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/* eslint-disable no-bitwise */
/*
This implementation of the Mersenne Twister is a port of the a
C implementation, by Takuji Nishimura and Makoto Matsumoto.
*/
/*
A C-program for MT19937, with initialization improved 2002/1/26.
Coded by Takuji Nishimura and Makoto Matsumoto.
Before using, initialize the state by using init_genrand(seed)
or init_by_array(init_key, key_length).
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Any feedback is very welcome.
[Mersenne Twister](https://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html)
email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
*/
/* Period parameters */
/**
* The size of the state vector for the Mersenne Twister algorithm.
*/
const N = 624;
/**
* The middle word, an offset used in the recurrence relation defining the series x, 1 ≤ m \< n
*/
const M = 397;
/**
* Constant vector a
*/
const MATRIX_A = 0x9908b0df;
/**
* Most significant w-r bits
*/
const UPPER_MASK = 0x80000000;
/**
* Least significant r bits
*/
const LOWER_MASK = 0x7fffffff;
/**
* Lookup table used in the Mersenne Twister algorithm for conditional XOR operations.
*/
const MAG01 = [0, MATRIX_A];
/**
* Generates a default seed value based on the current time.
*
* The seed is calculated as the sum of the current minute (in milliseconds),
* the current second (in milliseconds), and the current millisecond value.
* This provides a pseudo-random seed that changes every millisecond.
* @returns A number representing the seed value derived from the current time.
* @internal
*/
function defaultSeed(): number {
const currentDate = new Date();
return (
currentDate.getMinutes() * 60000 +
currentDate.getSeconds() * 1000 +
currentDate.getMilliseconds()
);
}
/**
* Implements the Mersenne Twister pseudorandom number generator (MT19937).
*
* The Mersenne Twister is a widely used PRNG known for its long period (2^19937−1),
* high performance, and high-quality randomness. This class provides methods to seed
* the generator and produce random numbers in various formats and intervals.
* @remarks
* - The generator can be seeded with a single number or an array of numbers.
* - Methods are provided to generate 32-bit and 31-bit integers, as well as floating-point numbers
* in different intervals.
* - This implementation is based on the original C code by Makoto Matsumoto and Takuji Nishimura.
*
* @example
* ```typescript
* const mt = new MersenneTwister(1234);
* mt.genrandInt32(); // 1982695502
* mt.genrandReal1(); // 0.33979119391641377
* mt.genrandReal2(); // 0.006705045932903886
* mt.genrandRes53(); // 0.489361593755425
* ```
*
* @see https://en.wikipedia.org/wiki/Mersenne_Twister
* @see http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
* @group Random
* @category Number Generation
*/
export class MersenneTwister {
private mti = N + 1; /* the array for the state vector */
private mt = new Uint32Array(N);
public constructor(seed: number | number[] = defaultSeed()) {
this.setSeed(seed);
}
/**
* Sets the seed for the random number generator.
*/
public setSeed(seed: number | number[]): void {
if (typeof seed === 'number') {
this.initGenrand(seed);
} else {
this.initByArray(seed);
}
}
/** initialize with a seed */
public initGenrand(seed: number): void {
this.mt[0] = seed;
this.mti = 1;
for (this.mti = 1; this.mti < N; ++this.mti) {
this.mt[this.mti] =
1812433253 * (this.mt[this.mti - 1] ^ (this.mt[this.mti - 1] >>> 30)) + this.mti;
}
// cspell:ignore TAOCP
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
}
/** initialize with array */
public initByArray(key: number[]): void {
this.initGenrand(19650218);
let i = 1;
let j = 0;
for (let k = Math.min(key.length, N); k; --k) {
this.mt[i] =
(this.mt[i] ^ ((this.mt[i - 1] ^ (this.mt[i - 1] >>> 30)) * 1664525)) +
key[j] +
j; /* non linear */
i++;
j++;
if (i >= N) {
this.mt[0] = this.mt[N - 1];
i = 1;
}
if (j >= key.length) {
j = 0;
}
}
for (let k = N - 1; k; --k) {
this.mt[i] =
(this.mt[i] ^ ((this.mt[i - 1] ^ (this.mt[i - 1] >> 30)) * 1566083941)) -
i; /* non linear */
if (++i >= N) {
this.mt[0] = this.mt[N - 1];
i = 1;
}
}
this.mt[0] = 0x80000000; /* MSB is 1; assuring non-zero initial array */
}
/** generates a random number on [0,0xffffffff]-interval */
public genrandInt32(): number {
let y;
if (this.mti >= N) {
let kk;
for (kk = 0; kk < N - M; ++kk) {
y = (this.mt[kk] & UPPER_MASK) | (this.mt[kk + 1] & LOWER_MASK);
this.mt[kk] = this.mt[kk + M] ^ (y >> 1) ^ MAG01[y & 0x1];
}
for (; kk < N - 1; ++kk) {
y = (this.mt[kk] & UPPER_MASK) | (this.mt[kk + 1] & LOWER_MASK);
this.mt[kk] = this.mt[kk + (M - N)] ^ (y >> 1) ^ MAG01[y & 0x1];
}
y = (this.mt[N - 1] & UPPER_MASK) | (this.mt[0] & LOWER_MASK);
this.mt[N - 1] = this.mt[M - 1] ^ (y >> 1) ^ MAG01[y & 0x1];
this.mti = 0;
}
y = this.mt[this.mti++];
/* Tempering */
y ^= y >> 11;
y ^= (y << 7) & 0x9d2c5680;
y ^= (y << 15) & 0xefc60000;
y ^= y >> 18;
return y;
}
/** generates a random number on [0,0x7fffffff]-interval */
public genrandInt31(): number {
return this.genrandInt32() >>> 1;
}
/** generates a random number on [0,1]-real-interval */
public genrandReal1(): number {
return this.genrandInt32() / 4294967295.0;
/* divided by 2^32-1 */
}
/** generates a random number on [0,1)-real-interval */
public genrandReal2(): number {
return this.genrandInt32() / 4294967296.0;
/* divided by 2^32 */
}
/** generates a random number on (0,1)-real-interval */
public genrandReal3(): number {
return (this.genrandInt32() + 0.5) / 4294967296.0;
/* divided by 2^32 */
}
/** generates a random number on [0,1) with 53-bit resolution*/
public genrandRes53(): number {
const a = this.genrandInt32() >> 5;
const b = this.genrandInt32() >> 6;
return (a * 67108864.0 + b) / 9007199254740992.0;
}
/* These real versions are due to Isaku Wada, 2002/01/09 added */
}
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