sampling.mm.perturb

sampling.mm.perturb(X, PertNum=1)

Performs a specified number of random element swaps on a sampling plan. If the plan is a Latin hypercube, the result remains a valid Latin hypercube.

Parameters

Name	Type	Description	Default
X	np.ndarray	A 2D array (sampling plan) of shape (n, k), where each row is a point and each column is a dimension.	required
PertNum	int	The number of element swaps (perturbations) to perform. Defaults to 1.	1

Returns

Name	Type	Description
	np.ndarray	np.ndarray: The perturbed sampling plan, identical in shape to the input, with one or more random column swaps executed.

Notes

Many thanks to the original author of this code, A Sobester, for providing the original Matlab code under the GNU Licence. Original Matlab Code: Copyright 2007 A Sobester: “This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU General Public License and GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/.”

Examples

>>> import numpy as np
>>> from spotoptim.sampling.mm import perturb
>>> # Create a simple 4x2 sampling plan
>>> X_original = np.array([
...     [1, 3],
...     [2, 4],
...     [3, 1],
...     [4, 2]
... ])
>>> # Perturb it once
>>> X_perturbed = perturb(X_original, PertNum=1)
>>> print(X_perturbed)
# The output may differ due to random swaps, but each column is still a permutation of [1,2,3,4].
    [[1 3]
    [2 2]
    [3 1]
    [4 4]]