sampling.design.generate_uniform_design
sampling.design.generate_uniform_design(bounds, n_design, seed=None)Generate a uniform random experimental design.
Generates n_design points uniformly distributed within the specified bounds. This function is compatible with SpotOptim’s random number handling.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| bounds | Union[List[Tuple[float, float]], np.ndarray] | Design space bounds. List of (lower, upper) tuples for each dimension. | required |
| n_design | int | Number of design points to generate. | required |
| seed | Optional[Union[int, Generator]] | Random seed or generator. Defaults to None. | None |
Returns
| Name | Type | Description |
|---|---|---|
| np.ndarray | np.ndarray: Generated design points of shape (n_design, n_dim). |
Examples
>>> import numpy as np
>>> from spotoptim.sampling.design import generate_uniform_design
>>> bounds = [(-5, 5), (0, 10)]
>>> X = generate_uniform_design(bounds, n_design=5, seed=42)
>>> X.shape
(5, 2)
>>> np.all((X >= [-5, 0]) & (X <= [5, 10]))
True