DynamicsAndNeuralSystems / DynamicsAndNeuralSystems/pyspi

Similarity or Distance - Higher is closer or lower is closer?

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Dominant language
Python
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Description

First of all, thanks for creating this awesome package.
I want to use it to evaluate the measures for finding related time series within industrial/building time series datasets.

For that, I have the following questions:
Is there a place where I can quickly gather whether the outcome of a measure is a similarity or a distance? In other words, whether something is more related if the number is higher (similarity) or more related if the metric is lower (distance).

The simplest example would be the differentiation between correlation and Euclidean distance of two time series. For related time series, one could expect the correlation to be high but the Euclidean distance to be low. When, for example, searching for the k most related time series throughout the different metrics implemented here, this information is of great interest.

I'm sorry if I missed that in the publication or the paper. Kindly refer me if there is information on that anywhere.

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First steps

  1. Read the whole issue, then the project's contributing guide.
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Research direction

No file or test is named. Review the package's implemented measures and the publication or paper referenced in the issue to determine which outputs are similarities and which are distances; done means users have a clear place to identify whether higher or lower values indicate closer relationships.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
documentation
Issue type
Documentation
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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