-
-
Notifications
You must be signed in to change notification settings - Fork 1
/
Correlation.cpp
264 lines (215 loc) · 4.56 KB
/
Correlation.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
//
// FILE: Correlation.cpp
// AUTHOR: Rob Tillaart
// VERSION: 0.3.2
// PURPOSE: Arduino Library to determine correlation between X and Y dataset
// URL: https://github.com/RobTillaart/Correlation
#include "Correlation.h"
Correlation::Correlation(uint8_t size)
{
_size = 20;
if (size > 0) _size = size;
_x = (float *) malloc(_size * sizeof(float));
_y = (float *) malloc(_size * sizeof(float));
clear();
}
Correlation::~Correlation()
{
if (_x) free(_x);
if (_y) free(_y);
}
void Correlation::clear()
{
_count = 0;
_index = 0;
_needRecalculate = true;
_runningMode = false;
_avgX = 0;
_avgY = 0;
_a = 0;
_b = 0;
_div_b = -1; // as 1/_b is undefined
_r = 0;
_sumErrorSquare = 0;
_sumXiYi = 0;
_sumXi2 = 0;
_sumYi2 = 0;
_doR2 = true;
_doE2 = true;
}
bool Correlation::add(float x, float y)
{
if ( (_count < _size) || _runningMode)
{
_x[_index] = x;
_y[_index] = y;
_index++;
if (_index >= _size) _index = 0;
if (_count < _size) _count++;
_needRecalculate = true;
return true;
}
return false;
}
bool Correlation::calculate(bool forced)
{
if (_count == 0) return false;
if (! (_needRecalculate || forced)) return true;
// CALC AVERAGE X, AVERAGE Y
float avgx = 0;
float avgy = 0;
float div_count = 1.0 / _count; // speed up averaging
for (uint8_t i = 0; i < _count; i++)
{
avgx += _x[i];
avgy += _y[i];
}
avgx *= div_count;
avgy *= div_count;
_avgX = avgx;
_avgY = avgy;
// CALC A and B ==> formula Y = A + B * X
float sumXiYi = 0;
float sumXi2 = 0;
float sumYi2 = 0;
for (uint8_t i = 0; i < _count; i++)
{
float xi = _x[i] - avgx;
float yi = _y[i] - avgy;
sumXiYi += (xi * yi);
sumXi2 += (xi * xi);
sumYi2 += (yi * yi);
}
float b = sumXiYi / sumXi2;
float a = avgy - b * avgx;
_a = a;
_b = b;
_div_b = 1.0 / b;
_sumXiYi = sumXiYi;
_sumXi2 = sumXi2;
_sumYi2 = sumYi2;
if (_doR2 == true)
{
// R is calculated instead of rSquared so we do not loose the sign.
// Rsquared from R is much faster than R from Rsquared.
_r = sumXiYi / sqrt(sumXi2 * sumYi2);
}
if (_doE2 == true)
{
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;
}
float Correlation::getEstimateY(float x)
{
if (_count == 0) return NAN;
if (_needRecalculate) calculate();
return _a + _b * x;
}
float Correlation::getEstimateX(float y)
{
if (_count == 0) return NAN;
if (_needRecalculate) calculate();
return (y - _a) * _div_b;
}
//////////////////////////////////////////////////////
//
// STATISTICAL
//
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;
}
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;
}
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;
}
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;
}
//////////////////////////////////////////////////////
//
// DEBUGGING - access to internal arrays.
//
bool Correlation::setXY(uint8_t index, float x, float y)
{
if (index >= _count) return false;
_x[index] = x;
_y[index] = y;
_needRecalculate = true;
return true;
}
bool Correlation::setX(uint8_t index, float x)
{
if (index >= _count) return false;
_x[index] = x;
_needRecalculate = true;
return true;
}
float Correlation::getX(uint8_t index)
{
if (index >= _count) return NAN;
return _x[index];
}
bool Correlation::setY(uint8_t index, float y)
{
if (index >= _count) return false;
_y[index] = y;
_needRecalculate = true;
return true;
}
float Correlation::getY(uint8_t index)
{
if (index > _count) return NAN;
return _y[index];
}
float Correlation::getSumXY()
{
return _sumXiYi;
}
float Correlation::getSumX2()
{
return _sumXi2;
}
float Correlation::getSumY2()
{
return _sumYi2;
}
// -- END OF FILE --