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 non-overlapping 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 128-bit 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
.