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        "author": "\u00c5smund Ervik",
        "author_email": "aaervik@gmail.com",
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            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Chemistry",
            "Topic :: Scientific/Engineering :: Physics"
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        "description": "##########################################################\nraaSAFT - coarse grained SAFT-gamma Mie molecular dynamics\n##########################################################\n\n- raaSAFT (pronounced \"raw saft\") is a Python framework that makes it easy to set up coarse-grained molecular dynamics simulations.\n- raaSAFT runs with HOOMD-blue as a backend, so you can use GPU power. Initial support for using GROMACS has been added.\n- raaSAFT uses the SAFT-gamma Mie force field, a powerful coarse-graining method\n  that gives accuracy comparable to atomistic models, with runtimes that are\n  orders of magnitude shorter.\n- Raasaft is a Norwegian word meaning \"pure fruit syrup\". Apart from the obvious saft <-> SAFT pun, \"raa\" means crude/raw/coarse, so it is twice as punny.\n\nInstallation\n============\n\n**Dependencies:**\n\n- raaSAFT uses HOOMD-blue, see the `HOOMD-blue install guide <https://codeblue.umich.edu/hoomd-blue/doc/page_install_guide.html>`_.\n- For now this is a dependency even if you want to run with GROMACS. The non-GPU version of HOOMD-blue is sufficient.\n- Note that HOOMD-blue runs on Linux or Mac OSX. Windows is not supported.\n\n**Simple installation:**\n\n.. code-block:: bash\n\n   pip install raasaft\n\n   # or to upgrade\n   pip install --upgrade raasaft\n\n   # To start using raaSAFT:\n   mkdir raasaft && cd raasaft\n   raasaft_init\n   # You now have the helpful directories tutorials/ replication/ and mysaft/\n   ls\n\n   # Read the \"Running simulations\" section below.\n\n**Installation for advanced users / contributors:**\n\n- Install dependencies. This includes HOOMD-blue and the Python packages `future` and `requests`.\n- Clone the repo at http://bitbucket.org/asmunder/raasaft\n    - The `maint` branch should be as stable as the version on PyPi\n    - The `master` branch changes frequently and may not always be stable\n- You probably want to add the repo directory to your PYTHONPATH.\n\nRunning simulations with raaSAFT\n================================\n\n- Look at the README.txt file in `raasaft/tutorials/` for examples of how to use raaSAFT. \n- In `raasaft/replication/` we include setups that can be used to replicate the findings of various papers.\n- In `raasaft/mysaft/` you find an example of how to add your own models for new molecules.\n    - You can use these user-defined models with e.g.  \n\n.. code-block:: python\n\n      from mysaft.example import Example\n      ex = Example(count=1e3)\n\n- If you want to use these models in jobscripts in different directories, add the full path to the `raasaft` folder to your `PYTHONPATH` shell variable (put this in your `.bashrc` file to make it permanent), e.g.:  \n      `export PYTHONPATH=$PYTHONPATH:\"/path/to/raasaft\"`\n- Contributions to raaSAFT with new models are always welcome, assuming the model has seen at least some level of validation.\n\nBottled SAFT\n============\n\nYou can get models (force field parameters) for 6000+ molecules from our database called Bottled SAFT: \n\nhttp://www.bottledsaft.org \n\nThis web application provides scripts that implement the search result in raaSAFT for you!\n\nLicense\n=======\n\nThe code is Free and Open Source software under the MIT license.\n\nContribute\n==========\n\nAll contributions are welcome!\n\nContact\n=======\n\nEmail Aasmund at aaervik@gmail.com",
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        "keywords": "molecular dynamics GPU SAFT Mie HOOMD",
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