sampling.design.generate_grid_design
sampling.design.generate_grid_design(bounds, n_design, seed=None)Generates a regular grid design.
Points are generated by creating a regular grid where the number of points per dimension is derived from n_design (floor(n_design^(1/n_dim))).
Note: The actual number of points returned might be less than n_design if n_design is not a perfect power of n_dim.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| bounds | Union[List[Tuple[float, float]], np.ndarray] | Design space bounds. | required |
| n_design | int | The target number of points. Used to determine points per dimension. | required |
| seed | Optional[Union[int, Generator]] | Unused, kept for API consistency. | None |
Returns
| Name | Type | Description |
|---|---|---|
| np.ndarray | np.ndarray: A 2D array of shape (points_per_dim^n_dim, n_dim) with grid points. |
Examples
>>> import numpy as np
>>> from spotoptim.sampling.design import generate_grid_design
>>> bounds = [(0, 1), (0, 1)]
>>> X = generate_grid_design(bounds, n_design=25) # 5^2 = 25
>>> X.shape
(25, 2)