Source code for openmdao.lib.doegenerators.full_factorial


.. _``:

The FullFactorial DOEgenerator implements a full factorial Design of Experiments; that is, it
generates a set of design points that fully span the range of the parameters at the requested
resolution. It plugs into the DOEgenerator socket on a DOEdriver."""

import logging
from itertools import product

# pylint: disable-msg=E0611,F0401
from openmdao.main.numpy_fallback import linspace

from openmdao.main.interfaces import implements, IDOEgenerator
from openmdao.lib.datatypes.api import Int
from openmdao.main.api import Container

[docs]class FullFactorial(Container): """ DOEgenerator that performs a full-factorial Design of Experiments. Plugs into the DOEgenerator socket on a DOEdriver.""" implements(IDOEgenerator) # pylint: disable-msg=E1101 num_parameters = Int(0, iotype="in", desc="Number of independent " "parameters in the DOE.") num_levels = Int(0, iotype="in", desc="Number of levels of values for " "each parameter.") def __init__(self, num_levels=0, *args, **kwargs): super(FullFactorial, self).__init__(*args, **kwargs) self.num_levels = num_levels def __iter__(self): """Return an iterator over our sets of input values.""" return product(*[linspace(0., 1., self.num_levels) for i in range(self.num_parameters)])
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