Metadata-Version: 1.1
Name: iminuit
Version: 1.2
Summary: Interactive Minimization Tools based on MINUIT
Home-page: https://github.com/iminuit/iminuit
Author: Piti Ongmongkolkul
Author-email: piti118@gmail.com
License: UNKNOWN
Download-URL: http://pypi.python.org/packages/source/i/iminuit/iminuit-1.2.tar.gz
Description: .. image:: https://img.shields.io/pypi/v/iminuit.svg
           :target: https://pypi.python.org/pypi/iminuit
        .. image:: https://img.shields.io/pypi/dm/iminuit.svg
           :target: https://pypi.python.org/pypi/iminuit
        
        iminuit
        -------
        
        Interactive IPython-Friendly Minimizer based on
        `SEAL Minuit2 <http://seal.web.cern.ch/seal/work-packages/mathlibs/minuit/release/download.html>`_.
        (A slightly modified version is included in the package no need to install it separately)
        
        It is designed from ground up to be fast, interactive and cython friendly. iminuit
        extracts function signature very permissively starting from checking *func_code*
        down to last resort of parsing docstring(or you could tell iminuit to stop looking
        and take your answer). The interface is inspired heavily
        by PyMinuit and the status printout is inspired by ROOT Minuit. iminuit is
        mostly compatible with PyMinuit(with few exceptions). Existing PyMinuit
        code can be ported to iminuit by just changing the import statement.
        
        In a nutshell::
        
            from iminuit import Minuit
            def f(x, y, z):
                return (x - 2) ** 2 + (y - 3) ** 2 + (z - 4) ** 2
            m = Minuit(f)
            m.migrad()
            print(m.values)  # {'x': 2,'y': 3,'z': 4}
            print(m.errors)  # {'x': 1,'y': 1,'z': 1}
        
        Install
        -------
        
        First install cython (`pip install cython`), then
        
        ::
        
            python setup.py install
        
        or from pip::
        
            pip install iminuit
        
        For Windows, Christoph Gohlke made a nice windows binary to save you all from Windows compilation nightmare:
        
           `http://www.lfd.uci.edu/~gohlke/pythonlibs/#iminuit <http://www.lfd.uci.edu/~gohlke/pythonlibs/#iminuit>`_
        
        Tutorial
        --------
        
        All the tutorials are in tutorial directory. You can view it online too.
        
        - `Quick start <http://nbviewer.ipython.org/urls/raw.github.com/iminuit/iminuit/master/tutorial/tutorial.ipynb>`_
        - `Hard Core Cython tutorial <http://nbviewer.ipython.org/urls/raw.github.com/iminuit/iminuit/master/tutorial/hard-core-tutorial.ipynb>`_.
          If you need to do a huge likelihood fit that needs speed, or you want to learn how to
          parallelize your stuff, this is for you.
        
        
        Documentation
        -------------
        
        http://iminuit.readthedocs.org/
        
        Technical Stuff
        ---------------
        
        Using it as a black box is a bad idea. Here are some fun reads; the order is given
        by the order I think you should read.
        
        * Wikipedia for `Quasi Newton Method <http://en.wikipedia.org/wiki/Quasi-Newton_method>`_ and
          `DFP formula <http://en.wikipedia.org/wiki/Davidon-Fletcher-Powell_formula>`_.
          The magic behind migrad.
        * `Variable Metric Method for Minimization <http://www.ii.uib.no/~lennart/drgrad/Davidon1991.pdf>`_ William Davidon 1991
        * `A New Approach to Variable Metric Algorithm. <http://comjnl.oxfordjournals.org/content/13/3/317.full.pdf+html>`_ (R.Fletcher 1970)
        * Original Paper: `MINUIT - A SYSTEM FOR FUNCTION MINIMIZATION AND ANALYSIS OF THE PARAMETER ERRORS AND CORRELATIONS <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.158.9157&rep=rep1&type=pdf>`_ by Fred James and Matts Roos.
        
        You can help
        ------------
        
        Github allows you to contribute to this project very easily just fork the
        repository, make changes and submit a pull request.
        
        Here's the list of concrete open issues and feature requests:
        https://github.com/iminuit/iminuit
        
        More generally any contribution to the docs, tests and package itself is welcome!
        
        * Documentation. Tell us what's missing, what's incorrect or misleading.
        * Tests. If you have an example that shows a bug or problem, please file an issue!
        * Performance. If you are a C/cython/python hacker go ahead and make it faster.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: C++
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: License :: OSI Approved :: MIT License
