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I have a suggestion for the seeding part. In NEP19, we recommend now to move away from the global state np.random.seed. Instead, the canonical way of using RNG is to use a generator with: rng = np.random.default_rng(seed_value). (Would be ok since you require a recent version of NumPy.)
This is especially important since in SciPy for e.g. we are not relying anymore on the global state but ask people to use the parameter random_state (sometimes called seed or rng depending on the function, sorry about the inconsistency, we are trying to resolve that slowly...).
The text was updated successfully, but these errors were encountered:
Hi, great library 👏
I have a suggestion for the seeding part. In NEP19, we recommend now to move away from the global state
np.random.seed
. Instead, the canonical way of using RNG is to use a generator with:rng = np.random.default_rng(seed_value)
. (Would be ok since you require a recent version of NumPy.)This is especially important since in SciPy for e.g. we are not relying anymore on the global state but ask people to use the parameter
random_state
(sometimes calledseed
orrng
depending on the function, sorry about the inconsistency, we are trying to resolve that slowly...).The text was updated successfully, but these errors were encountered: