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Python implementation of Espresso

Hi,

First of all thanks for the great article and open sourcing the matlab code for Espresso. Unfortunately I don't have a matlab license but I still would like try out Epsresso to assess performance on some of the time series cases I have.

I would gladly help to implement the python version of Espresso, but unfortunately the information in the article is insufficient for me to implement. I also noticed that the current matlab implementation does not follow the same conventions as the article. Would you be willing to share some extra details to help me implement a python version of Espresso?

Could we start with the WCAC calculation?

Importance of GT

Dear Authors,

From this implementation, it seems GT is the number of segment boundaries that is actually obtained from the ground-truth observations. However, is this parameter required? As one may directly need the number of change points without having any prior information about the actual number of changes in the signal.

Also, is there any python implementation of the same?

Thanks in advance.

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