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 dataecoglib.vis
multiple plotting modules for visualizing multi-channel timeseries, spatial maps, and other resultsecoglib.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.