-
Notifications
You must be signed in to change notification settings - Fork 1
/
laplace.js
182 lines (162 loc) · 4.44 KB
/
laplace.js
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
// @flow
/**
* Laplace distribution
* This is continuous distribution
* https://en.wikipedia.org/wiki/Laplace_distribution
* @param mu <number> - location, any value
* @param b <number> - scale, b > 0
* @returns Laplace distributed number
* Created by Alexey S. Kiselev
*/
import type { MethodError, RandomArray } from '../types';
import type { IDistribution } from '../interfaces';
import prng from '../prng/prngProxy';
class Laplace implements IDistribution {
location: number;
scale: number;
constructor(mu: number, b: number): void {
this.location = Number(mu);
this.scale = Number(b);
}
/**
* Generates a random number
* @returns a Laplace distributed number
*/
random(): number {
let u: number = (prng.random(): any);
return this._random(u);
}
/**
* Generates next seeded random number
* @returns {number}
*/
next(): number {
return this._random(prng.next());
}
_random(u: number): number {
if(u <= 0.5){
return this.location + this.scale * Math.log(2 * u);
}
return this.location - this.scale * Math.log(2 * (1 - u));
}
/**
* Generates Laplace distributed numbers
* @param n: number - Number of elements in resulting array, n > 0
* @returns Array<number> - Laplace distributed numbers
*/
distribution(n: number): RandomArray {
let laplaceArray: RandomArray = [],
random: RandomArray = (prng.random(n): any);
for(let i: number = 0; i < n; i += 1){
laplaceArray[i] = this._random(random[i]);
}
return laplaceArray;
}
/**
* Error handling
* @returns {boolean}
*/
isError(): MethodError {
if((!this.location && this.location !== 0) || !this.scale) {
return {error: 'Laplace distribution: you should point parameters "mu" and "b" (scale) with numerical values'};
}
if(this.scale <= 0){
return {error: 'Laplace distribution: parameter "b" (scale) must be a positive number'};
}
return { error: false };
}
/**
* Refresh method
* @param newMu: number - new parameter "mu"
* @param newB: number - new parameter "b"
* This method does not return values
*/
refresh(newMu: number, newB: number): void {
this.location = Number(newMu);
this.scale = Number(newB);
}
/**
* Class .toString method
* @returns {string}
*/
toString(): string {
let info = [
'Laplace Distribution',
`Usage: unirand.laplace(${this.location}, ${this.scale}).random()`
];
return info.join('\n');
}
/**
* Mean value
* Information only
* For calculating real mean value use analyzer
*/
get mean(): number {
return this.location;
}
/**
* Median value
* Information only
* For calculating real median value use analyzer
*/
get median(): number {
return this.location;
}
/**
* Mode value - value, which appears most often
* Information only
* For calculating real mode value use analyzer
*/
get mode(): number {
return this.location;
}
/**
* Variance value
* Information only
* For calculating real variance value use analyzer
*/
get variance(): number {
return 2 * Math.pow(this.scale, 2);
}
/**
* Skewness value
* Information only
* For calculating real skewness value use analyzer
*/
get skewness(): number {
return 0;
}
/**
* Kurtosis value
* Information only
* For calculating real kurtosis value use analyzer
*/
get kurtosis(): number {
return 3;
}
/**
* Entropy value
* Information only
* This formula uses Euler's number (base of natural logarithm)
* For calculating real entropy value use analyzer
*/
get entropy(): number {
return Math.log(2 * this.scale * 2.71828182845904523536);
}
/**
* All parameters of distribution in one object
* Information only
*/
get parameters(): {} {
return {
mean: this.mean,
median: this.median,
mode: this.mode,
variance: this.variance,
skewness: this.skewness,
entropy: this.entropy,
kurtosis: this.kurtosis
};
}
}
module.exports = Laplace;