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rfmeasurement

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An open-source Python framework for uncertainty-aware validation and reproducible analysis of RF measurements.

Status: early alpha (0.2.0). The public API is not yet stable and may change without notice between 0.x releases. See the roadmap for current progress and the changelog for release notes.

Documentation: https://rfmeasurement.readthedocs.io/en/latest/

Statement of need

RF measurement data (S-parameters and related quantities) is commonly analyzed without a structured record of measurement quality, uncertainty, or provenance. rfmeasurement adds a layer on top of established RF network-analysis tooling to turn raw measurement data into validated, uncertainty-aware, reproducible scientific results.

Do not only report an RF result. Report how the result was obtained, how trustworthy the measurement is, and what uncertainty contributes to the final value.

rfmeasurement does not replace scikit-rf; it builds on it, focusing on measurement provenance, measurement-quality assessment, uncertainty modelling and propagation, and reproducible reporting. See docs/scope.md for the boundary between the two projects.

Documentation

The published documentation (installation, API reference, contributing, license) is at https://rfmeasurement.readthedocs.io/en/latest/.

The full design and development specification lives in docs/:

Installation

pip install rfmeasurement

For development, see CONTRIBUTING.md for setting up a virtual environment and installing with the dev extra.

Supported Python versions: 3.10, 3.11, 3.12, 3.13.

Development

pytest

See CONTRIBUTING.md for how to propose changes, including scientific contributions.

Citation

If you use rfmeasurement in research, please cite it using the metadata in CITATION.cff. Every release is archived on Zenodo: 10.5281/zenodo.22058515 (this DOI always resolves to the latest version).

License

BSD 3-Clause License. See LICENSE.

Code of conduct

This project follows the Contributor Covenant.

Metadata

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