Metadata-Version: 2.1
Name: freud-analysis
Version: 0.10.0
Summary: Perform various analyses of particle simulations.
Home-page: http://bitbucket.org/glotzer/freud
License: UNKNOWN
Description: # freud
        
        [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.166564.svg)](https://doi.org/10.5281/zenodo.166564)
        [![Anaconda-Server Badge](https://anaconda.org/conda-forge/freud/badges/version.svg)](https://anaconda.org/conda-forge/freud)
        [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/glotzerlab/freud-examples/master?filepath=index.ipynb)
        [![ReadTheDocs](https://readthedocs.org/projects/freud/badge/?version=latest)](https://freud.readthedocs.io/en/latest/?badge=latest)
        [![Codecov](https://codecov.io/bb/glotzer/freud/branch/master/graph/badge.svg)](https://codecov.io/bb/glotzer/freud)
        
        The freud library provides users the ability to analyze molecular dynamics and Monte Carlo simulation trajectories
        for advanced metrics such as the radial distribution function and various order parameters. Its modules work with
        and return NumPy arrays, and are able to process both 2D and 3D data. Features in freud include computing the radial
        distribution function, local density, hexagonal order parameter and local bond order parameters,
        potentials of mean force and torque (PMFTs), Voronoi tessellations, and more.
        
        When using freud to process data for publication, please [use this citation](https://doi.org/10.5281/zenodo.166564).
        
        ## Mailing List
        
        If you have a question, please consider posting to the
        [freud-users mailing list](https://groups.google.com/forum/#!forum/freud-users).
        
        ## Examples
        
        Example Jupyter notebooks can be found in a [separate repository](https://bitbucket.org/glotzer/freud-examples).
        These notebooks may be launched [interactively on Binder](https://mybinder.org/v2/gh/glotzerlab/freud-examples/master?filepath=index.ipynb)
        or downloaded and run on your own system.
        
        ## Installing freud
        
        Official binaries of freud are available via [conda](https://conda.io/docs/) through [conda-forge](https://conda-forge.org/).
        To install freud, first download and install [miniconda](https://conda.io/miniconda.html) following
        [conda's instructions](https://conda.io/docs/user-guide/install/index.html).
        Then install freud:
        
        ```bash
        $ conda install -c conda-forge freud
        ```
        
        ## Compiling freud
        
        Building freud from source follows the typical setuptools pattern for Python packages:
        
        ```bash
        git clone --recurse-submodules https://bitbucket.org/glotzer/freud.git
        cd freud
        python setup.py install
        ```
        
        By default, freud installs to the [USER_SITE](https://docs.python.org/3/install/index.html) directory, which is in `~/.local` on Linux and in `~/Library` on macOS.
        `USER_SITE` is on the Python search path by default, so there is no need to modify `PYTHONPATH`.
        
        If you want to test freud without installing it for your system, you can instead build it in place.
        
        ```bash
        python setup.py build_ext --inplace
        ```
        
        For more detailed instructions, see [the documentation](https://freud.readthedocs.io).
        
        #### Note
        
        The freud library makes use of submodules.
        If you would like to update submodules yourself, please execute the following command after cloning:
        
        ```bash
        git submodule update --init
        ```
        
        ### Requirements
        
        * Required:
            * Python >= 2.7 (3.5+ recommended)
            * NumPy >= 1.7
            * C++11 capable compiler (tested with gcc >= 4.8.5, clang 3.5)
            * Intel Threading Building Blocks
        * Optional:
            * Cython >= 0.23 (to compile your own `_freud.cpp`)
        
        ## Job scripts
        
        The freud library is called using Python scripts.
        
        Here is a simple example.
        
        ```python
        import freud
        
        # create a freud compute object (rdf is the canonical example)
        rdf = freud.density.rdf(rmax=5, dr=0.1)
        # load in your data (freud does not provide a data reader)
        box_data = np.load("path/to/box_data.npy")
        pos_data = np.load("path/to/pos_data.npy")
        
        # create freud box
        box = freud.box.Box(Lx=box_data[0]["Lx"], Ly=box_data[0]["Ly"], is2D=True)
        # compute RDF
        rdf.compute(box, pos_data[0], pos_data[0])
        # get bin centers, rdf data
        r = rdf.getR()
        y = rdf.getRDF()
        ```
        
        ## Documentation
        
        The documentation is available online at [https://freud.readthedocs.io](https://freud.readthedocs.io).
        
        To build the documentation yourself, please install sphinx:
        
            conda install sphinx
        
        OR
        
            pip install sphinx
        
        To view the full documentation run the following commands in the source directory:
        
        ```bash
        # Linux
        cd doc
        make html
        xdg-open build/html/index.html
        
        # Mac
        cd doc
        make html
        open build/html/index.html
        ```
        
        If you have latex and/or pdflatex, you may also build a pdf of the documentation:
        
        ```bash
        # Linux
        cd doc
        make latexpdf
        xdg-open build/latex/freud.pdf
        
        # Mac
        cd doc
        make latexpdf
        open build/latex/freud.pdf
        ```
        
        ## Unit Tests
        
        The unit tests for freud use the Python `unittest` framework:
        
        ```bash
        # Run tests from the tests directory
        cd tests
        python -m unittest discover .
        ```
        
Platform: UNKNOWN
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*
Description-Content-Type: text/markdown
