rounded ints passed as arguments, floats used for internal calculations about doepipeline HOT 4 CLOSED

I suggest the approach mentioned in #5

from doepipeline.

This introduces an error. Quantitative variables should not be rounded of.

The need for this however highlights another error. There is currently no proper support for qualitative or ordinal factors which ought to be fixed, discussed in #5.

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This has been changed to only round the factor values that belong to the class OrdinalFactor, factor values of any other class are not rounded.

There is no support for dealing with ordinal factors in scipy.optimize from what I can tell. All the minimize functions deal with the factors as continuous. Without including another solver we will not be able to deal with ordinal factors the correct way.

Solving functions where parameters are ordinal is part of Integer programming (IP). There are open source solvers that can solve integer linear programming (ILP) and mixed integer programming (MIP) problems, such as GLPK with python bindings. However I cannot find any integer quadratic programming (IQP) or mixed integer quadratic programming (MIQP) solvers that are open source, but instead there are a number or proprietary softwares (some with free academic licenses).

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I consider this solved by the current way of simply rounding ordinal factors after optimization.

from doepipeline.