PyDOE

PyDOE: An Experimental Design Package for Python

PyDOE is a Python package for design of experiments (DOE), enabling scientists, engineers, and 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

Overview

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 (fracfact, fracfact_aliasing, fracfact_by_res, fracfact_opt, alias_vector_indices)
- Plackett-Burman (pbdesign)
- Generalized Subset Designs (gsd)
- Fold-over Designs (fold)
- John's 3/4 Fractional Factorial (john_three_quarter_design)
- Latin Square Designs (latin_square)
- Graeco-Latin Square Designs (graeco_latin_square)
- Hyper-Graeco-Latin Square Designs (hyper_graeco_latin_square)
- Blocking of Full Factorial Designs (block_full_factorial)
Mixture Designs
- Simplex-Lattice Design (simplex_lattice_design)
- Simplex-Centroid Design (simplex_centroid_design)
- Axial (Screening) Design (mixture_axial_design)
- Extreme-Vertices Design (extreme_vertices_design)
- Mixture-Process Variable Design (mixture_process_design)
Response-Surface Designs
- Box-Behnken (bbdesign)
- Central-Composite (ccdesign)
- Doehlert Design (doehlert_shell_design, doehlert_simplex_design)
- Star Designs (star)
- Union Designs (union)
- Repeated Center Points (repeat_center)
- Blocked Central Composite Design (block_ccdesign)
- Small Composite Design (small_composite_design)
Space-Filling Designs
- Latin-Hypercube (lhs)
- Orthogonal Array-based Latin Hypercube (oa_lhd)
- Sliced Latin Hypercube (sliced_lhs)
- Nested Latin Hypercube (nested_lhs)
- Maximin Distance Design (maximin_design)
- Minimax Distance Design (minimax_design)
- Maximum Projection Design (maxpro_design)
- Nearly Orthogonal Latin Hypercube (nearly_orthogonal_lhs)
- Random Uniform (random_uniform)
Low-Discrepancy Sequences
- Sukharev Grid (sukharev_grid)
- Sobol’ Sequence (sobol_sequence)
- Halton Sequence (halton_sequence)
- Hammersley Point Set (hammersley_sequence)
- Rank-1 Lattice Design (rank1_lattice)
- Korobov Sequence (korobov_sequence)
- Faure Sequence (faure_sequence)
- Niederreiter Sequence (niederreiter_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)
- Iman-Conover Method (iman_conover)
Taguchi Designs
- Orthogonal arrays and robust design utilities (taguchi_design, compute_snr, get_orthogonal_array, list_orthogonal_arrays, TaguchiObjective)
Optimal Designs
- Advanced optimal design algorithms (optimal_design)
- Optimality criteria (a_optimality, c_optimality, d_optimality, e_optimality, g_optimality, i_optimality, s_optimality, t_optimality, v_optimality)
- Efficiency measures (a_efficiency, d_efficiency)
- Search algorithms (sequential_dykstra, simple_exchange_wynn_mitchell, fedorov, modified_fedorov, detmax)
- Design utilities (criterion_value, information_matrix, build_design_matrix, build_uniform_moment_matrix, generate_candidate_set)
Sparse Grid Designs
- Sparse Grid Design (doe_sparse_grid)
- Sparse Grid Dimension (sparse_grid_dimension)
Specialized Designs
- Definitive Screening Design (definitive_screening_design)
- Supersaturated Design (supersaturated_design)
Sequential / Adaptive Designs
- Sequential Design Driver (sequential_design)
- Gaussian Process Surrogate (GaussianProcessRegressor)
- Acquisition Functions (expected_improvement, probability_of_improvement, upper_confidence_bound)

Installation

pip install pydoe

Credits

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

License

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

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