PyDOE is a Python package for design of experiments (DOE)enabling scientistsengineersand statisticians to efficiently construct experimental designs.

• Website: https://pydoe.github.io/pydoe/
• Documentation: https://pydoe.github.io/pydoe/reference/factorial/
• Source code: https://github.com/pydoe/pydoe
• Contributing: https://pydoe.github.io/pydoe/contributing/
• Bug reports: https://github.com/pydoe/pydoe/issues

The package provides extensive support for design-of-experiments (DOE) methods and is capable of creating designs for any number of factors.

It provides:

• Factorial Designs

  • General Full-Factorial (fullfact)
  • 2-level Full-Factorial (ff2n)
  • 2-level Fractional Factorial (fracfactfracfact_aliasingfracfact_by_resfracfact_optalias_vector_indices)
  • Plackett-Burman (pbdesign)
  • Generalized Subset Designs (gsd)
  • Fold-over Designs (fold)

• Response-Surface Designs

  • Box-Behnken (bbdesign)
  • Central-Composite (ccdesign)
  • Doehlert Design (doehlert_shell_designdoehlert_simplex_design)
  • Star Designs (star)
  • Union Designs (union)
  • Repeated Center Points (repeat_center)

• Space-Filling Designs

  • Latin-Hypercube (lhs)
  • Random Uniform (random_uniform)

• Low-Discrepancy Sequences

  • Sukharev Grid (sukharev_grid)
  • Sobol’ Sequence (sobol_sequence)
  • Halton Sequence (halton_sequence)
  • Rank-1 Lattice Design (rank1_lattice)
  • Korobov Sequence (korobov_sequence)
  • Cranley-Patterson Randomization (cranley_patterson_shift)

• Clustering Designs

  • Random K-Means (random_k_means)

• Sensitivity Analysis Designs

  • Morris Method (morris_sampling)
  • Saltelli Sampling (saltelli_sampling)

• Taguchi Designs

  • Orthogonal arrays and robust design utilities (taguchi_designcompute_snrget_orthogonal_arraylist_orthogonal_arraysTaguchiObjective)

• Optimal Designs

  • Advanced optimal design algorithms (optimal_design)
  • Optimality criteria (a_optimalityc_optimalityd_optimalitye_optimalityg_optimalityi_optimalitys_optimalityt_optimalityv_optimality)
  • Efficiency measures (a_efficiencyd_efficiency)
  • Search algorithms (sequential_dykstrasimple_exchange_wynn_mitchellfedorovmodified_fedorovdetmax)
  • Design utilities (criterion_valueinformation_matrixbuild_design_matrixbuild_uniform_moment_matrixgenerate_candidate_set)

• Sparse Grid Designs

  • Sparse Grid Design (doe_sparse_grid)
  • Sparse Grid Dimension (sparse_grid_dimension)

pip install pydoe

For more info see: https://pydoe.github.io/pydoe/credits/

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