Metadata-Version: 2.1
Name: iminuit
Version: 2.8.3
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+LGPL
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
Description: .. |iminuit| image:: doc/_static/iminuit_logo.svg
           :alt: iminuit
           :target: http://iminuit.readthedocs.io/en/latest
        
        |iminuit|
        =========
        
        .. skip-marker-do-not-remove
        
        .. image:: https://scikit-hep.org/assets/images/Scikit--HEP-Project-blue.svg
           :target: https://scikit-hep.org
        .. image:: https://img.shields.io/pypi/v/iminuit.svg
           :target: https://pypi.org/project/iminuit
        .. image:: https://img.shields.io/conda/vn/conda-forge/iminuit.svg
           :target: https://github.com/conda-forge/iminuit-feedstock
        .. image:: https://coveralls.io/repos/github/scikit-hep/iminuit/badge.svg?branch=develop
           :target: https://coveralls.io/github/scikit-hep/iminuit?branch=develop
        .. image:: https://readthedocs.org/projects/iminuit/badge/?version=stable
           :target: https://iminuit.readthedocs.io/en/stable
        .. image:: https://img.shields.io/pypi/l/iminuit
          :alt: License
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3949207.svg
           :target: https://doi.org/10.5281/zenodo.3949207
        
        *iminuit* is a Jupyter-friendly Python interface for the *Minuit2* C++ library maintained by CERN's ROOT team.
        
        Minuit was designed to minimise statistical cost functions, for likelihood and least-squares fits of parametric models to data. It provides the best-fit parameters and error estimates from likelihood profile analysis.
        
        - Supported CPython versions: 3.6+
        - Supported PyPy versions: 3.6
        - Supported platforms: Linux, OSX and Windows.
        
        The iminuit package comes with additional features:
        
        - Included cost functions for binned and unbinned maximum-likelihood and (robust)
          least-squares fits
        - Support for SciPy minimisers
        - Numba support (optional)
        
        Checkout our large and comprehensive list of `tutorials`_ that take you all the way from beginner to power user. For help and how-to questions, please use the `discussions`_ on GitHub.
        
        .. image:: https://mybinder.org/badge_logo.svg
           :target: https://mybinder.org/v2/gh/scikit-hep/iminuit/develop?filepath=doc%2Ftutorial
        
        In a nutshell
        -------------
        
        .. code-block:: python
        
            from iminuit import Minuit
        
            def cost_function(x, y, z):
                return (x - 2) ** 2 + (y - 3) ** 2 + (z - 4) ** 2
        
            fcn.errordef = Minuit.LEAST_SQUARES
        
            m = Minuit(cost_function, 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
        .. _tutorials: https://iminuit.readthedocs.io/en/stable/tutorials.html
        .. _discussions: https://github.com/scikit-hep/iminuit/discussions
        
Platform: UNKNOWN
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
Provides-Extra: test
Provides-Extra: doc
