A napari plugin that classifies annotated signals stored in a table in the .features of a Labels layer using scikit-learn RandomForest classifier.
It also provides a sub-signal classifier that can be used to classify sub-signals inside time-series. First it detects sub-sginals with a template matching algorithm and then classifies them also using scikit-learn RandomForest classifier.
This plugin employs and works in synergy with the napari-signal-selector plugin. Take a look at it to see how to annotate signals in a plotter linked to a napari Labels layer with the .features attribute.
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
You can install napari-signal-classifier via pip:
pip install napari-signal-classifier
To install latest development version :
pip install git+https://github.com/zoccoler/napari-signal-classifier.git
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
Distributed under the terms of the BSD-3 license, "napari-signal-classifier" is free and open source software
If you encounter any problems, please file an issue along with a detailed description.