# Mersenne Twister > A 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator.
## Usage ```javascript var mt19937 = require( '@stdlib/random/base/mt19937' ); ``` #### mt19937() Returns a pseudorandom integer on the interval `[1, 4294967295]`. ```javascript var r = mt19937(); // returns ``` #### mt19937.normalized() Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision. ```javascript var r = mt19937.normalized(); // returns ``` #### mt19937.factory( \[options] ) Returns a 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator. ```javascript var rand = mt19937.factory(); ``` The function accepts the following `options`: - **seed**: pseudorandom number generator seed. - **state**: a [`Uint32Array`][@stdlib/array/uint32] containing pseudorandom number generator state. If provided, the function ignores the `seed` option. - **copy**: `boolean` indicating whether to copy a provided pseudorandom number generator state. Setting this option to `false` allows sharing state between two or more pseudorandom number generators. Setting this option to `true` ensures that a returned generator has exclusive control over its internal state. Default: `true`. By default, a random integer is used to seed the returned generator. To seed the generator, provide either an `integer` on the interval `[1, 4294967295]` ```javascript var rand = mt19937.factory({ 'seed': 1234 }); var r = rand(); // returns 822569775 ``` or, for arbitrary length seeds, an array-like `object` containing unsigned 32-bit integers ```javascript var Uint32Array = require( '@stdlib/array/uint32' ); var rand = mt19937.factory({ 'seed': new Uint32Array( [ 291, 564, 837, 1110 ] ) }); var r = rand(); // returns 1067595299 ``` To return a generator having a specific initial state, set the generator `state` option. ```javascript var rand; var bool; var r; var i; // Generate pseudorandom numbers, thus progressing the generator state: for ( i = 0; i < 1000; i++ ) { r = mt19937(); } // Create a new MT19937 PRNG initialized to the current state of `mt19937`: rand = mt19937.factory({ 'state': mt19937.state }); // Test that the generated pseudorandom numbers are the same: bool = ( rand() === mt19937() ); // returns true ``` #### mt19937.NAME The generator name. ```javascript var str = mt19937.NAME; // returns 'mt19937' ``` #### mt19937.MIN Minimum possible value. ```javascript var min = mt19937.MIN; // returns 1 ``` #### mt19937.MAX Maximum possible value. ```javascript var max = mt19937.MAX; // returns 4294967295 ``` #### mt19937.seed The value used to seed `mt19937()`. ```javascript var rand; var r; var i; // Generate pseudorandom values... for ( i = 0; i < 100; i++ ) { r = mt19937(); } // Generate the same pseudorandom values... rand = mt19937.factory({ 'seed': mt19937.seed }); for ( i = 0; i < 100; i++ ) { r = rand(); } ``` #### mt19937.seedLength Length of generator seed. ```javascript var len = mt19937.seedLength; // returns ``` #### mt19937.state Writable property for getting and setting the generator state. ```javascript var r = mt19937(); // returns r = mt19937(); // returns // ... // Get a copy of the current state: var state = mt19937.state; // returns r = mt19937(); // returns r = mt19937(); // returns // Reset the state: mt19937.state = state; // Replay the last two pseudorandom numbers: r = mt19937(); // returns r = mt19937(); // returns // ... ``` #### mt19937.stateLength Length of generator state. ```javascript var len = mt19937.stateLength; // returns ``` #### mt19937.byteLength Size (in bytes) of generator state. ```javascript var sz = mt19937.byteLength; // returns ``` #### mt19937.toJSON() Serializes the pseudorandom number generator as a JSON object. ```javascript var o = mt19937.toJSON(); // returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] } ```
## Notes - [Mersenne Twister][mersenne-twister] is **not** a cryptographically secure PRNG, as the PRNG is based on a linear recursion. Any pseudorandom number sequence generated by a linear recursion is **insecure**, due to the fact that one can predict future generated outputs by observing a sufficiently long subsequence of generated values. - Compared to other PRNGs, [Mersenne Twister][mersenne-twister] has a large state size (`~2.5kB`). Because of the large state size, beware of increased memory consumption when using the `factory()` method to create many [Mersenne Twister][mersenne-twister] PRNGs. When appropriate (e.g., when external state mutation is not a concern), consider sharing PRNG state. - A seed array of length `1` is considered **equivalent** to an integer seed equal to the lone seed array element and vice versa. - If PRNG state is "shared" (meaning a state array was provided during PRNG creation and **not** copied) and one sets the generator state to a state array having a different length, the PRNG does **not** update the existing shared state and, instead, points to the newly provided state array. In order to synchronize PRNG output according to the new shared state array, the state array for **each** relevant PRNG must be **explicitly** set. - If PRNG state is "shared" and one sets the generator state to a state array of the same length, the PRNG state is updated (along with the state of all other PRNGs sharing the PRNG's state array). - The PRNG has a period of `2^19937 - 1`.
## Examples ```javascript var mt19937 = require( '@stdlib/random/base/mt19937' ); var seed; var rand; var i; // Generate pseudorandom numbers... for ( i = 0; i < 100; i++ ) { console.log( mt19937() ); } // Create a new pseudorandom number generator... seed = 1234; rand = mt19937.factory({ 'seed': seed }); for ( i = 0; i < 100; i++ ) { console.log( rand() ); } // Create another pseudorandom number generator using a previous seed... rand = mt19937.factory({ 'seed': mt19937.seed }); for ( i = 0; i < 100; i++ ) { console.log( rand() ); } ```
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## References - Matsumoto, Makoto, and Takuji Nishimura. 1998. "Mersenne Twister: A 623-dimensionally Equidistributed Uniform Pseudo-random Number Generator." _ACM Transactions on Modeling and Computer Simulation_ 8 (1). New York, NY, USA: ACM: 3–30. doi:[10.1145/272991.272995][@matsumoto:1998a]. - Harase, Shin. 2017. "Conversion of Mersenne Twister to double-precision floating-point numbers." _ArXiv_ abs/1708.06018 (September). .