pydoe 0.1.alpha

Design of experiments 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:

1. 2-level full-factorial

2. Generic full-factorial

3. Box-Behnken

4. Central-Composite

The following are in the works (probably), so stay tuned!

1. Plackett-Burman designs

2. Fractional-factorial designs

3. Split-plot designs

4. Incomplete block designs

5. D-Optimal designs

Requirements

• NumPy

Basic Examples

The main import:

>>> from pyDOE import *

2-Level full-factorial designs (ff2n) only require the number of factors:

>>> ff2n(3)
array([[-1., -1., -1.],
       [ 1., -1., -1.],
       [-1.,  1., -1.],
       [ 1.,  1., -1.],
       [-1., -1.,  1.],
       [ 1., -1.,  1.],
       [-1.,  1.,  1.],
       [ 1.,  1.,  1.]])

General full-factorial designs (fullfact) require an array of integers, one integer for each factor, where the integer value is the number of levels for that factor:

>>> fullfact([2, 4, 3])
array([[ 0.,  0.,  0.],
       [ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 1.,  1.,  0.],
       [ 0.,  2.,  0.],
       [ 1.,  2.,  0.],
       [ 0.,  3.,  0.],
       [ 1.,  3.,  0.],
       [ 0.,  0.,  1.],
       [ 1.,  0.,  1.],
       [ 0.,  1.,  1.],
       [ 1.,  1.,  1.],
       [ 0.,  2.,  1.],
       [ 1.,  2.,  1.],
       [ 0.,  3.,  1.],
       [ 1.,  3.,  1.],
       [ 0.,  0.,  2.],
       [ 1.,  0.,  2.],
       [ 0.,  1.,  2.],
       [ 1.,  1.,  2.],
       [ 0.,  2.,  2.],
       [ 1.,  2.,  2.],
       [ 0.,  3.,  2.],
       [ 1.,  3.,  2.]])

Box-Behnken designs (bbdesign) require the number of factors and optional number of center points (NOTE: the number of center points is not automatically calculated! It needs to be given explicitly, default = 1):

>>> bbdesign(3, center=5)
array([[-1., -1.,  0.],
       [ 1., -1.,  0.],
       [-1.,  1.,  0.],
       [ 1.,  1.,  0.],
       [-1.,  0., -1.],
       [ 1.,  0., -1.],
       [-1.,  0.,  1.],
       [ 1.,  0.,  1.],
       [ 0., -1., -1.],
       [ 0.,  1., -1.],
       [ 0., -1.,  1.],
       [ 0.,  1.,  1.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.]])

Central-Composite designs (ccdesign) require the number of factors, an optional number of center points, and an optional type description (i.e. face=... which can be one of:

1. “circumscribed” or “ccc” (default)

2. “faced” or “ccf”

3. “inscribed” or “cci”

(Note: the alpha value for the star points is automatically calculated):

>>> ccdesign(3, face='ccc', center=4)
array([[-1.        , -1.        , -1.        ],
       [ 1.        , -1.        , -1.        ],
       [-1.        ,  1.        , -1.        ],
       [ 1.        ,  1.        , -1.        ],
       [-1.        , -1.        ,  1.        ],
       [ 1.        , -1.        ,  1.        ],
       [-1.        ,  1.        ,  1.        ],
       [ 1.        ,  1.        ,  1.        ],
       [-1.68179283,  0.        ,  0.        ],
       [ 1.68179283,  0.        ,  0.        ],
       [ 0.        , -1.68179283,  0.        ],
       [ 0.        ,  1.68179283,  0.        ],
       [ 0.        ,  0.        , -1.68179283],
       [ 0.        ,  0.        ,  1.68179283],
       [ 0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ]])

Contact

Any feedback, questions, bug reports, or words of encouragement can be sent to the author.

License

This package is provided under two licenses:

1. The BSD License

2. Any other that the author approves (just ask!)

References

• Factorial designs

• Box-Behnken designs

• Central composite designs