espresso
A Python framework for preprocessing, processing, visualization, event detection, and event curation of high-density time-series signals and multi-channel data streams.
Key Capabilities
- Signal Preprocessing: Optimized digital filtering pipelines and artifact rejection workflows.
- Event Detection: Automated extraction of transient oscillations and sharp-wave ripples.
- Signal Visualization: Modern hardware-accelerated time-series traces and interpolated spectrogram displays.
- Event Curation: Interactive manual and automated classification workflows to review, filter, and tag detected transient neural events. (Coming soon)
Installation
pip install espresso-neuro
Usage
Refer to the examples/ directory for complete, runnable pipeline scripts demonstrating signal processing, downsampling metrics, and hardware-accelerated user interface execution.
License & Attribution
This project is licensed under the GNU General Public License v3 - see the LICENSE file for details.
Third-Party Code
- The ripple detection module in
src/espresso/hfo/ripple_detector.pycontains algorithm logic adapted from the FKLab Python Core library by the Kloosterman Lab.
1 maintainer
Metadata
1 maintainer
Release files for espresso-neuro 26.5.15
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| espresso_neuro-26.5.15-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 106.0 kB
Release files / espresso_neuro-26.5.15.tar.gz
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