Metadata-Version: 2.1
Name: atooms-pp
Version: 2.1.0
Summary: Post-processing tools for particle simulations
Home-page: http://www.coulomb.univ-montp2.fr/perso/daniele.coslovich/
Author: Daniele Coslovich
Author-email: daniele.coslovich@umontpellier.fr
License: GPLv3
Description: Post processing
        ===============
        
        Python post processing tools to compute static and dynamic correlation
        functions from particle simulations
        
        -  Real space: radial distribution function, mean square displacement,
           time-dependent overlap functions, non-Gaussian parameter
        -  Fourier space: structure factor, intermediate scattering functions,
           four-point dynamic susceptibility
        
        This package relies on
        `atooms <https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing.git>`__
        to read trajectory files.
        
        Quick start
        -----------
        
        Installation is easy (see `Installation <#installation>`__ for more
        details)
        
        ::
        
           pip install atooms-pp
        
        We can now compute correlation functions from trajectories produced by
        particle simulation codes. Any trajectory format recognized by atooms
        can be processed, for instance most “xyz” files should work fine.
        
        As an example, we compute the structure factor S(k) for the trajectory
        file ``trajectory.xyz`` contained in the ``data/`` directory.
        
        .. figure:: https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing/raw/develop/docs/anim.gif
           :alt: https://www.coulomb.univ-montp2.fr/perso/daniele.coslovich/anim.gif
        
           https://www.coulomb.univ-montp2.fr/perso/daniele.coslovich/anim.gif
        
        In the example above, we used 20% of the available time frames to
        compute the averages using the ``--norigins`` flag. Without it,
        atooms-pp applies an heuristics to determine the number of time frames
        required to achieve a reasonable data quality.
        
        The results of the calculation are stored in
        ``data/trajectory.xyz.pp.sk``. If the system is a mixture of different
        types of particles, say A and B, the program will create additional
        files for partial correlations, named ``trajectory.xyz.pp.sk.A-A``,
        ``trajectory.xyz.pp.sk.B-B`` and ``trajectory.xyz.pp.sk.A-B``.
        
        The same calculation can be done from python:
        
        .. code:: python
        
           from atooms.trajectory import Trajectory
           import atooms.postprocessing as pp
        
           with Trajectory('data/trajectory.xyz') as t:
                p = pp.StructureFactor(t)
                p.do()
        
        Checkout the
        `tutorial <https://www.coulomb.univ-montp2.fr/perso/daniele.coslovich/pp_notebook/>`__
        and
        `notebook <https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing/raw/develop/docs/tutorial.ipynb>`__
        for more details.
        
        Requirements
        ------------
        
        -  `numpy <https://pypi.org/project/numpy/>`__
        -  `atooms <https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing.git>`__
        -  [optional] `argh <https://pypi.org/project/argh/>`__ (only needed
           when using ``pp.py``)
        -  [optional] `tqdm <https://pypi.org/project/tqdm/>`__ (enable progress
           bars)
        -  [optional] `argcomplete <https://pypi.org/project/argcomplete/>`__
           (enable tab-completion for ``pp.py``)
        
        Installation
        ------------
        
        If you cannot install the package system-wide, you can still install it
        in the user space. Either from pypi
        
        ::
        
           pip install --user atooms-pp
        
        or cloning the project repo
        
        ::
        
           git clone https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing.git
           cd postprocessing
           make user
        
        The commands above will install ``pp.py`` under ``~/.local/bin``. Make
        sure this folder is in your ``$PATH``. To install system-wide,
        ``sudo make install``.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Physics
Description-Content-Type: text/markdown
