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
|
<?php
/**
* Compute running mean, variance, and extrema of a stream of numbers.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along
* with this program; if not, write to the Free Software Foundation, Inc.,
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
* http://www.gnu.org/copyleft/gpl.html
*
* @file
* @ingroup Profiler
*/
// Needed due to PHP non-bug <https://bugs.php.net/bug.php?id=49828>.
define( 'NEGATIVE_INF', -INF );
/**
* Represents a running summary of a stream of numbers.
*
* RunningStat instances are accumulator-like objects that provide a set of
* continuously-updated summary statistics for a stream of numbers, without
* requiring that each value be stored. The measures it provides are the
* arithmetic mean, variance, standard deviation, and extrema (min and max);
* together they describe the central tendency and statistical dispersion of a
* set of values.
*
* One RunningStat instance can be merged into another; the resultant
* RunningStat has the state it would have had if it had accumulated each
* individual point. This allows data to be summarized in parallel and in
* stages without loss of fidelity.
*
* Based on a C++ implementation by John D. Cook:
* <http://www.johndcook.com/standard_deviation.html>
* <http://www.johndcook.com/skewness_kurtosis.html>
*
* The in-line documentation for this class incorporates content from the
* English Wikipedia articles "Variance", "Algorithms for calculating
* variance", and "Standard deviation".
*
* @since 1.23
*/
class RunningStat implements Countable {
/** @var int Number of samples. **/
public $n = 0;
/** @var float The first moment (or mean, or expected value). **/
public $m1 = 0.0;
/** @var float The second central moment (or variance). **/
public $m2 = 0.0;
/** @var float The least value in the the set. **/
public $min = INF;
/** @var float The most value in the set. **/
public $max = NEGATIVE_INF;
/**
* Count the number of accumulated values.
* @return int Number of values
*/
public function count() {
return $this->n;
}
/**
* Add a number to the data set.
* @param int|float $x Value to add
*/
public function push( $x ) {
$x = (float) $x;
$this->min = min( $this->min, $x );
$this->max = max( $this->max, $x );
$n1 = $this->n;
$this->n += 1;
$delta = $x - $this->m1;
$delta_n = $delta / $this->n;
$this->m1 += $delta_n;
$this->m2 += $delta * $delta_n * $n1;
}
/**
* Get the mean, or expected value.
*
* The arithmetic mean is the sum of all measurements divided by the number
* of observations in the data set.
*
* @return float Mean
*/
public function getMean() {
return $this->m1;
}
/**
* Get the estimated variance.
*
* Variance measures how far a set of numbers is spread out. A small
* variance indicates that the data points tend to be very close to the
* mean (and hence to each other), while a high variance indicates that the
* data points are very spread out from the mean and from each other.
*
* @return float Estimated variance
*/
public function getVariance() {
if ( $this->n === 0 ) {
// The variance of the empty set is undefined.
return NAN;
} elseif ( $this->n === 1 ) {
return 0.0;
} else {
return $this->m2 / ( $this->n - 1.0 );
}
}
/**
* Get the estimated stanard deviation.
*
* The standard deviation of a statistical population is the square root of
* its variance. It shows shows how much variation from the mean exists. In
* addition to expressing the variability of a population, the standard
* deviation is commonly used to measure confidence in statistical conclusions.
*
* @return float Estimated standard deviation
*/
public function getStdDev() {
return sqrt( $this->getVariance() );
}
/**
* Merge another RunningStat instance into this instance.
*
* This instance then has the state it would have had if all the data had
* been accumulated by it alone.
*
* @param RunningStat RunningStat instance to merge into this one
*/
public function merge( RunningStat $other ) {
// If the other RunningStat is empty, there's nothing to do.
if ( $other->n === 0 ) {
return;
}
// If this RunningStat is empty, copy values from other RunningStat.
if ( $this->n === 0 ) {
$this->n = $other->n;
$this->m1 = $other->m1;
$this->m2 = $other->m2;
$this->min = $other->min;
$this->max = $other->max;
return;
}
$n = $this->n + $other->n;
$delta = $other->m1 - $this->m1;
$delta2 = $delta * $delta;
$this->m1 = ( ( $this->n * $this->m1 ) + ( $other->n * $other->m1 ) ) / $n;
$this->m2 = $this->m2 + $other->m2 + ( $delta2 * $this->n * $other->n / $n );
$this->min = min( $this->min, $other->min );
$this->max = max( $this->max, $other->max );
$this->n = $n;
}
}
|