# Copyright (C) 2024 Jakub Więckowski
import numpy as np
from ...validator import Validator
from ...utils import memory_guard
[docs]
@memory_guard
def random_distribution(size: int) -> np.ndarray:
"""
Generate a set of normalized weights sampled from a random distribution ( from half-open interval [0.0, 1.0) ).
Parameters:
------------
size : int
Number of weights to generate.
Returns:
---------
ndarray
Array of normalized weights sampled from a random distribution.
Example
---------
>>> weights = random_distribution(3)
>>> print(weights)
"""
Validator.is_type_valid(size, (int, np.integer), 'size')
Validator.is_positive_value(size, var_name='size')
weights = np.abs(np.random.random(size=size))
return np.array(weights) / np.sum(weights)