expandLHS 1.1.0

A Python package to expand a Latin Hypercube Sample

[](https://doi.org/10.5281/zenodo.15076931)

## expandLHS

expandLHS is a Python module that implements a model-free expansion algorithm for a Latin Hypercube sample set. The Latin Hypercube Sampling (LHS) is a stratified sampling technique that allows to generate $N$ near-random samples in the $P$-dimensional hypercube $[0, 1)^P$. It is a space-filling sampling strategy that ensures the one-dimensional projection property, i.e. the samples are uniformly distributed in each one-dimension projection. This module extends the usage of this technique by implementing an expansion algorithm. Starting from an initial LHS set of size $N$, expandLHS samples $M$ additional points in a LHS-like fashion trying to preserve the LHS properties at most.

This algorithm is introduced in - “LHS in LHS”: a new expansion strategy for Latin hypercube sampling in simulation design. M. Boschini, D. Gerosa, A. Crespi, M. Falcone (to be published)

The code is distributed under version control at - [github.com/m-boschini/expandLHS](https://github.com/m-boschini/expandLHS)

The documentation is available at

• [m-boschini.github.io/expandLHS](https://m-boschini.github.io/expandLHS)

To install the code simply use

pip install expandLHS

An example notebook can be found in the [documentation](https://m-boschini.github.io/expandLHS) together with a detailed description of the functions.

expandLHS is released under the MIT License.

#### Change log

• v1.1.0 New feature: now it is possible to initialise a Latin Hypercube when the class is created

• v1.0.0 First public release.

(Third-level versions not explicitly indicated refer to patches for minor typos/bug fixes)