numpy.random.SeedSequence¶

class
numpy.random.
SeedSequence
(entropy=None, *, spawn_key=(), pool_size=4)¶ SeedSequence mixes sources of entropy in a reproducible way to set the initial state for independent and very probably nonoverlapping BitGenerators.
Once the SeedSequence is instantiated, you can call the
generate_state
method to get an appropriately sized seed. Callingspawn(n)
will createn
SeedSequences that can be used to seed independent BitGenerators, i.e. for different threads.Parameters:  entropy : {None, int, sequence[int]}, optional
The entropy for creating a
SeedSequence
. spawn_key : {(), sequence[int]}, optional
A third source of entropy, used internally when calling
SeedSequence.spawn
 pool_size : {int}, optional
Size of the pooled entropy to store. Default is 4 to give a 128bit entropy pool. 8 (for 256 bits) is another reasonable choice if working with larger PRNGs, but there is very little to be gained by selecting another value.
 n_children_spawned : {int}, optional
The number of children already spawned. Only pass this if reconstructing a
SeedSequence
from a serialized form.
Notes
Best practice for achieving reproducible bit streams is to use the default
None
for the initial entropy, and then useSeedSequence.entropy
to log/pickle theentropy
for reproducibility:>>> sq1 = np.random.SeedSequence() >>> sq1.entropy 243799254704924441050048792905230269161 # random >>> sq2 = np.random.SeedSequence(sq1.entropy) >>> np.all(sq1.generate_state(10) == sq2.generate_state(10)) True
Attributes:  entropy
 n_children_spawned
 pool
 pool_size
 spawn_key
 state
Methods
generate_state
(n_words[, dtype])Return the requested number of words for PRNG seeding. spawn
(n_children)Spawn a number of child SeedSequence
s by extending thespawn_key
.