experiment-design 0.1.2

Tools to create designs of experiments

experiment-design: Tools to create and extend experiment plans

experiment-design allows you to create high quality designs of experiment with just a few lines of code. Additionally, it allows you to extend the designs of experiments...

... create and optimize orthogonal sampling designs with any distribution supported by scipy.stats

...and easily simulate correlated variables.

There is even more! See the documentation for more details and especially the section "Why should you use experiment-design?"

Also, see demos to understand how the images above were created.

Install

experiment-design can be installed easily from PyPI using

pip install experiment-design

Cite

You can use the zenodo DOI to cite the code, but if this repository helps you with your research, please consider citing either of the following:

• Journal paper about locally extending experiment designs for adaptive sampling:

@Article{Bogoclu2021,
  title       = {Local {L}atin hypercube refinement for multi-objective design uncertainty optimization},
  author      = {Can Bogoclu and Tamara Nestorovi{\'c} and Dirk Roos},
  journal     = {Applied Soft Computing},
  year        = {2021},
  arxiv       = {2108.08890},
  doi         = {10.1016/j.asoc.2021.107807},
  pdf         = {https://www.sciencedirect.com/science/article/abs/pii/S1568494621007286},
}

• PhD thesis:

@phdthesis{Bogoclu2022,
  title       = {Local {L}atin hypercube refinement for uncertainty quantification and optimization: {A}ccelerating the surrogate-based solutions using adaptive sampling},
  author      = {Bogoclu, Can},
  school      = {Ruhr-Universit\"{a}t Bochum},
  type         = {PhD thesis},
  year        = {2022},
  doi         = {10.13154/294-9143},
  pdf         = {https://d-nb.info/1268193348/34},
}