Metadata-Version: 2.1
Name: root-numpy
Version: 4.7.3
Summary: The interface between ROOT and NumPy
Home-page: http://scikit-hep.org/root_numpy
Author: the root_numpy developers
Author-email: rootpy-dev@googlegroups.com
Maintainer: Noel Dawe
Maintainer-email: noel@dawe.me
License: new BSD
Description: .. image:: https://img.shields.io/pypi/v/root_numpy.svg
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        root_numpy is a Python extension module that provides an efficient interface
        between `ROOT <http://root.cern.ch/>`_ and `NumPy <http://www.numpy.org/>`_.
        root_numpy's internals are compiled C++ and can therefore handle large amounts
        of data much faster than equivalent pure Python implementations.
        
        With your ROOT data in NumPy form, make use of NumPy's `broad library
        <http://docs.scipy.org/doc/numpy/reference/>`_, including fancy indexing,
        slicing, broadcasting, random sampling, sorting, shape transformations, linear
        algebra operations, and more. See this `tutorial
        <https://docs.scipy.org/doc/numpy-dev/user/quickstart.html>`_ to get started.
        NumPy is the fundamental library of the scientific Python ecosystem. Using
        NumPy arrays opens up many new possibilities beyond what ROOT offers. Convert
        your TTrees into NumPy arrays and use `SciPy <http://www.scipy.org/>`_ for
        numerical integration and optimization, `matplotlib <http://matplotlib.org/>`_
        for plotting, `pandas <http://pandas.pydata.org/>`_ for data analysis,
        `statsmodels <http://statsmodels.sourceforge.net/>`_ for statistical modelling,
        `scikit-learn <http://scikit-learn.org/>`_ for machine learning, and perform
        quick exploratory analysis in a `Jupyter notebook <https://jupyter.org/>`_.
        
        At the core of root_numpy are powerful and flexible functions for converting
        `ROOT TTrees <https://root.cern.ch/doc/master/classTTree.html>`_ into
        `structured NumPy arrays
        <http://docs.scipy.org/doc/numpy/user/basics.rec.html>`_ as well as converting
        NumPy arrays back into ROOT TTrees. root_numpy can convert branches of strings
        and basic types such as bool, int, float, double, etc. as well as
        variable-length and fixed-length multidimensional arrays and 1D or 2D vectors
        of basic types and strings. root_numpy can also create columns in the output
        array that are expressions involving the TTree branches similar to
        ``TTree::Draw()``.
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
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 :: Python :: 3.5
Classifier: Programming Language :: C++
Classifier: Programming Language :: Cython
Classifier: Development Status :: 5 - Production/Stable
Provides-Extra: with-numpy
