pyDOE3: An experimental design package for python

This package is designed to help the scientist, engineer, statistician, etc., to construct appropriate experimental designs.

Capabilities

The package currently includes functions for creating designs for any number of factors:

• Factorial Designs

  • General Full-Factorial (fullfact)
  • 2-level Full-Factorial (ff2n)
  • 2-level Fractional Factorial (fracfact)
  • Plackett-Burman (pbdesign)
  • Generalized Subset Designs (gsd)

• Response-Surface Designs

  • Box-Behnken (bbdesign)
  • Central-Composite (ccdesign)
  • Doehlert Design (doehlert_shell_design, doehlert_simplex_design)

• Randomized Designs

  • Latin-Hypercube (lhs)

• Low-Discrepancy Sequences

  • Sukharev Grid (sukharev_grid)

• Taguchi Designs

  • Orthogonal arrays and robust design utilities (taguchi_design, compute_snr)

• Optimal Designs

  • Advanced optimal design algorithms (optimal_design)
  • Optimality criteria (A, C, D, E, G, I, S, T, V)
  • Search algorithms (Sequential (Dykstra), Simple Exchange (Wynn-Mitchell), Fedorov, Modified Fedorov, DETMAX)

See Documentation.

Installation

pip install pyDOE3

Credits

pyDOE original code was originally converted from code by the following individuals for use with Scilab:

• Copyright (C) 2012-2013, Michael Baudin
• Copyright (C) 2012, Maria Christopoulou
• Copyright (C) 2010-2011, INRIA, Michael Baudin
• Copyright (C) 2009, Yann Collette
• Copyright (C) 2009, CEA, Jean-Marc Martinez

pyDOE was converted to Python by the following individual:

• Copyright (c) 2014, Abraham D. Lee

The following individuals forked pyDOE and worked on pyDOE2:

• Copyright (C) 2018, Rickard Sjögren and Daniel Svensson

pyDOE3 is a fork of the pyDOE2. It came to life to solve bugs and issues that remained unsolved in the pyDOE2 package.

License

This package is provided under the BSD License (3-clause)

References

• Factorial designs
• Plackett-Burman designs
• Box-Behnken designs
• Central composite designs
• Doehlert Design
• Latin-Hypercube designs
• Taguchi designs
• Generalized Subset Designs
• Optimal experimental design