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Installation

You may build distributions in several ways:

  • as a standalone C++ library
  • as a standalone Python package
  • as a Python package wrapping the dynamically-linked C++ library

Note

On OSX, distributions builds with newer versions of clang, but some systems default to g++. You can force distributions to use clang by setting the CC environment variable before running any pip, cmake, or make commands with export CC=clang.

Python Standalone

Install numpy and scipy. Then:

pip install distributions

C++ Standalone

Install requirements:

sudo apt-get install cmake libeigen3-dev

To install in ./lib:

make install

Alternatively, set a custom install location:

CMAKE_INSTALL_PREFIX=/my/prefix make install

Python wrapping libdistributions

Follow instructions for C++ Standalone. Install numpy and scipy. Then:

LIBRARY_PATH=/my/prefix/lib pip install distributions

Warning

When using wrapped libdistributions, the dynamic linker must be able to find the library. The environment variables used to do this differ from platform to platform.

On Linux, you might run python as follows:

LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/my/prefix/lib python

On OSX, you'll need a different flag:

DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:/my/prefix/lib python

If you use virtualenv with virtualenvwrapper and use the virtualenv root as your prefix, it is convenient to add a postactivate hook to set this environment. On Linux, this would look like this:

echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$VIRTUAL_ENV/lib' >> $VIRTUAL_ENV/bin/postactivate

Developer Quick Start

This will install both the static and dynamic versions of libdistributions within a virtualenv, then install the distributions Python package built to wrap libdistributions.

Install cmake. Install numpy, scipy, cython, and nosetests so that they're available within a python virtualenv. Activate that virtualenv. Then:

make test

The top-level Makefile provides many targets useful for development.