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46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
"""Set of random number generator functions: seeding, generator, hashing seeds."""
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from __future__ import annotations
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import numpy as np
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from gymnasium import error
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def np_random(seed: int | None = None) -> tuple[np.random.Generator, int]:
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"""Returns a NumPy random number generator (RNG) along with seed value from the inputted seed.
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If ``seed`` is ``None`` then a **random** seed will be generated as the RNG's initial seed.
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This randomly selected seed is returned as the second value of the tuple.
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.. py:currentmodule:: gymnasium.Env
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This function is called in :meth:`reset` to reset an environment's initial RNG.
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Args:
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seed: The seed used to create the generator
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Returns:
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A NumPy-based Random Number Generator and generator seed
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Raises:
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Error: Seed must be a non-negative integer
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"""
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if seed is not None and not (isinstance(seed, int) and 0 <= seed):
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if isinstance(seed, int) is False:
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raise error.Error(
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f"Seed must be a python integer, actual type: {type(seed)}"
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)
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else:
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raise error.Error(
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f"Seed must be greater or equal to zero, actual value: {seed}"
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)
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seed_seq = np.random.SeedSequence(seed)
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np_seed = seed_seq.entropy
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rng = RandomNumberGenerator(np.random.PCG64(seed_seq))
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return rng, np_seed
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RNG = RandomNumberGenerator = np.random.Generator
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