Freedom251 › Statistical Analysis Software
OApackage (Orthogonal Array Package)
Visit OApackage (Orthogonal Array Package) Alternatives Pricing
What OApackage (Orthogonal Array Package) is
OApackage (Orthogonal Array Package) is free, BSD-style licensed software for generating and analyzing orthogonal arrays, optimal designs, and conference designs. It uses exhaustive enumeration and optimization algorithms to create designs, then calculates criteria such as D-efficiency, rank, generalized word length patterns, F-vectors, and J-characteristics. Its coordinate-exchange algorithm can optimize D-, Ds-, and D1-efficiency combinations, although the documentation gives no guarantee of the largest possible D-efficiency. The package includes C++ and Python interfaces, command-line tools, a Matlab interface, and an R interface for optimal-design functions through CRAN. Python installation uses pip; CMake can build the command-line tools and C++ library. The documented Python interface requires NumPy, Matplotlib, and SWIG. Arrays are readable as text or binary files, and gzip-compressed binary files can be read. Writing compressed files is not supported. Normal-form reduction and isomorphism testing are included.
Who it suits
It suits science and research users working with orthogonal arrays and experimental designs through scripting, command-line tools, or programming interfaces. It is also relevant when readable or binary array files and design-efficiency analysis are needed.
What it does well
- Free BSD-style licensed package
- Python, C++, Matlab, R, and command-line interfaces
- Reads text, binary, and gzip-compressed arrays
- Calculates D-efficiency and array criteria
- Supports normal forms and isomorphism testing
What to know first
- No statistical tests
- No regression models
- No Bayesian analysis
- Compressed files cannot be written
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| OApackage | BSD-style licensed package · requires Python and dependencies | Free |
As oapackage.readthedocs.io lists them, read 9 Oct 2026. The maker's own page has the final word.
Verdict
OApackage focuses on orthogonal-array and optimal-design generation and analysis, with several interfaces and file formats. Its narrow statistical scope matters if you require regression, Bayesian analysis, or general statistical testing.
Facts from OApackage (Orthogonal Array Package)'s own pages
- Analysis
- It calculates structural and statistical properties including array rank, generalized wordlength pattern, F-values, J-characteristics, and design efficiencies. · oapackage.readthedocs.io, 9 Oct 2026
- Array analysis
- For orthogonal arrays, it can calculate generalized word length patterns, F-vectors, and J-characteristics. · oapackage.readthedocs.io, 9 Oct 2026
- Bayesian analysis
- No · oapackage.readthedocs.io, 23 Sept 2026
- Data handling
- Arrays can be stored in readable text or binary formats, and most tools transparently read compressed binary array files; writing compressed files is not supported. · github.com, 9 Oct 2026
- Data import formats
- .oa text and binary array files; gzip-compressed files supported · oapackage.readthedocs.io, 23 Sept 2026
- D-efficient designs
- The coordinate-exchange algorithm generates designs that optimize D-efficiency, but the documentation says there is no guarantee they have the largest possible D-efficiency. · oapackage.readthedocs.io, 9 Oct 2026
- Dependencies
- PyPI specifies Python 3.10 or newer and lists NumPy, python-dateutil, and Matplotlib as dependencies. · pypi.org, 9 Oct 2026
- Deployment
- desktop · oapackage.readthedocs.io, 23 Sept 2026
- Free plan
- Yes · oapackage.readthedocs.io, 23 Sept 2026
- Generation
- It uses exhaustive enumeration and optimization algorithms to generate arrays and designs. · oapackage.readthedocs.io, 9 Oct 2026
- Installation
- The Python interface can be installed with pip, and the command-line tools and C++ library can be built with CMake. · oapackage.readthedocs.io, 9 Oct 2026
- Intended audience
- PyPI classifies the project for science and research audiences. · pypi.org, 9 Oct 2026
- Interfaces
- The package provides C++ and Python interfaces, command-line tools, and a Matlab interface for generating optimal designs. · oapackage.readthedocs.io, 9 Oct 2026
- License
- The code is available under a BSD-style license. · oapackage.readthedocs.io, 9 Oct 2026
- Maintainer
- PyPI names Pieter Eendebak as the author and lists the account eendebakpt as the maintainer. · pypi.org, 9 Oct 2026
- Normal forms
- The package includes functionality for reducing arrays to normal form and testing isomorphism. · github.com, 9 Oct 2026
- Optimal designs
- Its coordinate-exchange algorithm generates D-efficient designs and can optimize weighted combinations of D-, Ds-, and D1-efficiency criteria. · oapackage.readthedocs.io, 9 Oct 2026
- Platforms
- The documentation says the package is continuously tested on Linux and Windows. · oapackage.readthedocs.io, 9 Oct 2026
- Purpose
- OApackage generates and analyses orthogonal arrays, optimal designs, and conference designs. · oapackage.readthedocs.io, 9 Oct 2026
- Regression models
- No · oapackage.readthedocs.io, 23 Sept 2026
- R interface
- An R interface to the optimal-design functionality is available from CRAN. · oapackage.readthedocs.io, 9 Oct 2026
- Scripting support
- Yes · oapackage.readthedocs.io, 23 Sept 2026
- Statistical tests
- No · oapackage.readthedocs.io, 23 Sept 2026
- Support
- The repository directs users to its CONTRIBUTING.md file for contribution, unit-testing, and support information. · github.com, 9 Oct 2026
Where OApackage (Orthogonal Array Package) stands on Freedom251
- Statistical Analysis Software#26 of 106