mirror of
https://github.com/RobTillaart/Arduino.git
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221 lines
4.0 KiB
C++
221 lines
4.0 KiB
C++
//
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// FILE: Correlation.cpp
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// AUTHOR: Rob Tillaart
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// VERSION: 0.1.3
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// PURPOSE: Arduino Library to determine correlation between X and Y dataset
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//
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// HISTORY:
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// 0.1.3 2021-01-16 add size in constructor,
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// add statistical + debug functions
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// 0.1.2 2020-12-17 add arduino-CI + unit tests
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// + size() + getAvgX() + getAvgY()
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// 0.1.1 2020-06-05 fix library.json
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// 0.1.0 2020-05-17 initial version
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#include "Correlation.h"
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Correlation::Correlation(uint8_t size)
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{
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_size = size;
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_x = (float *) malloc(_size * sizeof(float));
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_y = (float *) malloc(_size * sizeof(float));
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clear();
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}
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Correlation::~Correlation()
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{
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free(_x);
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free(_y);
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}
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void Correlation::clear()
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{
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_count = 0;
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_idx = 0;
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_needRecalculate = true;
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_runningMode = false;
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_avgX = 0;
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_avgY = 0;
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_a = 0;
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_b = 0;
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_rSquare = 0;
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_sumErrorSquare = 0;
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_sumXiYi = 0;
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_sumXi2 = 0;
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_sumYi2 = 0;
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}
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bool Correlation::add(float x, float y)
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{
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if ( (_count < _size) || _runningMode)
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{
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_x[_idx] = x;
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_y[_idx] = y;
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_idx++;
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if (_idx >= _size) _idx = 0;
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if (_count < _size) _count++;
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_needRecalculate = true;
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return true;
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}
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return false;
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}
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bool Correlation::calculate()
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{
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if (_count == 0) return false;
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if (!_needRecalculate) return true;
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// CALC AVERAGE X, AVERAGE Y
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_avgX = 0;
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_avgY = 0;
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for (uint8_t i = 0; i < _count; i++)
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{
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_avgX += _x[i];
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_avgY += _y[i];
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}
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_avgX /= _count;
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_avgY /= _count;
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// CALC A and B ==> formula Y = A + B*X
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_sumXiYi = 0;
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_sumXi2 = 0;
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_sumYi2 = 0;
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for (uint8_t i = 0; i < _count; i++)
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{
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float xi = _x[i] - _avgX;
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float yi = _y[i] - _avgY;
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_sumXiYi += (xi * yi);
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_sumXi2 += (xi * xi);
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_sumYi2 += (yi * yi);
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}
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_b = _sumXiYi / _sumXi2;
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_a = _avgY - _b * _avgX;
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_rSquare = _sumXiYi * _sumXiYi / (_sumXi2 * _sumYi2);
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// CALC _sumErrorSquare
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_sumErrorSquare = 0;
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for (uint8_t i = 0; i < _count; i++)
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{
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float EY = _a + _b * _x[i];
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float ei = _y[i] - EY;
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_sumErrorSquare += (ei * ei);
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}
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_needRecalculate = false;
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return true;
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}
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float Correlation::getEstimateY(float x)
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{
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if (_count == 0) return NAN;
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if (_needRecalculate) calculate();
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return _a + _b * x;
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}
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float Correlation::getEstimateX(float y)
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{
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if (_count == 0) return NAN;
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if (_needRecalculate) calculate();
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return (y - _a) / _b;
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}
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//////////////////////////////////////////////////////
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//
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// STATISTICAL
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//
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float Correlation::getMaxX()
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{
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if (_count == 0) return NAN;
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float rv = _x[0];
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for (uint8_t i = 1; i < _count; i++)
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{
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if (_x[i] > rv) rv = _x[i];
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}
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return rv;
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}
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float Correlation::getMinX()
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{
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if (_count == 0) return NAN;
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float rv = _x[0];
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for (uint8_t i = 1; i < _count; i++)
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{
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if (_x[i] < rv) rv = _x[i];
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}
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return rv;
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}
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float Correlation::getMaxY()
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{
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if (_count == 0) return NAN;
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float rv = _y[0];
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for (uint8_t i = 1; i < _count; i++)
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{
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if (_y[i] > rv) rv = _y[i];
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}
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return rv;
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}
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float Correlation::getMinY()
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{
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if (_count == 0) return NAN;
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float rv = _y[0];
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for (uint8_t i = 1; i < _count; i++)
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{
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if (_y[i] < rv) rv = _y[i];
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}
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return rv;
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}
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//////////////////////////////////////////////////////
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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 idx, float x, float y)
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{
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if (idx >= _count) return false;
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_x[idx] = x;
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_y[idx] = y;
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_needRecalculate = true;
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return true;
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}
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bool Correlation::setX(uint8_t idx, float x)
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{
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if (idx >= _count) return false;
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_x[idx] = x;
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_needRecalculate = true;
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return true;
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}
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float Correlation::getX(uint8_t idx)
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{
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if (idx >= _count) return NAN;
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return _x[idx];
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}
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bool Correlation::setY(uint8_t idx, float y)
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{
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if (idx >= _count) return false;
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_y[idx] = y;
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_needRecalculate = true;
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return true;
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}
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float Correlation::getY(uint8_t idx)
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{
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if (idx > _count) return NAN;
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return _y[idx];
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}
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// -- END OF FILE --
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