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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. Calling `spawn(n) <spawn>` will
create ``n`` 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 use
`SeedSequence.entropy` to log/pickle the `entropy` 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
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