Metadata-Version: 1.1
Name: phenum
Version: 1.6.0
Summary: Enumeration of symmetrically unique derivative superstructures of crystals.
Home-page: https://github.com/wsmorgan/phonon-enumeration
Author: Wiley S Morgan
Author-email: wiley.s.morgan@gmail.com
License: MIT
Description: [![PyPI](https://img.shields.io/pypi/v/fortpy.svg)](https://pypi.python.org/pypi/phenum/) [![Build Status](https://travis-ci.org/wsmorgan/phonon-enumeration.svg?branch=master)](https://travis-ci.org/wsmorgan/phonon-enumeration)
        
        # phonon-enumeration
        
        This code is used to enumerate all the derivative structures of a
        system within a crystalographic system within specified concentration
        and cell size ranges. The code uses a newly developed group theoretic
        approach that is extremely efficient and can include the enumeration
        of displacement directions, or arrow directions, within a system.
        
        ## Prerequisites
        
        The code currently requires a modified version of the previous
        enumeration code, available at https://github.com/msg-byu/enumlib, to
        run. To make this modified code do the following, get the symlib library:
        
        ```
        git clone https://github.com/msg-byu/symlib.git
        cd symlib/src/
        make F90=(your compiler, gfortran or ifort)
        cd ../../
        ```
        
        Then get a copy of enumlib:
        
        ```
        git clone https://github.com/msg-byu/enumlib.git
        ```
        
        Now copy the Makefile, derivative_structure_generator.f90, and
        wrapper.f90 from the phonon-enumeration/support directory to the
        enumlib/src/ directory. Now we can make the enum.x executable and
        place it in our path:
        
        ```
        cd enumlib/src/
        make F90=(your compiler) enum.x
        cp enum.x /bin/.
        ```
        
        In order for enum.x to run you will need to have its input folder
        struct_enum.in, an example of which can be found in the input folder,
        for the system you desire to model. You may then choose to run enum.x
        yourself to generate the needed input files by typing:
        
        ```
        enum.x
        ```
        
        This will now generate a number of files titled cell_# where # is the
        cell size. These files contain the information needed to run the new
        enumeration code. If you do not run enum.x the enumeration.py code
        will execute it for you as long as its in your path. The input files
        are setup so that each HNF with it's SNF and left transform (as
        described in http://msg.byu.edu/papers/multi.pdf and
        http://msg.byu.edu/papers/GLWHart_enumeration.pdf) are listed in a
        file titeled matrices:
        
        ```
          #n	SNF		   HNF			          left transform
           1  1  1  4    1  0  1  0  0  4      1    0    0    0    1    0    0    0    1
           1  1  1  4    1  0  1  0  1  4      1    0    0    0    1    0    0   -1    1   
        ```
        
        The first digit indicates which of the group.n files contains the
        symmetry group for that system. As can be seen only the diagonals of
        the SNF and lower traingular entries of the HNF should be included in
        this file. The group.n files contain the permutations of the sites on
        the lattice that constitute the symmtery group.
        
        ## Installing the code
        
        To install the code use the following command in the
        phonon-enumeration directory:
        
        ```
        python setup.py install
        ```
        
        ## Running the code
        
        You now have everything you need to run the new enumeration code. You
        have two options for how to proceed. First the algorithm can use the
        burnside polya algorithm to predict the number of unique structures
        that exist for each HNF and symmetry group produced. This mode is run
        as follows:
        
        ```
        enumeration.py -polya
        ```
        
        and expects a file called lattice.in an example of which can be found
        in the input folder. This mode produces a file for each cell size that
        lists the number of unique configurations for each HNF at every
        possible concentration range for the cell size. This data can be very
        useful when modeling large systems as it will allow the user to select
        an appropriate distribution of structures to use given the number of
        each type available.
        
        The second option is the actual enumeration of derivative
        structures. This mode is run using:
        
        ```
        enumeration.py -enum
        ```
        
        and expects a file called enum.in which can also be found in the input
        folder. The enum.in folder should contain a list of the desired HNFs,
        their concentration ranges, and the number of arrangements for the HNF
        concetrtaion range pair the user would like. For example:
        ```
        # HNF                           Conc.       Number
          1 0 1 0 2 11                  8 3         2
          1 0 1 3 4 8                   4 4         1
          1 0 1 1 4 11                  6 5         3
          1 0 1 0 0 10                  6 4         2
          1 0 1 1 5 10                  8 2         1
          1 0 1 1 2 10                  7 3         1
          1 0 1 0 3 11                  7 4         3
          1 0 1 0 2 9                   5 4         2
        ```
        
        ## Python Packages Used
        
        The enumeration.py code require the following python packages to run:
        
        - numpy
        
        - pyparsing
        
        - termcolor
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python
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
