Implement subcooling correlations

[blakeNaccarato]

This meta-issue tracks the overall effort towards https://github.com/softboiler/boilercv/milestone/1.

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[blakeNaccarato]

How can an Implementation produce anything other than a str as a result? Maybe instead, the Implementation is always called in the absence of a certain form existing. How could this be cached, or need it be cached? If the python form is missing, but is derived from the sympy form, like solving for a particular variable, can that be done on the fly with each call?

Ultimately, we want to actually generate Python modules representing the symbolic and Python/numeric forms, which is easy for forms representable entirely as text. But what about complex forms that would otherwise require some pickling or binary storage? I don't want to ship binaries in boilercv, or check pickles into version control, so Implementation could represent how a given form can be produced from another.

For an Equation, does that mean that the result of an Implementation is a lambda function? Maybe we just have a Function model which also has a forms attribute, but its forms are the text you would eval or write to a generated Python module. But you would need to hook up the imports properly, so an correlations.abc_1985 Python function would need to know how to import a correlations.symbolic.abc_1985 module. These could be a second attribute, modules, which hold the module paths to be generated for each form.

[blakeNaccarato]

Need to further document and test after merging #186. For now, just trying to get all equations modeled before going further into the documentation effort for this.