paramrf 0.10.6

ParamRF: Parametric Radio Frequency Modelling, Fitting and Sampling

ParamRF: Parametric Radio Frequency Modelling, Fitting and Sampling

ParamRF, or pmrf, is an open-source radio frequency (RF) modelling framework. It provides an object-orientated means of modelling, fitting and sampling both circuit and numerical RF models in the frequency-domain, using JAX and Equinox.

ParamRF
Author	Gary Allen
Homepage	github.com/paramrf/paramrf
Docs	paramrf.github.io/paramrf
Paper	ParamRF: A JAX-Native Framework for Declarative Circuit Modelling

Installation

ParamRF can be installed using pip directly:

pip install paramrf

Optional dependencies

Several additional dependencies are required/recommended for more advanced use-cases.

For PolyChord fitting:

pip install git+https://github.com/PolyChord/PolyChordLite.git anesthetic mpi4py

For BlackJAX fitting:

pip install git+https://github.com/handley-lab/blackjax@nested_sampling anesthetic

For eqx-learn surrogate modeling:

pip install git+https://github.com/eqx-learn/eqx-learn

Citation

If you have used ParamRF for academic work, please cite the original paper:

G.V.C. Allen, D.I.L. de Villiers, (2025). ParamRF: A JAX-native Framework for Declarative Circuit Modelling. arXiv, https://doi.org/10.48550/arXiv.2510.15881.

or with BibTeX:

@article{paramrf,
    doi = {10.48550/arXiv.2510.15881},
    url = {https://doi.org/10.48550/arXiv.2510.15881}, 
    year = {2025},
    month = {Oct},
    title = {ParamRF: A JAX-native Framework for Declarative Circuit Modelling}, 
    author = {Gary V. C. Allen and Dirk I. L. de Villiers},
    eprint = {2510.15881},
    archivePrefix = {arXiv},
    primaryClass = {cs.OH},
}

Contributions

Since the library is in very early stages and likely contains several bugs, contributions are more than welcome by submitting a PR (especially for the docs!). However, before making any major changes, please open an issue so we can discuss the general intention of the contribution.