import numpy as np
def hypercube_points(
num_points: int, hypercube_size: float, num_dimensions: int
) -> np.ndarray:
"""
Generates random points uniformly distributed within an n-dimensional hypercube.
Args:
num_points: Number of points to generate.
hypercube_size: Size of the hypercube.
num_dimensions: Number of dimensions of the hypercube.
Returns:
An array of shape (num_points, num_dimensions)
with generated points.
"""
rng = np.random.default_rng()
shape = (num_points, num_dimensions)
return hypercube_size * rng.random(shape)