pybader (v0.3.12)

pybader is a threaded implementation of grid-based Bader charge analysis. It performs grid-based Bader charge analysis as presented in W Tang et al 2009 J. Phys.: Condens. Matter 21 084204. Methods have been updated to allow threading over multiple threads. It runs on POSIX systems, Mac OS, and Windows.

Usage

Installation will create 2 executeables (bader, bader-read) that can be used to run and read the output of the Bader calculation. To view available flags run:

$ bader --help
$ bader-read --help

By default the program bader will output a file called bader.p which is a pickled Bader object. This file can be interpreted by the bader-read script. Human readable files can also be created in place of the bader.p file by supplying the flag --output dat to the main bader program. If you would like this to be the default behaviour (bader.p files contain the entire charge denisty and voxel to Bader volume and/or atom map so can be quite large) there is a config.ini file with sections for all the configurable variables. The location of this varies depending on platform but can be found by checking the pybader.__config__ variable. The current default settings are shown below

[DEFAULT]
method = neargrid
refine_method = neargrid
vacuum_tol = None
refine_mode = ('changed', 2)
bader_volume_tol = 0.001
export_mode = None
prefix = ''
output = pickle
threads = 1
fortran_format = 0
speed_flag = False
spin_flag = False

Check the examples folder and function doc strings for information on how to interface with the python module.

import pybader
from pybader import (
    methods,
    refinement,
    thread_handlers,
    interface,
)
import pybader.io
from inspect import getmembers, ismodule

help(pybader)
help(methods)
help(refinement)
help(thread_handlers)
help(interface)

for name, module in getmemebers(pybader.io, ismodule):
    help(module)

Requirements

pyBader requires a small number of open source projects to work properly, if using pip to install they should be installed automatically:

• Numpy - NumPy is the fundamental package for scientific computing with Python.
• Numba - A Just-In-Time Compiler for Numerical Functions in Python.
• tqdm - A Fast, Extensible Progress Bar for Python and CLI.
• pandas - A Library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Installation

It's recommended to create a virtual python environment for the installation using a manager of your choice, this is optional and the docuemented manager is pyenv:

$ pyenv virtualenv pybader
$ pyenv activate pybader

Then the package can be installed using one of the methods described below:

Pip

Use the standard pip installer

$ pip install pybader

From source

Clone the repositry and make sure setuptools is installed

$ git clone https://github.com/kerrigoon/pybader
$ python pybader/setup.py install

Development

Want to contribute? Great! Open your favorite Terminal and run these commands.

$ git clone https://github.com/kerrigoon/pybader
$ pip install -e pybader/

Fiddle away and submit pull requests.

License

MIT