aind-ephys-utils#

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Helpful methods for exploring in vivo electrophysiology data.

Motivation#

This library is intended to encompass a set of versatile, general-purpose methods for transforming and exploring spike trains and local field potential data. It will be developed in parallel to two other Python packages, aind-ephys-plots and aind-ephys-widgets, but can also be used on its own.

We hope that these libraries will reduce the amount of redundant code written for exploratory analysis performed on high-density electrophysiology data at the Allen Institute for Neural Dynamics. The code will be public from the start, so others are welcome to contribute to the development as well.

Design principles#

Functions added to this library should try to adhere to the following guidelines:

  • Their primary inputs/output are numpy ndarrays, pandas DataFrames, or xarray DataArrays. The analysis code shouldn’t depend on any library-specific Python classes.

  • They have minimal external dependencies. Ideally the library will only require xarray (which itself depends on numpy and pandas), scipy, and scikit-learn, and perhaps a few other packages.

  • They have a variety of use cases. Project-specific code should live in Code Ocean capsules, or eventually separate libraries.