<commit_before>EigenPy — Efficient Python bindings between Numpy/Eigen
======

<p align="center">
  <a href="https://opensource.org/licenses/BSD-2-Clause"><img src="https://img.shields.io/badge/License-BSD%202--Clause-green.svg" alt="License"/></a>
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  <a href="https://anaconda.org/conda-forge/eigenpy"><img src="https://img.shields.io/conda/vn/conda-forge/eigenpy.svg" alt="Conda Version"/></a>
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**EigenPy** is an open source framework which allows to bind the famous [Eigen](http://eigen.tuxfamily.org) C++ library in Python.

**EigenPy** provides:
 - full memory sharing between Numpy and Eigen avoiding memory allocation
 - full support Eigen::Ref avoiding memory allocation
 - exposition of the Geometry module of Eigen for easy code prototyping
 - standard matrix decomposion routines of Eigen such as the Cholesky decomposition, SVD decomposition, QR decomposition, and etc.
 - full support of SWIG objects

## Setup

The installation of **EigenPy** on your computer is made easy for Linux/BSD, Mac OS X and Windows environments.
<commit_msg>readme: remove useless badge<commit_after>EigenPy — Efficient Python bindings between Numpy/Eigen
======

<p align="center">
  <a href="https://opensource.org/licenses/BSD-2-Clause"><img src="https://img.shields.io/badge/License-BSD%202--Clause-green.svg" alt="License"/></a>
  <a href="https://travis-ci.org/stack-of-tasks/eigenpy"><img src="https://travis-ci.org/stack-of-tasks/eigenpy.svg?branch=master" alt="Build Status"/></a>
  <a href="https://anaconda.org/conda-forge/eigenpy"><img src="https://img.shields.io/conda/dn/conda-forge/eigenpy.svg" alt="Conda Downloads"/></a>
  <a href="https://anaconda.org/conda-forge/eigenpy"><img src="https://img.shields.io/conda/vn/conda-forge/eigenpy.svg" alt="Conda Version"/></a>
  <a href="https://badge.fury.io/py/eigenpy"><img src="https://badge.fury.io/py/eigenpy.svg" alt="PyPI version" height="18"></a>
</p>

**EigenPy** is an open source framework which allows to bind the famous [Eigen](http://eigen.tuxfamily.org) C++ library in Python.

**EigenPy** provides:
 - full memory sharing between Numpy and Eigen avoiding memory allocation
 - full support Eigen::Ref avoiding memory allocation
 - exposition of the Geometry module of Eigen for easy code prototyping
 - standard matrix decomposion routines of Eigen such as the Cholesky decomposition, SVD decomposition, QR decomposition, and etc.
 - full support of SWIG objects

## Setup

The installation of **EigenPy** on your computer is made easy for Linux/BSD, Mac OS X and Windows environments.

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