This package contains modules for calculating and approximating the Mittag-Leffler function.
The mittag_leffler.py module contains a Python port of
a published
Matlab implementation of
the generalized Mittag-Leffler function, written by Konrad Hinsen. The module ml_internal.py contains the internal functions for mittag_leffler.py. The script test_ml.py contains tests for the functions in mittag_leffler.py. To use the Python port of the Matlab implementation, simply import ml from mittag_leffler.py.
The pade_approx.py module contains a Python implementation of a global Pade approximation for the Mittag-Leffler function as described by Sarumi, Furati, and Khaliq. This approximation is valid for z < 0, 0 < alpha < 1, beta >= alpha, (alpha, beta) != (1, 1). The approximaton is highly accurate and requires 3 orders of magnitude less computation time than the Matlab algorithm.