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PyHank - Quasi-Discrete Hankel Transforms for Python

Edward Rogers

Documentation Status CI Coverage PyPI version Ruff

PyHank is a python implementation of the quasi-discrete Hankel transform as developed by Manuel Guizar-Sicairos and Julio C. Guitierrez-Vega:

"Computation of quasi-discrete Hankel transforms of the integer order for propagating optical wave fields" Manuel Guizar-Sicairos and Julio C. Guitierrez-Vega J. Opt. Soc. Am. A 21 (1) 53-58 (2004)

It operates on functions stored in NumPy arrays. If you want a Hankel transform that operates on a callable function, you may be interested in hankel by Steven Murray.

PyHank 3.0 includes a high-performance compiled Rust backend (powered by hankrs), delivering 10x–50x speedups for transform setup and computation across multi-dimensional arrays, with automatic fallback to pure Python where a compiler is unavailable.

I have used this code extensively for beam-propagation-method calculations of radially-symmetric beams. In the radially symmetric case, the 2D FFT over x and y that would be used in a non-symmetric system is replaced by a 1D QDHT over r, making the computational load much lighter and allowing bigger simulations.

PyHank was inspired by Adam Wyatt's Matlab version which I used for many years, before moving to Python and needing my own implementation. It aims to simplify the interface (using Python's object-oriented approach) and utilise existing NumPy/SciPy functions wherever possible.

It has both a simple single-shot interface, and an object-oriented approach that precomputes transform matrices to speed up computation significantly when making multiple transforms on the same grid.

Contributions and comments are welcome using GitHub at: https://github.com/etfrogers/pyhank

Installation

Pre-compiled binary wheels (with compiled native Rust acceleration) are provided on PyPI for 64-bit Linux, macOS (Apple Silicon and Intel), and 64-bit Windows:

pip install pyhank

For development and running tests:

pip install -e .[dev]

For building documentation:

pip install -e .[docs]

Bugs & Contribution

Please use Github to report bugs, feature requests and submit your code: http://github.com/etfrogers/pyhank

Documentation

The documentation for PyHank can be found at Read the docs

Usage

See the Usage examples at ReadTheDocs

Project links

Data verified by PyPI on Sep 1, 2026
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  • Released:
Stable release available (2.5.1)

1 maintainer

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Avatar for etfrogers from gravatar.com etfrogers

Credits

Author: Edward Rogers

GitHub Statistics

Data verified by PyPI on Sep 1, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT

Requires

Python >=3.10

Provides Extra

dev docs

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