Metadata-Version: 2.1
Name: definitive-screening-design
Version: 0.3.0
Summary: Definitive Screening Design
Home-page: https://github.com/danieleongari/definitive_screening_design
Author: Daniele Ongari
Author-email: Daniele.Ongari@Solvay.com
License: None
Description: # Definitive Screening Design (DSD)
        
        ## Main References
        
        - Bradley Jones and Christopher J. Nachtsheim. "A Class of Three-Level Designs for Definitive Screening in the Presence of Second-Order Effects" Journal of Quality Technology 43, no. 1 (January 2011): 1–15. https://doi.org/10.1080/00224065.2011.11917841.
        - Bradley Jones and Christopher J. Nachtsheim. "Definitive screening designs with added two-level categorical factors" Journal of Quality Technology 45.2 (2013): 121-129. https://doi.org/10.1080/00224065.2013.11917921
        
        ## Further References about the practical use of this design
        
        - Bradley Jones. ["Proper and Improper use of Definitive Screening Designs"](https://community.jmp.com/t5/JMP-Blog/Proper-and-improper-use-of-Definitive-Screening-Designs-DSDs/ba-p/30703?trMode=source)
        - Douglas Motngomery. [Coursera lesson on "General Structure of a DSD with m Factors"](https://www.coursera.org/lecture/response-surfaces-mixtures-model-building/general-structure-of-a-definitive-screening-design-with-m-factors-N1Ebc)
        - Paul Nelson. ["The Evolution of Definitive Screening Designs from Optimal (Custom) DoE"](https://www.prismtc.co.uk/resources/blogs-and-articles/article-the-evolution-of-definitive-screening-designs-from-optimal-custom-design-of-experiments)
        
        ## Installation
        ```
        pip install definitive_screening_design
        ```
        
        ## Example
        Generate a Definitive Design screening with three numerical and two 2-levels categoricals factors,
        using the protocol presented in the 2013 paper.
        The result is a Pandas DataFrame.
        
        ```
        import definitive_screening_design as dsd
        dsd.generate(n_num=3, n_cat=2)
        ```
        |    |   X01 |   X02 |   X03 |   C01 |   C02 |
        |---:|------:|------:|------:|------:|------:|
        |  1 |     0 |     1 |     1 |     2 |     2 |
        |  2 |    -0 |    -1 |    -1 |     1 |     1 |
        |  3 |     1 |     0 |    -1 |     2 |     2 |
        |  4 |    -1 |    -0 |     1 |     1 |     1 |
        |  5 |     1 |    -1 |     0 |     1 |     2 |
        |  6 |    -1 |     1 |    -0 |     2 |     1 |
        |  7 |     1 |     1 |    -1 |     2 |     1 |
        |  8 |    -1 |    -1 |     1 |     1 |     2 |
        |  9 |     1 |     1 |     1 |     1 |     2 |
        | 10 |    -1 |    -1 |    -1 |     2 |     1 |
        | 11 |     1 |    -1 |     1 |     2 |     1 |
        | 12 |    -1 |     1 |    -1 |     1 |     2 |
        | 13 |     0 |     0 |     0 |     1 |     1 |
        | 14 |     0 |     0 |     0 |     2 |     2 |
        
        Check the `notebooks` folder for further examples and explainations.
Platform: UNKNOWN
Classifier: Programming Language :: Python
Description-Content-Type: text/markdown
Provides-Extra: testing
Provides-Extra: pre-commit
