OpenMDAO/OpenMDAO-Framework — Issue #663: Metamodel training with constant inputs
Author: JustinSGray
Created: 2011-10-25 18:10:47+00:00
State: open
Labels: enhancement

When you train metamodel on data, there is the possibility that some of the inputs will have constant values. If that happens, then when you go to train surrogates, you should exclude the data associated withe the constant valued input, as this will cause problems. This means that the metamodel will provide predictions, independent of the constant valued input.

Hence the value of the constant input needs to be stored in the metamodel, and during prediction if that value is changed at all from what it was set to during training then an error needs to be raised saying that the prediction can't be done because the assumption of some_var=some_val was violated.

Also, if all inputs are constant valued, then during the training an error should be raised, because there is nothing to fit the surrogate models to!