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After #413 is merged, we will have a nice workflow for defining regions of interest, and determining if positions were inside them or not.
This should enable us to write an example (using the EPM sample dataset) in which we use these features to compute time spent in the open vs closed arms of the maze.
The example should essentially replicate the analysis presented in this notebook (from section D onwards).
I'm happy to assign this to myself, as I wrote that jupyter notebook to begin with.
The text was updated successfully, but these errors were encountered:
After #413 is merged, we will have a nice workflow for defining regions of interest, and determining if positions were inside them or not.
This should enable us to write an example (using the EPM sample dataset) in which we use these features to compute time spent in the open vs closed arms of the maze.
The example should essentially replicate the analysis presented in this notebook (from section D onwards).
I'm happy to assign this to myself, as I wrote that jupyter notebook to begin with.
The text was updated successfully, but these errors were encountered: