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neurokit2

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About neurokit2

N

neurokit2

Builds and audits reproducible NeuroKit2 research workflows

neurokit2 is an agent skill for building and auditing reproducible research workflows with NeuroKit2, a Python library for physiological signals. It covers preprocessing of physiological time series, event and interval analysis, and multimodal alignment of different signals. The skill is careful about its evidence. The snapshot was checked on 1 October 2026 against stable PyPI release 0.2.13, released on 2 March 2026, against its Python metadata and wheel dependencies, against the GitHub release notes and source at that tag, and against the official API pages and examples. The current wheel requires pandas below 3.0.0, and the refreshed core checks used Python 3.13, NumPy 2.5.3 and pandas 2.3.3, because forcing pandas 3 conflicts with the upstream metadata. The API fragments assume that you supply your own arrays and imports. Some optional paths, such as MNE source reconstruction, cvxEDA, EMD and pyRQA, were source-reviewed but not run. The skill states plainly that synthetic checks establish software behaviour, not empirical validity. Use it when you are analysing physiological signals for research and want the workflow to be reproducible and clearly documented.

View neurokit2All AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/neurokit2