This example will generate a potential for tantalum as published in Thompson, A.P. et. al, J. Comp. Phys. 285 (2015) 316-330. This version of the tantalum potential uses the linear version of SNAP.

To run this example, use the following command in this directory:

python -m fitsnap3 Ta-example.in

Ta-example.in

Input file containing parameters to run FitSNAP and generate the tantalum potential

JSON/

Directory that contains all the training configurations which are organized into different groups.

Ta_pot.snapcoeff

SNAP potential coefficient file that contains all the beta coefficients for this potential. This is one of two files needed to use this potential in LAMMPS

Ta_pot.snapparam

SNAP potential parameters file that contains the hyperparameters and options used during the fit for this potential. This is one of two files needed to use this potential in LAMMPS

Ta_metrics.md

Contains a variety of error metrics for all the training groups for this fit.

Note that the 20May21_Standard/ directory contains sample output for this example

FitSNAP.df

Pickled pandas dataframe whose columns contain various quantities associated with the fit. For those unfamiliar with pandas dataframes, this file can be loaded in python with:

    import pandas as pd
    data = pd.read_pickle("FitSNAP.df")

and we can extract data using typical pandas dataframe attributes, for example:

    print(data.columns) # see which columns we have
    print(data["Row_Type"].values) # print the values of row types in the A matrix

rcutfac = 4.67637 : Radial cutoff (hyperparameters) chosen for this potential wj1 = 1.0 : Elemental weight on tantalum for density expansion radelem1 = 0.5 : Tantalum per-element cutoff type1 = Ta : Chemical symbol for element which should match training files in JSON quadraticflag = 0 : Quadratic SNAP is turned off, using linear SNAP

See docs/TEMPLATE.in for further information on input parameters

The JSON configurations and hyperparameters used for this example are published in:

Thompson, A. P., Swiler, L. P., Trott, C. R., Foiles, S. M., & Tucker, G. J. (2015). Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials. Journal of Computational Physics, 285, 316-330

Note to Developers: Make sure this example still reproduces the same results when modifying code

After running the example, use python compare_snapcoeff.py to calculate the max absolute difference in SNAP coefficients from the standard. The values should agree within a near zero amount (machine precision or close).