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README.md

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@@ -10,14 +10,17 @@ EigenPy — Efficient Python bindings between Numpy/Eigen
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<a href="https://github.com/psf/black"><img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black"></a>
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</p>
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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.
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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 via Boost.Python.
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**EigenPy** provides:
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- full memory sharing between Numpy and Eigen avoiding memory allocation
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- full support Eigen::Ref avoiding memory allocation
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- full support of the Eigen::Tensor module
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- exposition of the Geometry module of Eigen for easy code prototyping
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- standard matrix decomposion routines of Eigen such as the Cholesky decomposition, SVD decomposition, QR decomposition, and etc.
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- full support of SWIG objects
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- full support of runtime declaration of Numpy scalar types
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- extended API to expose std::vector types
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## Setup
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### The Conda approach
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You simply need this simple line:
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```
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```bash
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conda install eigenpy -c conda-forge
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```
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### Ubuntu
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You can easily install **EigenPy** from binairies.
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curl http://robotpkg.openrobots.org/packages/debian/robotpkg.key | sudo apt-key add -
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```
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3. You need to run at least once apt update to fetch the package descriptions:
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```
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```bash
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sudo apt-get update
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```
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#### Install EigenPy
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4. The installation of **EigenPy** and its dependencies is made through the line:
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For Python 2.7
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```
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sudo apt install robotpkg-py27-eigenpy
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```
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or for Python 3.{5,6,7}
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```
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```bash
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sudo apt install robotpkg-py35-eigenpy
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```
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where 35 should be replaced by the python 3 you want to work this (e.g. `robotpkg-py36-eigenpy` to work with Python 3.6).

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