Refactor parameter links and summary

[rutgerfick]

The current parameter linking system works but is difficult to interact with and add custom functions into.

• Parameter and optimization link descriptions should be passed as dictionaries.
• each dictionary describes the mathematical relation that is imposed, which parameter are input, which parameter are removed or added.
• Linking and optimization dictionaries should have similar setup, but optimization dictionaries need to somehow be more complicated to include optimization ranges for the new optimization parameter.
• In relation to replaying parameter links from spherical mean models to regular or sh-models, it should be able to pass a list of these dictionaries and the model will then just replay these links.

In relation to fixing parameters

• parameter should not just be removed from the parameter list, (meaning if you call the same function again it will give an error since the parameter was removed, unless the model is re-initialized). The system should be changed so that parameter are recatagorized somehow and a summary function can be called which lists which parameter are optimized / fixed / linked.

The linking functions sometimes vary whether they are given to distributed models or MC models. This should be resolved.