Difference between revisions of "Minfx"
(Submission of the minfx project.)
|Line 19:||Line 19:|
Revision as of 17:30, 8 March 2013
The minfx project is a Python package for numerical optimisation, being a large collection of standard minimisation algorithms. This includes the line search methods: steepest descent, back-and-forth coordinate descent, quasi-Newton BFGS, Newton, Newton-CG; the trust-region methods: Cauchy point, dogleg, CG-Steihaug, exact trust region; the conjugate gradient methods: Fletcher-Reeves, Polak-Ribiere, Polak-Ribiere +, Hestenes-Stiefel; the miscellaneous methods: Grid search, Simplex, Levenberg-Marquardt; and the augmented function constraint algorithms: logarithmic barrier and method of multipliers (or augmented Lagrangian method).
DocumentationThe API documentation with full descriptions of all the optimisation algorithms is available at http://home.gna.org/minfx/.
released on 23 September 2014
|License||Verified by||Verified on||Notes|
|GNU GPLv3+||Jgay||8 March 2013|
Leaders and contributors
|Edward d'Auvergne||Project Admin|
Resources and communication
|Developer||Mailing List Info/Archive||https://mail.gna.org/public/minfx-commits/|
|User||Mailing List Subscribe||http://gna.org/mail/?group=minfx|
|Developer||VCS Repository Webview||http://svn.gna.org/viewcvs/minfx/|
|User||Mailing List Info/Archive||https://mail.gna.org/public/minfx-announce/|
|Developer||Mailing List Info/Archive||https://mail.gna.org/public/minfx-devel/|
|Required to use||Python|
|Required to use||numpy|
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the page “GNU Free Documentation License”.
The copyright and license notices on this page only apply to the text on this page. Any software or copyright-licenses or other similar notices described in this text has its own copyright notice and license, which can usually be found in the distribution or license text itself.