Metadata-Version: 1.2
Name: Febiss
Version: 0.9.0
Summary: Tool to ease GIST analysis and display and select FEBISS waters
Home-page: UNKNOWN
Author: Miguel Steiner
Author-email: steiner.mig@gmail.com
License: MIT
Description: Free Energy Based Identification of Solvation Sites (FEBISS)
        ============================================================
        
        Installation
        ------------
        
        FEBISS can be installed using pip (pip3) once the repository has been cloned:
        
        .. code-block:: bash
        
           git clone https://github.com/PodewitzLab/FEBISS.git
           pip install ./febiss
        
        A non super user can install the package using a virtual environment, or
        the ``--user`` flag.
        
        A manual with detailed instructions can be found in the Github repo.
        
        
        Prerequisites
        -------------
        
        Basic Requirements
        ..................
        
        FEBISS is expected to run on Linux systems and the following
        programs/packages are required:
        
        - Python3
        - Git
        - GCC >= v7.0.0
        
        Febiss Python Package
        .....................
        
        The main Python package called FEBISS requires only basic additional packages, which will 
        be automatically installed when installing FEBISS, using ``pip``. These packages are
        listed in the file ``requirements.txt``.
        
        C++ Requirements
        ................
        
        To run analyses of trajectories the open-source software CPPTRAJ modified with the GIGIST 
        repository is used. These dependencies are not necessary for the installation of FEBISS, 
        but rather FEBISS provides a script to set-up these dependencies via
        
        .. code-block:: bash
        
           febiss_setup
        
        Please be aware that CPPTRAJ may require libraries that cannot be installed via FEBISS, but 
        have to be installed by the user first. CPPTRAJ makes use of the following libraries:
        
        - NetCDF
        - BLAS
        - LAPACK
        - Gzip
        - Bzip2
        - Parallel NetCDF (-mpi build only, for NetCDF trajectory output in parallel)
        - CUDA (-cuda build only)
        - FFTW (mostly optional; required for PME functionality and very large FFTs)
        
        We therefore recommend to install some basic libraries via
        
        .. code-block:: bash
        
           sudo apt-get install libblas-dev liblapack-dev libbz2-dev libnetcdf-dev
        
        Should you encounter difficulties in the installation of CPPTRAJ, we refer to the README
        of the GIGIST and CPPTRAJ repositories.
        
        Basic Usage
        -----------
        
        If you installed FEBISS and its dependencies ``febiss_setup``, you can use FEBISS 
        to analyse trajectories for water placements, plot the data and select the waters you want 
        to further investigate within a bar chart.
        
        To get a list of all available options and a useful input file, you can call
        
        .. code-block:: bash
        
           febiss_settings
        
        This will place the file ``all-settings.yaml`` in your current directory. This input 
        file requires only 2 alterations to be a valid input file. You have to give the name of your 
        topology file and the base name of your trajectory file(s). Along those 2 mandatory settings 
        you find all other available settings both for the GIST analysis and the plotting of the retrieved 
        data. Once you performed the analysis, you can also skip this step and directly plot the data.
        The analysis and plotting are done via calling the main program along with the yaml input file:
        
        .. code-block:: bash
        
           febiss all-settings.yaml
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.6
