bundles / numpy latest / numpy / random / _sfc64 / SFC64
class
numpy.random._sfc64:SFC64
source: build-install/usr/lib/python3.14/site-packages/numpy/random/_sfc64.cpython-314-x86_64-linux-gnu.so
Signature
class SFC64 ( seed = None ) Members
Summary
BitGenerator for Chris Doty-Humphrey's Small Fast Chaotic PRNG.
Parameters
seed: {None, int, array_like[ints], SeedSequence}, optionalA seed to initialize the BitGenerator. If None, then fresh, unpredictable entropy will be pulled from the OS. If an
intorarray_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]). SFC64 incorporates a 64-bit counter which means that the absolute minimum cycle length is and that distinct seeds will not run into each other for at least 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.
Aliases
-
numpy.random.SFC64