CCS - Curvature Constrained Splines

The CCS package is a tool to construct two-body potentials using the idea of curvature constrained splines.

Getting Started

Package Layout

ccs-0.1.0
├── bin
│   ├── atom-json               
│   └── ccs_fit                 
├── ccs
│   ├── __init__.py                     
│   ├── main.py                 
│   ├── objective.py            
│   └── spline_functions.py     
├── examples
│   ├── Ne-FCC
│   │   ├── input.json          
│   │   └── structures.json     
│   └── O2
│       ├── input.json
│       └── structures.json
├── LICENSE
├── README.md
└── setup.py

• atom-json-A tool to convert OUTCAR (VASP output) files to structures.json
• ccs_fit - The executable file for ccs package.
• main.py - A module to parse input files.
• objective.py - A module which contains the objective function and solver.
• spline_functions.py - A module for spline construction/evaluation/output.

Prerequisites

You need to install the following softwares

pip install numpy
pip install scipy
pip install ase
pip install cvxopt

Installing from source

Git clone

git clone git@github.com:aksam432/CCS.git
cd CCS
python setup.py install

Environment Variables

Set the following environment variables:

$export PYTHONPATH=<path-to-CCS-package>:$PYTHONPATH
$ export PATH=<path-to-CCS-bin>:$PATH

Tutorials

We provide two tutorials in the examples folder. To run the example, go to one of the folders ( O2 or Ne-FCC ). Each contain two primary input files required for fitting. A sample input.json for O2 is shown below:

{

"Twobody":{
	"O-O":{
		"Rmin":0.95,   
		"Rcut":2.5,
		"Nknots":20

	}
	},

"Onebody":["O"],

"Reference":"structures.json"
			
}

The input.json file should provide spline interval cutoff's (Rcut and Rmin), number of knots (Nknots), and path to the structure.json file. The onebody energy terms should be provided as a json array using atomic symbols. The format for structure.json is shown below :

{
        "S1": {
                "Energy": -4.22425752,
                "Atoms": {
                        "O": 2
                },
                "O-O": [
                        0.96
                ]
        },
        "S2": {
                "Energy": -5.29665634,
                "Atoms": {
                        "O": 2
                },
                "O-O": [
                        0.98
                ]
        },
        "S3": {
                "Energy": -6.20910363,
                "Atoms": {
                        "O": 2
                },
                "O-O": [
                        1.0
                ]
        },
        "S4": {
                "Energy": -6.98075271,
                "Atoms": {
                        "O": 2
                },
                "O-O": [
                        1.02
                ]
        }
}

The structure.json file contains different configurations labeled ("S1", "S2"...) and corresponding energy, pairwise distances (contained in an array labelled as "O-O" for oxygen). The stoichiometry of each configuration is given under the atoms label (" Atoms") as a key-value pair ("O" : 2 ).

To perform the fit :

ccs_fit

The following output files are obtained:

splines.out error.out ccs.log summary.png 

• splines.out - Contains the spline coefficients for two body potential.
• error.out - Contains target energies, predicted energies and absolute error for each configuration.
• ccs.log - Contains debug information
• summary.png - Plot showing fit quality, selected spline coefficients, and distance histogram.

Authors

• Akshay Krishna AK
• Jolla Kullgren
• Eddie Wadbro

License

This project is licensed under the GPLv3 License - see the LICENSE file for details.

Acknowledgement

We thank all the members of TEOROO-group at Uppsala University, Sweden.