Validation module. Most of these functions are plain checking and easy to understand.
check_random_state(seed)
Turn seed into a np.random.RandomState instance.
Parameters:
-
seed
(Union[None, int, RandomState]
)
–
If seed is None, return the RandomState singleton used by np.random.
If seed is an int, return a new RandomState instance seeded with seed.
If seed is already a RandomState instance, return it.
Otherwise raise ValueError.
Returns:
-
RandomState
–
The random state object based on seed
parameter.
Source code in stemflow/utils/validation.py
| def check_random_state(seed: Union[None, int, np.random.RandomState]) -> np.random.RandomState:
"""Turn seed into a np.random.RandomState instance.
Args:
seed:
If seed is None, return the RandomState singleton used by np.random.
If seed is an int, return a new RandomState instance seeded with seed.
If seed is already a RandomState instance, return it.
Otherwise raise ValueError.
Returns:
The random state object based on `seed` parameter.
"""
if seed is None or seed is np.random:
return np.random.mtrand._rand
if isinstance(seed, int):
return np.random.RandomState(seed)
if isinstance(seed, np.random.RandomState):
return seed
raise ValueError("%r cannot be used to seed a numpy.random.RandomState instance" % seed)
|