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 called seed or rng depending on the function, sorry about the inconsistency, we are trying to resolve that slowly...).
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 calledseedorrngdepending on the function, sorry about the inconsistency, we are trying to resolve that slowly...).