=====================================================
``pyDOE``: The experimental design package for python
=====================================================
The ``pyDOE`` 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``)
- *Response-Surface Designs*
#. **Box-Behnken** (``bbdesign``)
#. **Central-Composite** (``ccdesign``)
- *Randomized Designs*
#. **Latin-Hypercube** (``lhs``)
*See the* `package homepage`_ *for details on usage and other notes*
What's New
==========
In this release, an incorrect indexing variable in the internal LHS function
`_pdist` has been corrected so point-distances are now calculated accurately.
Requirements
============
- NumPy
- SciPy
Installation and download
=========================
See the `package homepage`_ for helpful hints relating to downloading
and installing pyDOE.
Source Code
===========
The latest, bleeding-edge but working `code
<https://github.com/tisimst/pyDOE/tree/master/pyDOE>`_
and `documentation source
<https://github.com/tisimst/pyDOE/tree/master/doc/>`_ are
available `on GitHub <https://github.com/tisimst/pyDOE/>`_.
Contact
=======
Any feedback, questions, bug reports, or success stores should
be sent to the `author`_. I'd love to hear from you!
Credits
=======
This code was originally published 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
- Website: forge.scilab.org/index.php/p/scidoe/sourcetree/master/macros
Much thanks goes to these individuals.
And thanks goes out to the following for finding and offering solutions for
bugs:
- Ashmeet Singh
License
=======
This package is provided under two licenses:
1. The *BSD License* (3-clause)
2. Any other that the author approves (just ask!)
References
==========
- `Factorial designs`_
- `Plackett-Burman designs`_
- `Box-Behnken designs`_
- `Central composite designs`_
- `Latin-Hypercube designs`_
.. _author: mailto:tisimst@gmail.com
.. _Factorial designs: http://en.wikipedia.org/wiki/Factorial_experiment
.. _Box-Behnken designs: http://en.wikipedia.org/wiki/Box-Behnken_design
.. _Central composite designs: http://en.wikipedia.org/wiki/Central_composite_design
.. _Plackett-Burman designs: http://en.wikipedia.org/wiki/Plackett-Burman_design
.. _Latin-Hypercube designs: http://en.wikipedia.org/wiki/Latin_hypercube_sampling
.. _package homepage: http://pythonhosted.org/pyDOE
.. _lhs documentation: http://pythonhosted.org/pyDOE/randomized.html#latin-hypercube
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"description": "=====================================================\n``pyDOE``: The experimental design package for python\n=====================================================\n\nThe ``pyDOE`` package is designed to help the \n**scientist, engineer, statistician,** etc., to construct appropriate \n**experimental designs**.\n\nCapabilities\n============\n\nThe package currently includes functions for creating designs for any \nnumber of factors:\n\n- *Factorial Designs*\n\n #. **General Full-Factorial** (``fullfact``)\n\n #. **2-level Full-Factorial** (``ff2n``)\n\n #. **2-level Fractional Factorial** (``fracfact``)\n\n #. **Plackett-Burman** (``pbdesign``)\n\n- *Response-Surface Designs* \n\n #. **Box-Behnken** (``bbdesign``)\n\n #. **Central-Composite** (``ccdesign``)\n\n- *Randomized Designs*\n\n #. **Latin-Hypercube** (``lhs``)\n \n*See the* `package homepage`_ *for details on usage and other notes*\n\nWhat's New\n==========\n\nIn this release, an incorrect indexing variable in the internal LHS function\n`_pdist` has been corrected so point-distances are now calculated accurately.\n\nRequirements\n============\n\n- NumPy\n- SciPy\n\nInstallation and download\n=========================\n\nSee the `package homepage`_ for helpful hints relating to downloading\nand installing pyDOE.\n\nSource Code\n===========\n\nThe latest, bleeding-edge but working `code\n<https://github.com/tisimst/pyDOE/tree/master/pyDOE>`_\nand `documentation source\n<https://github.com/tisimst/pyDOE/tree/master/doc/>`_ are\navailable `on GitHub <https://github.com/tisimst/pyDOE/>`_.\n\nContact\n=======\n\nAny feedback, questions, bug reports, or success stores should\nbe sent to the `author`_. I'd love to hear from you!\n\nCredits\n=======\n\nThis code was originally published by the following individuals for use with\nScilab:\n \n- Copyright (C) 2012 - 2013 - Michael Baudin\n- Copyright (C) 2012 - Maria Christopoulou\n- Copyright (C) 2010 - 2011 - INRIA - Michael Baudin\n- Copyright (C) 2009 - Yann Collette\n- Copyright (C) 2009 - CEA - Jean-Marc Martinez\n\n- Website: forge.scilab.org/index.php/p/scidoe/sourcetree/master/macros\n\nMuch thanks goes to these individuals.\n\nAnd thanks goes out to the following for finding and offering solutions for\nbugs:\n\n- Ashmeet Singh\n\nLicense\n=======\n\nThis package is provided under two licenses:\n\n1. The *BSD License* (3-clause)\n2. Any other that the author approves (just ask!)\n\nReferences\n==========\n\n- `Factorial designs`_\n- `Plackett-Burman designs`_\n- `Box-Behnken designs`_\n- `Central composite designs`_\n- `Latin-Hypercube designs`_\n\n.. _author: mailto:tisimst@gmail.com\n.. _Factorial designs: http://en.wikipedia.org/wiki/Factorial_experiment\n.. _Box-Behnken designs: http://en.wikipedia.org/wiki/Box-Behnken_design\n.. _Central composite designs: http://en.wikipedia.org/wiki/Central_composite_design\n.. _Plackett-Burman designs: http://en.wikipedia.org/wiki/Plackett-Burman_design\n.. _Latin-Hypercube designs: http://en.wikipedia.org/wiki/Latin_hypercube_sampling\n.. _package homepage: http://pythonhosted.org/pyDOE\n.. _lhs documentation: http://pythonhosted.org/pyDOE/randomized.html#latin-hypercube",
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