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optimagic is a Python package for numerical optimization. It is a unified interface to optimizers from SciPy, NlOpt and many other Python packages.
optimagic’s minimize function works just like SciPy’s, so you don’t have to adjust
your code. You simply get more optimizers for free. On top you get powerful diagnostic
tools, parallel numerical derivatives and more. If you want to see what optimagic can
do, check out this tutorial
optimagic was formerly called estimagic, because it also provides functionality to perform statistical inference on estimated parameters. estimagic is now a subpackage of optimagic, which is documented here.
New users of optimagic should read this first.
Detailed instructions for specific and advanced tasks.
Installation instructions for optimagic and optional dependencies.
List of numerical optimizers and their optional parameters.
Background information on key topics central to the package.
Detailed description of the optimagic API.
Collection of tutorials, talks, and screencasts on optimagic.
We thank all institutions that have funded or supported optimagic (formerly estimagic)
Useful links for search: Index | Module Index | Search Page