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PyNE: The Nuclear Engineering Toolkit

branch: staging
readme.rst

PyNE: The Nuclear Engineering Toolkit

The PyNE project aims to provide a common set of tools for nuclear science and engineering needs.

If you are interested in the package itself, or would like to help and contribute, please let us know either on the mailing list (https://groups.google.com/forum/#!forum/pyne-dev, pyne-dev@googlegroups.com) or github.

Examples, documentation, and more can be found at http://pyne.io/, the official PyNE projectsite.

Installation

Dependencies

PyNE has the following dependencies:

  1. CMake (>= 2.8.5)
  2. NumPy (>= 1.8.0)
  3. SciPy
  4. Cython (>= 0.19.1)
  5. HDF5
  6. PyTables
  7. Python 2.7

Additionally, building the documentation requires the following:

  1. Sphinx
  2. SciSphinx
  3. breathe
  4. PrettyTable

Binary

A binary distribution of PyNE is currently available for windows only on 32-bit python using conda. In order to install use the following command:

conda install -c https://conda.binstar.org/batesca pyne_win32py27

Conda binaries are coming soon for other platforms.

Source

Installing PyNE from source is a two-step process. First, download and unzip the source (zip, tar). Then run the following commands from the unzipped directory:

cd pyne/
python setup.py install --user
scripts/nuc_data_make

The setup.py command compiles and installs the PyNE source code. The nuc_data_make builds and installs a database of nuclear data. Unfortunately, this must be done as a second step because most nuclear data is under some form of license restriction or export control which prevents the developers from distributing it with PyNE. However, the nuc_data_make program (which is installed by setup.py) will do its best to find relevant nuclear data elsewhere on your machine or from public sources on the internet.

Conda Install Instructions

On mac and linux PyNE can be installed via the package manager conda. After installing anaconda or miniconda from http://continuum.io/downloads add conda's binary directory to your bash profile by adding:

export PATH=/path/to/anaconda/bin:$PATH

to your .bashrc or .bash_profile. Then in a new shell:

conda install conda-build jinja2 nose setuptools pytables hdf5 scipy

on linux you may also need to run:

conda install patchelf
Then dowload the latest conda-recipes:
https://github.com/conda/conda-recipes/archive/master.zip

cd to the conda-recipes directory and run:

conda build pyne
conda install $(conda build --output pyne)
nuc_data_make

Mac OSX Specific Instructions

These instructions are based on using the homebrew http://brew.sh/ package manager Install command line tools from https://developer.apple.com/downloads/ you will need to create an account in order to download:

ruby -e "$(curl -fsSL https://raw.github.com/mxcl/homebrew/go/install)"
brew doctor
brew tap homebrew/science
brew install hdf5
brew install cmake
brew install python

Add:

export PATH=/usr/local/bin:$PATH
export PATH=/usr/local/share/python:$PATH

to ~/.bash_profile, then:

source ~/.bash_profile
sudo pip install numpy
sudo chown -R $(whoami) /usr/local
brew install gfortran
pip install scipy
pip install cython
pip install numexpr
pip install tables

download pyne-staging cd to that directory:

cd Downloads/pyne-staging
python setup.py install

Once those lines have been added, run the following command before running nuc_data_make:

source ~/.bashrc

Contributing

We highly encourage contributions to PyNE! If you would like to contribute, it is as easy as forking the repository on GitHub, making your changes, and issuing a pull request. If you have any questions about this process don't hesitate to ask the mailing list (https://groups.google.com/forum/#!forum/pyne-dev, pyne-dev@googlegroups.com).

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