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LLNL / MuyGPyS

A fast, pure python implementation of the MuyGPs Gaussian process realization and training algorithm.
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library needs to be more functional #94

Closed bwpriest closed 1 year ago

bwpriest commented 1 year ago

I have come to the conclusion that MuyGPyS has too many procedural conditionals to be maintainable. We need to refactor much of the library to functionally construct MuyGPs processes in a way that is set at object creation time. In particular, we need to break MuyGPS.regress into MuyGPS.posterior_mean() and MuyGPS.posterior_variance(). Rather than writing these methods as normal member functions, they should be defined at object creation time based upon model choices - e.g. homo/heterscedasticity, variance form, etc. There are other examples that I will document in this thread as they arise.

bwpriest commented 1 year ago

This has been mostly addressed by PRs #104 and #107, and the iss #106 will wrap up most of the remaining remnants of the old flow.