# MT19937
> Create an iterator for a 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator.
## Usage
```javascript
var iterator = require( '@stdlib/random/iter/mt19937' );
```
#### iterator( \[options] )
Returns an iterator for generating pseudorandom numbers via a 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator.
```javascript
var it = iterator();
// returns
## Notes
- If an environment supports `Symbol.iterator`, the returned iterator is iterable.
- [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.
- The PRNG has a period of `2^19937 - 1`.
- If PRNG state is "shared" (meaning a state array was provided during iterator creation and **not** copied) and one sets the underlying generator state to a state array having a different length, the iterator does **not** update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for **each** relevant iterator and/or PRNG must be **explicitly** set.
- If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other iterator and/or PRNGs sharing the PRNG's state array).
## Examples
```javascript
var iterator = require( '@stdlib/random/iter/mt19937' );
var it;
var r;
// Create a seeded iterator for generating pseudorandom numbers:
it = iterator({
'seed': 1234,
'iter': 10
});
// Perform manual iteration...
while ( true ) {
r = it.next();
if ( r.done ) {
break;
}
console.log( r.value );
}
```
* * *
## 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). .
[mersenne-twister]: https://en.wikipedia.org/wiki/Mersenne_Twister
[@matsumoto:1998a]: https://doi.org/10.1145/272991.272995
[@stdlib/array/uint32]: https://www.npmjs.com/package/@stdlib/array-uint32