Metadata-Version: 1.1
Name: pyDOE
Version: 0.3.8
Summary: Design of experiments for Python
Home-page: https://github.com/tisimst/pyDOE
Author: Abraham Lee
Author-email: tisimst@gmail.com
License: BSD License (3-Clause)
Description: =====================================================
        ``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
        
Keywords: DOE,design of experiments,experimental design,optimization,statistics,python
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
