Metadata-Version: 2.1
Name: iminuit
Version: 2.5.0
Summary: Jupyter-friendly Python frontend for MINUIT2 in C++
Home-page: http://github.com/scikit-hep/iminuit
Author: Piti Ongmongkolkul and the iminuit team
Maintainer: Hans Dembinski
Maintainer-email: hans.dembinski@gmail.com
License: MIT
Download-URL: https://pypi.python.org/pypi/iminuit
Project-URL: Documentation, https://iminuit.readthedocs.io
Project-URL: Source Code, http://github.com/scikit-hep/iminuit
Platform: Windows
Platform: Linux
Platform: Mac OS-X
Platform: Unix
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Requires-Dist: numpy

*iminuit* is a Jupyter-friendly Python interface for the *Minuit2* C++ library maintained by CERN's ROOT team.

It can be used as a general robust function minimisation method, but is most
commonly used for likelihood fits of models to data, and to get model parameter
error estimates from likelihood profile analysis.

- Supported CPython versions: 3.6+
- Supported PyPy versions: 3.6
- Supported platforms: Linux, OSX and Windows.

* PyPI: https://pypi.org/project/iminuit
* Documentation: http://iminuit.readthedocs.org
* Source: https://github.com/scikit-hep/iminuit
* Gitter: https://gitter.im/Scikit-HEP/community
* License: *MINUIT2* is LGPL-2.1 and *iminuit* is MIT
* Citation: https://doi.org/10.5281/zenodo.3949207

In a nutshell
-------------

.. code-block:: python

    from iminuit import Minuit

    def fcn(x, y, z):
        return (x - 2) ** 2 + (y - 3) ** 2 + (z - 4) ** 2

    fcn.errordef = Minuit.LEAST_SQUARES

    m = Minuit(fcn, x=0, y=0, z=0)

    m.migrad()  # run optimiser
    print(m.values)  # x: 2, y: 3, z: 4

    m.hesse()   # run covariance estimator
    print(m.errors)  # x: 1, y: 1, z: 1

Versions
--------

**The current 2.x series has introduced breaking interfaces changes with respect to the 1.x series.**

All interface changes are documented in the `changelog`_ with recommendations how to upgrade. To keep existing scripts running, pin your major iminuit version to <2, i.e. ``pip install 'iminuit<2'`` installs the 1.x series.

.. _changelog: https://iminuit.readthedocs.io/en/stable/changelog.html


