Metadata-Version: 2.1
Name: hankel
Version: 0.0.0.dev0
Summary: Hankel Transformations using method of Ogata 2005
Home-page: https://github.com/steven-murray/hankel
Author: Steven Murray
Author-email: steven.murray@curtin.edu.au
License: MIT
Description: hankel
        ======
        
        .. image:: https://travis-ci.org/steven-murray/hankel.svg?branch=master
           :target: https://travis-ci.org/steven-murray/hankel
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        .. image:: http://joss.theoj.org/papers/10.21105/joss.01397/status.svg
           :target: https://doi.org/10.21105/joss.01397
        .. image:: https://img.shields.io/pypi/v/hankel.svg
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           :target: https://github.com/ambv/black
        
        Perform simple and accurate Hankel transformations using the method of
        Ogata 2005.
        
        Hankel transforms and integrals are commonplace in any area in which
        Fourier Transforms are required over fields that
        are radially symmetric (see
        `Wikipedia <https://en.wikipedia.org/wiki/Hankel_transform>`_ for a
        thorough description).
        They involve integrating an arbitrary function multiplied by a Bessel
        function of arbitrary order (of the first kind).
        Typical integration schemes often fail because of the highly
        oscillatory nature of the transform. Ogata's
        quadrature method used in this package provides a fast and accurate
        way of performing the integration based on
        locating the zeros of the Bessel function.
        
        Features
        --------
        
        -  Accurate and fast solutions to many Hankel integrals
        -  Easy to use and re-use
        -  Arbitrary order transforms
        -  Built-in support for radially symmetric Fourier Transforms
        -  Thoroughly tested.
        -  only Python 3 compatible.
        
        Quick links
        -----------
        
        - **Documentation:** `<https://hankel.readthedocs.io>`_
        - **Quickstart+Description:** `Getting Started <https://hankel.readthedocs.io/en/latest/demos/getting_started.html>`_
        
        Installation
        ------------
        Either clone the repository and install locally (best for developer installs)::
        
            $ git clone https://github.com/steven-murray/hankel.git
            $ cd hankel/
            $ pip install -U .
        
        Or install from PyPI::
        
            $ pip install hankel
        
        Or install with conda::
        
            $ conda install -c conda-forge hankel
        
        The only dependencies are `numpy <https://www.numpy.org>`_,
        `scipy <https://www.scipy.org>`_ and `mpmath <https://www.mpmath.org>`_.
        These will be installed automatically if they are not already installed.
        
        Dependencies required purely for development (testing and linting etc.) can be installed
        via the optional extra `pip install hankel[dev]`. If using `conda`, they can still be
        installed via `pip`: `pip install -r requirements_dev.txt`.
        
        For instructions on testing `hankel` or any other development- or contribution-related
        issues, see the `contributing guide <CONTRIBUTING.rst>`_.
        
        Acknowledging
        -------------
        If you find `hankel` useful in your research, please cite
        
            S. G. Murray and F. J. Poulin, "hankel: A Python library for performing simple and
            accurate Hankel transformations", Journal of Open Source Software,
            4(37), 1397, https://doi.org/10.21105/joss.01397
        
        Also consider starring this repository!
        
        References
        ----------
        Based on the algorithm provided in
        
            H. Ogata, A Numerical Integration Formula Based on the Bessel
            Functions, Publications of the Research Institute for Mathematical
            Sciences, vol. 41, no. 4, pp. 949-970, 2005. DOI: 10.2977/prims/1145474602
        
        Also draws inspiration from
        
            Fast Edge-corrected Measurement of the Two-Point Correlation
            Function and the Power Spectrum Szapudi, Istvan; Pan, Jun; Prunet,
            Simon; Budavari, Tamas (2005) The Astrophysical Journal vol. 631 (1)
            DOI: 10.1086/496971
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Requires-Python: >=3.5
Provides-Extra: dev
Provides-Extra: docs
Provides-Extra: tests
