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JuliaDynamics / ComplexityMeasures.jl

Estimators for probabilities, entropies, and other complexity measures derived from data in the context of nonlinear dynamics and complex systems
MIT License
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Make all probability estimators have an explicit outcome space? #185

Closed Datseris closed 1 year ago

Datseris commented 1 year ago

It's like 99% sure you'll agree with this @kahaaga , but shall we just go ahead and ensure all probabilities Estimators have a well defined outocme space? Which means, if input x is necessary, it must already be given at the point where the probability estimator is instantiated?

This has numerous benefits:

  1. The estimators always have a well defined outcome_space which is by now an integral part of the API
  2. Maximum entropy is simplified and doesn't need input x.
kahaaga commented 1 year ago

It's like 99% sure you'll agree with this @kahaaga , but shall we just go ahead and ensure all probabilities Estimators have a well defined outocme space? Which means, if input x is necessary, it must already be given at the point where the probability estimator is instantiated?

I think we agreed on this at some point, in some comment, in some PR, somewhere. I'm still totally on board with this.

Datseris commented 1 year ago

Also outcome_space becomes a 1 argument function. ok. we do it then. first things first, #184 first.

kahaaga commented 1 year ago

Yes, let's do one thing at a time, so we don't end up with more conflicting branches.