Package to generate and analyse orthogonal arrays and optimal designs
Project description
Orthogonal Array Package
The Orthogonal Array package contains functionality to generate and analyse orthogonal arrays, optimal designs and conference designs. Features include generation of complete series of orthogonal arrays, reduction of arrays to normal form and calculation of properties such as the strength or D-efficiency of an array. For more information about the package see the documentation at https://oapackage.readthedocs.io/en/latest/ and the webpage http://pietereendebak.nl/oapackage/.
Usage
The package can be used from Python:
>>> import oapackage
>>> al=oapackage.exampleArray(0)
>>> al.showarray()
array:
0 0
0 0
0 1
0 1
1 0
1 0
1 1
1 1
>>> print('D-efficiency %f, rank %d' % (al.Defficiency(), al.rank()) )
D-efficiency 1.000000, rank 2
>>> print('Generalized wordlength pattern: %s' % str(al.GWLP()))
Generalized wordlength pattern: (1.0, 0.0, 0.0)
For more examples see the Jupyter notebooks in the docs/examples.
Acknowledgements
If you use this code or any of the results, please cite this program as follows:
- Complete Enumeration of Pure-Level and Mixed-Level Orthogonal Arrays, E.D. Schoen, P.T. Eendebak, M.V.M. Nguyen, Volume 18, Issue 2, pages 123-140, 2010.
- Two-Level Designs to Estimate All Main Effects and Two-Factor Interactions, Pieter T. Eendebak, Eric D. Schoen, Technometrics Vol. 59 , Iss. 1, 2017
The code was written by:
- Pieter Eendebak pieter.eendebak@gmail.com
- Alan Vazquez-Alcocer
- Vincent Brouerius van Nidek
Ideas contributed by:
- Eric Schoen eric.schoen@tno.nl
- Alan Vazquez-Alcocer alanrvazquez@gmail.com
See the file LICENSE for copyright details.
Installation
The Python interface to the package is available on the Python Package index. Installation can be done using the following command:
$ pip install OApackage
(or pip install OApackage --user
if you do not have admin rights). To compile the package you need Python, Numpy and Swig 3.x.
The command line tools have been tested using Linux, Windows XP/Win7/Win10 and Raspberry Pi.
The program uses a cmake
build system. From the command line type:
$ mkdir -p build; cd build
$ cmake ..
$ make
$ make install
Testing
To perform tests run pytest
. To obtain a coverage report, run
$ coverage run --source='./oapackage' -m pytest
$ coverage report --omit oapackage/markup.py,oapackage/tests.py,oapackage/deprecated.py
Continuous integration and testing for the C++ library is performed on Travis and for the Python package on AppVeyor.
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