functions provides a variety of special functions, including common test functions for parameter estimations such as Rosenbrock and Griewank, test functions for parameter sensitivity analysis such as the Ishigami and Homma function, several forms of the logistic function and its first and second derivatives, and a variety of functions together with robust and square cost functions to use with scipy.optimize package.
The module is part of the JAMS Python package https://github.com/mcuntz/jams_python It will be synchronised with the JAMS package irregularily if used in other packages.
|copyright:||Copyright 2014-2020 Matthias Cuntz, see AUTHORS.md for details.|
|license:||MIT License, see LICENSE for details.|
||Module with general functions that are not specialised for fitting, optimisation, sensitivity analysis, etc.|
||Module defines common functions that are used in curve_fit or fmin parameter estimations.|
||Module with several forms of the logistic function and its first and second derivatives.|
||Module provides common test functions for parameter estimation and optimisation algorithms such as Rosenbrock and Griewank functions.|
||Module provides test functions for parameter sensitivity analysis from|