Metadata-Version: 2.1
Name: gwr-inversion
Version: 1.0.1
Summary: GWR Algorithm Numerical Laplace Inversion
Home-page: https://github.com/petbox-dev/gwr
Author: David S. Fulford
Author-email: petbox.dev@gmail.com
License: UNKNOWN
Description: Gaver-Wynn-Rho Algorithm
        ------------------------
        
        This is a Python reproduction of the Mathematica package that provides the GWR
        function, ``NumericalLaplaceInversion.m``.
        
        https://library.wolfram.com/infocenter/MathSource/4738/
        
        This package provides only one function: ``gwr``. The function calculates the
        value of the inverse of a Laplace transform at a specified time value,
        ``Sequence`` of time values, or numpy array of time values.
        
        The Laplace transform should be provided as a function that uses the ``mpmath``
        library for a scalar value of the Laplace parameter.  The ``math`` library and
        ``numpy`` functions do not support multiprecision math and will return invalid
        results if they are used.
        
        Simple Example
        --------------
        
        .. code-block:: python
        
            >>> import math
            >>> from gwr_inversion import gwr
            >>> from mpmath import mp
        
            >>> def lap_ln_fn(s: float):
            ...     # log function
            ...     return -mp.log(s) / s - 0.577216 / s
        
            >>> gwr(lap_log_fn, time=5.0, M=32)
                mpf('1.6094375773356333')
        
            >>> math.log(5.0)
            1.6094379124341003
        
        
        See the notebooks in ``test\`` for other use examples.
        
        The method is described in: ValkÃ³, P.P., and Abate J. 2002. Comparison of
        Sequence Accelerators for the Gaver Method of Numerical Laplace Transform
        Inversion. *Computers and Mathematics with Application* **48** (3): 629â€“636.
        https://doi.org/10.1016/j.camwa.2002.10.017.
        
        More information on multi-precision inversion can be found in: ValkÃ³, P.P.and
        Vajda, S. 2002. Inversion of Noise-Free Laplace Transforms: Towards a
        Standardized Set of Test Problems. *Inverse Problems in Engineering* **10** (5):
        467-483. https://doi.org/10.1080/10682760290004294.
        
Keywords: laplace,inversion,transform,gwr
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries
Classifier: Typing :: Typed
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
