ecoglib: visualization and statistics for high density microecog signals

This library contains high-level analysis tools for "topos" and "chronos" aspects of spatio-temporal signals (array timesries). The packages are organized for

• ecoglib.estimation statistical estimation tools for spatial, timeseries, and general data
• ecoglib.vis multiple plotting modules for visualizing multi-channel timeseries, spatial maps, and other results
• ecoglib.signal_testing signal diagonstics for electrode based recordings

This library builds on top of ecogdata, which can preprocess electrode recordings from multiple file types

Install

First step: set up ecogdata following instructions here: https://github.com/miketrumpis/ecogdata

Whether you have chosen to use conda or a plain virtual environment, use pip to install ecoglib.

Choose whether to use PyQt5 or PySide2.

• PyQt5: this is probably the best option (presently), but it is known not to work on Windows 8
• PySide2: also works, has a less restrictive license

This choice affects the install variation, which is specified in the brackets. You can either clone & install in one step (using PyQt5 in these example, replace with "pyside2" if needed):

$ pip install "ecoglib[pyqt] @ git+https://github.com/miketrumpis/ecoglib.git"

Or, to track the repository, clone and install separately.

$ git clone https:github.com/miketrumpis/ecoglib.git
$ pip install ./ecoglib[pyqt]

Install variation for testing

To run tests, install with the [pyqt,test] variation and run

$ python -m pytest --pyargs ecoglib

Docs & demo notebooks

To build API documentation and usage demos, you must clone the repository. Then add [pyqt,docs] to the install command to get Sphinx and other tools. You can now run:

$ cd docs
$ make all

Alternatively, install jupyter and run the notebooks in docs/source/usage_demos interactively.