index];
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}
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// -- END OF FILE --
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