64-bit Mersenne Twister

class randomgen.mt64.MT64(seed=None, *, mode=None)

Container for the 64-bit Mersenne Twister pseudo-random number generator

Parameters:
seed=None

Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**64 - 1 inclusive, an array (or other sequence) of unsigned 64-bit integers, a SeedSequence instance or None (the default). If seed is None, then 312 64-bit unsigned integers are read from /dev/urandom (or the Windows analog) if available. If unavailable, a hash of the time and process ID is used.

mode=None

The seeding mode to use. “legacy” uses the legacy SplitMix64-based initialization. “sequence” uses a SeedSequence to transforms the seed into an initial state. None defaults to “sequence”.

lock

Lock instance that is shared so that the same bit git generator can be used in multiple Generators without corrupting the state. Code that generates values from a bit generator should hold the bit generator’s lock.

Type:

threading.Lock

seed_seq

The SeedSequence instance used to initialize the generator if mode is “sequence” or is seed is a SeedSequence. None if mode is “legacy”.

Type:

{None, SeedSequence}

Notes

MT64 provides a capsule containing function pointers that produce doubles, and unsigned 32 and 64- bit integers ([1], [2]). These are not directly consumable in Python and must be consumed by a Generator or similar object that supports low-level access.

The Python stdlib module “random” also contains a Mersenne Twister pseudo-random number generator.

State and Seeding

The MT64 state vector consists of a 312-element array of 64-bit unsigned integers plus a single integer value between 0 and 312 that indexes the current position within the main array.

MT64 is seeded using either a single 64-bit unsigned integer or a vector of 64-bit unsigned integers. In either case, the input seed is used as an input (or inputs) for a hashing function, and the output of the hashing function is used as the initial state. Using a single 64-bit value for the seed can only initialize a small range of the possible initial state values.

Compatibility Guarantee

MT64 makes a guarantee that a fixed seed and will always produce the same random integer stream.

References

Seeding and State

seed([seed])

Seed the generator

state

Get or set the PRNG state

Extending

cffi

CFFI interface

ctypes

ctypes interface

Testing

random_raw([size, output])

Return randoms as generated by the underlying BitGenerator