Developer's documentation

This documentation addresses users that would like to contribute to the software by either solving bugs, improving documentation, or adding new methods. All contributions come in the form of Pull Requests, for which we strongly advise to follow good practices in scientific code, which means that they are properly formatted, documented, tested, etc.

New indicators or change metrics

As explained already in e.g., SlidingWindowConfig, new indicators or change metrics are standard Julia functions, so you only need to define such a function (and document it, test it, etc.).

New pipeline for estimating changes

This means to contribute a fundamentally new "pipeline" for estimating/detecting transitions in timeseries. This new pipeline defines what a "transition" means. To add a new pipeline follow these steps:

1. Define a new subtype of ChangesConfig
2. Define a new subtype of ChangesResults
3. Add a method for estimate_changes which accepts the new ChangesConfig subtype you defined and returns the ChangesResults subtype you defined.

And that's it!

Optionally you can further extend:

• TransitionsInTimeseries.plot_indicator_changes with the new ChangesResults type you defined. Note the plotting functions are in the ext folder of the repository.
• significant_transitions(res::ChangesResults, signif::Significance) with your new ChangesResults type and as many Significance subtypes you have the capacity to extend for.

New pipeline for estimating significance

Statistically significant changes are "transitions". However, what "significant" means is not universal. There are different ways to test for significance and TransitionsInTimeseries.jl allows various methods.

To add a new pipeline for estimating significance follow these steps:

1. Define a new subtype of Significance
2. Extend significant_transitions(res::ChangesResults, signif::Significance) with your new type and as many ChangesResults subtypes as you have capacity for.

And that's it! Unfortunately so far we have found no way to make the significant_transitions code agnostic of the changes result, so you would need to add a method manually for every ChangesResults.

Optionally you can further extend TransitionsInTimeseries.plot_significance! (which you can find in the ext folder) for visualizing the significance results.