# SFC64 Small Fast Chaotic PRNG#

class numpy.random.SFC64(seed=None)#

BitGenerator for Chris Doty-Humphrey’s Small Fast Chaotic PRNG.

Parameters
seed{None, int, array_like[ints], SeedSequence}, optional

A seed to initialize the BitGenerator. If None, then fresh, unpredictable entropy will be pulled from the OS. If an int or array_like[ints] is passed, then it will be passed to SeedSequence to derive the initial BitGenerator state. One may also pass in a SeedSequence instance.

Notes

SFC64 is a 256-bit implementation of Chris Doty-Humphrey’s Small Fast Chaotic PRNG ([1]). SFC64 has a few different cycles that one might be on, depending on the seed; the expected period will be about $$2^{255}$$ ([2]). SFC64 incorporates a 64-bit counter which means that the absolute minimum cycle length is $$2^{64}$$ and that distinct seeds will not run into each other for at least $$2^{64}$$ iterations.

SFC64 provides a capsule containing function pointers that produce doubles, and unsigned 32 and 64- bit integers. These are not directly consumable in Python and must be consumed by a Generator or similar object that supports low-level access.

State and Seeding

The SFC64 state vector consists of 4 unsigned 64-bit values. The last is a 64-bit counter that increments by 1 each iteration.

The input seed is processed by SeedSequence to generate the first 3 values, then the SFC64 algorithm is iterated a small number of times to mix.

Compatibility Guarantee

SFC64 makes a guarantee that a fixed seed will always produce the same random integer stream.

References

1

“PractRand”

2

“Random Invertible Mapping Statistics”

## State#

 state Get or set the PRNG state

## Extending#

 cffi CFFI interface ctypes ctypes interface