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Simplify SurrogateTest
#337
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Actually, I am not sure how the conditional data are handled. If a user provides an anonymous function, how does one handle the "conditional data" possibility...? |
I guess that's why |
The more I read the docstring the less understand what |
Hey, @Datseris! These are all good questions. I'm in the process of rethinking the estimator-measure design here (a necessary consequence of JuliaDynamics/ComplexityMeasures.jl#316). This will be a breaking change.
I'm also looking into possible designs that allow us to re-use it, but I haven't landed on anything yet. I'm exploring some options as part of the changes implemented here due to JuliaDynamics/ComplexityMeasures.jl#316.
That is one possible solution that I'm looking into. However, it needs to be determined whether this should be an API requirement, or if we should treat it more loosely. I can't really say anything definitive here before I've finished up the migration to the API in JuliaDynamics/ComplexityMeasures.jl#316, though. I'm super busy at the moment, but will try to finish this up as soon as possible! |
Yes, that would be optimal. We then have to make sure that this is meaning for all implemented (and future) association measures, not just the information theoretic ones. |
I see some problems with
SurrogateTest
.First, we have the same name in TimeseriesSurrogates.jl. Will we have a conflict of names? Perhaps name this as
SurrogateAssocaitionTest
? Or, better yet, do we need a new type at all? Why can't we use the existing type from TimeseiesSurrogates.jl as is?Second, is there a reaspon for
SurrogateTest
to acceptest
as input? A user should create and provide an anonymous function with theest
. If user wants to usemeasure
withest
, then user createsf = (x, y) -> measure(est, x, y)
and providesf
as first argument. We should demonstrate this in the docstring ofSurrogateTest
.Third, I am not sure it is useful to duplicate the table that compares association measures in the docstring. Especially if we remove the redundant
est
then the table offers no extra information versus the one present in the assocation measures page. EDIT: Okay, I am partly wrong. One needs to say which measures are compatible. But we shouldn't duplicate info on what the measures can do or not w.r.t. pairwise or conditional.The text was updated successfully, but these errors were encountered: