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Copyright (C) 2014 Cornell University
Response_Surface is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, see <http://www.gnu.org/licenses/gpl-2.0.html>
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Contact:
Kyle Perline, krp73@cornell.edu
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This is a general API for response (or regression) surfaces. Suppose we have a set of n samples in d-dimensions represented as an nXd matrix S and a set of n corresponding values in v-dimensions represented as an nXv matrix V. A response surface is a 'best-fit' f:R^d -> R^v based on (S,V). 
There are two main components:
1. Transformation of S and V to S' and V'. For example, some response surface methods perform better if S and V are first normalized to the unit hypercubes.
2. Response surface best-fits. For example, polynomial regression or Radial Basis Function regression.
For an introduction of how to use this, see RS_poly_testing.py.
For details on how to construct a new transformation function, see transformation.py. 
For an example of how to construct a new response surface method, see both RS_Parent.py and RS_poly.py.