Metadata-Version: 1.1
Name: pyDOE2
Version: 1.0.2
Summary: Design of experiments for Python
Home-page: https://github.com/clicumu/pyDOE2
Author: Rickard Sjögren
Author-email: r.sjogren89@gmail.com
License: BSD License (3-Clause)
Description-Content-Type: UNKNOWN
Description: pyDOE2: An experimental design package for python
        =====================================================
        
        `pyDOE2` is a fork of the [`pyDOE`](https://github.com/tisimst/pyDOE) package 
        that is designed to help the scientist, engineer, statistician, etc., to 
        construct appropriate experimental designs.
        
        This fork came to life to solve bugs and issues that remained unsolved in the
        original package.
        
        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 original [package homepage](http://pythonhosted.org/pyDOE) for details 
        on usage and other notes.
        
        Requirements
        ------------
        
        - NumPy
        - SciPy
        
        Installation and download
        -------------------------
        
        Through pip:
        
        ```
        pip install pyDOE2
        ```
        
        
        Credits
        -------
        
        `pyDOE` original code was originally converted from code 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
        
        `pyDOE` was converted to Python by the following individual:
        
        - Copyright (c) 2014, Abraham D. Lee
        
        The following individuals forked and works `pyDOE2`:
        
        - Copyright (C) 2018 - Rickard SjÃ¶gren and Daniel Svensson
        
        
        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](http://en.wikipedia.org/wiki/Factorial_experiment)
        - [Plackett-Burman designs](http://en.wikipedia.org/wiki/Plackett-Burman_design)
        - [Box-Behnken designs](http://en.wikipedia.org/wiki/Box-Behnken_design)
        - [Central composite designs](http://en.wikipedia.org/wiki/Central_composite_design)
        - [Latin-Hypercube designs](http://en.wikipedia.org/wiki/Latin_hypercube_sampling)
        
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 :: 2.7
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
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
