SFC64 Generator¶

class randomgen.sfc.SFC64(seed=
None
, w=1
, k=1
, *, mode='sequence'
)¶ Chris DotyHumphrey’s Small Fast Chaotic PRNG with optional Weyl Sequence
 Parameters:¶
 seed=
None
¶ A seed to initialize the BitGenerator. If None, then fresh, unpredictable entropy will be pulled from the OS. If an
int
orarray_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. w=
1
¶ The starting value of the Weyl sequence. If None, then the initial value is generated from the SeedSequence.
 k=
1
¶ The increment to the Weyl sequence. Must be odd, and if even, 1 is added. If None, then k is generated from the `SeedSequence.
 mode=
'sequence'
¶ The default uses a seed sequence to initialize all unspecified values. When using “numpy” uses the seed sequence to initialize three values and checks that both w and k are 1.
 seed=
Notes
SFC64
is a 256bit implementation of Chris DotyHumphrey’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 64bit 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 aGenerator
or similar object that supports lowlevel access.State and Seeding
The
SFC64
state vector consists of 4 unsigned 64bit values. The last is a 64bit counter that increments by 1 each iteration. The input seed is processed by SeedSequence to generate the first 3 values, then theSFC64
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.Examples
SFC64
supports generating distinct streams using different Weyl increments. The recommend practice is to chose a set of distinct odd coefficients that have 32 or fewer bits set of 1 (i.e., <= 50%).>>> import numpy as np >>> from randomgen import SFC64, SeedSequence >>> NUM_STREAMS = 8196 >>> seed_seq = SeedSequence(325874985469) >>> bit_gen = SFC64(seed_seq) >>> weyl_inc = bit_gen.weyl_increments(NUM_STREAMS) >>> streams = [SFC64(seed_seq, k=k) for k in list(weyl_inc)] >>> [stream.random_raw() for stream in streams[:3]] [13020151409549081939, 8062752282355435850, 13933250373249421220]
References
Seeding and State¶

Seed the generator 
Get or set the PRNG state 
Extending¶
CFFI interface 

ctypes interface 
Testing¶

Return randoms as generated by the underlying BitGenerator 
Parallelization¶

Generate distinct Weyl increments to construct multiple streams 